Dynamic Simulation of
Gas-Lift Wells and
Systems
API RECOMMENDED PRACTICE 19G11 (RP 19G11)
DRAFT #12, January 15, 2011
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Copyright @ l993 American Petroleum Institute
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 1
Foreword
This Recommended Practice (RP) is under the jurisdiction of the API Committee on
Standardization of Production Equipment (Committee 19).
This document presents Recommended Practices for Dynamic Simulation of Gas-Lift Wells and
Systems. Other API Specifications, API Recommended Practices, and Gas Processors Suppliers
Association (GPSA) documents may be referenced and should be used for assistance in design
and operation.
API Recommended Practices may be used by anyone desiring to do so, and diligent effort has
been made by the Institute to assure the accuracy and reliability of the data contained therein.
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Copyright © 2009 American Petroleum Institute
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 2
Policy
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API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 3
TABLE OF CONTENTS
API................................................................................................................................................................... 1
AMERICAN PETROLEUM INSTITUTE ................................................................................................................ 2
PRODUCTION DEPARTMENT ....................................................................................................................................... 2
API ................................................................................................................................................................... 2
COPYRIGHT @ L993 AMERICAN PETROLEUM INSTITUTE ................................................................................................. 2
FOREWORD ..................................................................................................................................................... 1
POLICY ............................................................................................................................................................. 2
TABLE OF CONTENTS........................................................................................................................................ 3
TERMS AND ABBREVIATIONS ........................................................................................................................... 5
ABBREVIATIONS USED IN THIS DOCUMENT, AND THEIR MEANINGS ............................................................. 11
DYNAMIC SIMULATION OF GAS-LIFT WELLS AND SYSTEMS ........................................................................... 14
1.
2.
3.
4.
5.
API RP 19G11 ............................................................................................................................................ 14
Introduction .................................................................................................................................................. 14
SUMMARY OF RECOMMENDED PRACTICES FOR DYNAMIC SIMULATION OF GAS-LIFT WELLS AND SYSTEMS ..................... 15
INTRODUCTION TO DYNAMIC SIMULATION OF GAS-LIFT WELLS AND SYSTEMS .......................................................... 33
Document Objectives .................................................................................................................................... 33
Dynamic Simulation - Definition and Basic Concepts ................................................................................... 34
Difference between Steady-State and Dynamic Simulation Techniques ...................................................... 44
TYPICAL GAS-LIFT WELL AND SYSTEM OPERATIONS ............................................................................................. 50
Continuous gas-lift ........................................................................................................................................ 50
Intermittent gas-lift ...................................................................................................................................... 53
Gas-assisted plunger lift ............................................................................................................................... 56
Dual gas-lift .................................................................................................................................................. 58
Single-point gas-lift ....................................................................................................................................... 61
Auto gas-lift .................................................................................................................................................. 62
Riser gas-lift .................................................................................................................................................. 63
Gas-lift for gas well deliquification ............................................................................................................... 64
Gas-lift unloading ......................................................................................................................................... 65
Use of gas-lift for well kick-off ...................................................................................................................... 66
Use of gas-lift for wellbore clean-up ............................................................................................................. 67
Gas-lift system distribution ........................................................................................................................... 67
Use of un-dehydrated gas ............................................................................................................................. 68
Use of non-hydrocarbon gases such as CO2 and N2 ...................................................................................... 68
Naturally Flowing Gas-Lift Wells .................................................................................................................. 69
RECOGNIZE WHEN DYNAMIC SIMULATION IS BENEFICIAL ...................................................................................... 70
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 4
Use dynamic simulation to determine and respond when a well or system may be unstable. .................... 70
Use dynamic simulation to determine when to use gas-lift to re-start wells. .............................................. 72
Use dynamic simulation to determine when to start gas-lift in a flowing well. ........................................... 73
Use dynamic simulation to determine the need to start gas-lift due to liquid loading in gas wells. ............ 74
Use dynamic simulation to aid in optimizing intelligent and complex well completions. ............................. 78
Use dynamic simulation to aid in understanding when cross flow and/or commingling occur. .................. 81
Use dynamic simulation to optimize gas-lift well and system shut-in and start-up operations. .................. 83
6. INFORMATION REQUIRED FOR DYNAMIC SIMULATION .......................................................................................... 87
Fluid properties ............................................................................................................................................. 87
Well Profile and Well Schematic ................................................................................................................... 89
Inflow performance relationship .................................................................................................................. 90
Boundary Conditions ..................................................................................................................................... 91
7. APPLICATION OF DYNAMIC SIMULATION ............................................................................................................ 92
Integrated modelling .................................................................................................................................... 92
Real-time modelling ...................................................................................................................................... 93
Use of dynamic simulation modelling for gas-lift system management ...................................................... 95
Appropriate dynamic simulation techniques and their implementation ...................................................... 98
8. INFORMATION PROVIDED BY DYNAMIC SIMULATION .......................................................................................... 105
Slugging flow: ............................................................................................................................................. 105
Water effects on corrosion and hydrates: .................................................................................................. 110
Production chemistry: ................................................................................................................................. 126
Gas-lift valve performance: ........................................................................................................................ 131
Well equipment: ......................................................................................................................................... 139
Well design: ................................................................................................................................................ 143
9. CASE HISTORIES .......................................................................................................................................... 147
Case History 1: Penguins Gas-Lift ............................................................................................................... 147
THE PHASES OF CLEARING MEG FROM THE GAS-LIFT LINE AND CROSSOVERS, AND THE UNLOADING OF THE BASE OIL FROM THE
ANNULI WERE MODELLED IN AN ITERATIVE FASHION TO DETERMINE THE REQUIRED PROCEDURES TO REMAIN WITHIN THE SYSTEM
LIMITATIONS. ...................................................................................................................................................... 149
Case History 2: Transient Gas-Lift Analysis in ERD and non-ERD Wells ...................................................... 150
10.
REFERENCES .......................................................................................................................................... 167
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 5
Terms and Abbreviations
Terms Used in this Document, and Their Definitions
1. Beaning up:
The process of increasing the wellhead choke size to adjust
the flow rate.
2. Black oil correlations:
The black-oil model assumes that the reservoir fluids
consist of three phases: oil, water, and gas. These are
defined with a minimum of information (specific gravity,
gas-oil ratio, and water cut), with gas dissolving in oil and
oil vaporizing in gas. Water is assumed to be inert. Use
correlations to determine the fluid properties at different
pressures and temperatures (P-T).
3. Boundary conditions:
The fluid type, flow rate, pressure, and temperature values
assigned to the selected model boundaries (inputs, outputs,
and surrounding environment of the model) used in solving
the differential equations that apply to dynamic simulation.
4. Bull heading:
This is a process to forcibly pump fluids into a wellbore to
stop the well from flowing.
5. Commingling:
This is a process where fluids from different productive
formations are combined and produced them through a
single conduit.
6. Cross flow:
This describes the flow of reservoir fluids from one
productive formation into another.
7. de Waard Model:
This is a CO2 corrosion model that is commonly used in
Industry.
8. Distributed IPR:
This methodology is used to divide the reservoir’s
productive intervals into zones and calculating individual
IPR’s for each separate zone.
9. Drift-flux models:
This is a model that treats the two phases as a mixture.
Gas is assumed to be drifting along with liquid and the gas
velocity can be described by a slip relation.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 6
10. Dry tree:
This describes wellhead equipment that is not in contact
with the sea water. It has all tree components housed in a
chamber or encapsulated by a subsea vessel, or it is
located in a production/drilling platform using a dry tree
riser.
11. Dynamic simulation:
This refers to multiphase flow transient numerical
simulation.
12. Dynamic water and gas coning: This refers to the change in oil-water or gas-oil interface
profiles in the near wellbore area as a result of reservoir
pressure depletion during production life , and/or as a result
of drawdown on wellbore production pressure above a
critical value.
13. Field life cycle:
This refers to changes in operating conditions from the
moment the field is opened to production until it is closed
and abandoned.
14. Flashing:
This refers to the process of rapidly reducing the pressure
of a hydrocarbon sample to lower pressure and
temperature in steps to determine its components at each
step.
15. Flow assurance:
This refers to ensuring successful and economical flow of
hydrocarbon streams from the reservoir to the point of sale.
16. Flow regime:
This is the prevailing gas, oil, and water geometrical
distribution when flowing through a pipe.
17. Flow regime classes:
These are the common flow regimes for gas-liquid mixtures
such as bubble flow, dispersed bubble flow, plug flow, slug
flow, froth flow, mist flow, churn flow, and annular flow.
18. Forchheimer IPR model:
This is an inflow performance relationship model developed
by Forchheimer and widely accepted and applied in gas
wells.
19. Hydrates:
Gas hydrates are solid ice-like crystalline compounds
formed by water and natural gas molecules at high
pressures and low temperatures.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 7
20. Hydrodynamic slugging:
These slug flow conditions are caused by gas flowing at a
fast rate over a slower flowing liquid phase. The gas will
form waves on the liquid surface, which may grow to bridge
the whole cross-section of the line. This creates a blockage
on the gas flow, which travels as a slug through the line.
21. Intelligent wells:
This refers to well completions where data recording and
well control can be perform remotely. A well equipped with
monitoring equipment and flow control components can be
adjusted to optimize production remotely, either
automatically or with operator intervention.
22. Joule Thompson cooling:
The Joule–Thomson effect describes the temperature
change of a gas when it is forced through a valve or porous
medium while the entire system is kept insulated so that no
heat is exchanged with the environment. The change may
be positive or negative. For each gas, there is an inversion
point that depends on P-T, below which it is cooled and
above which it is heated. The magnitude of the change of
temperature with pressure depends on the Joule-Thomson
coefficient for each particular gas. The Joule-Thomson
effect often causes a temperature decrease as gas flows
through pores of a reservoir to the wellbore. At room
temperature, all gases except hydrogen, helium, and neon
cool upon expansion by the Joule-Thomson process.
23. Kick-off:
This refers to bringing an off production well back to
production when there are only formation fluids in the
wellbore.
24. Kick-off water cut limit:
This is the water cut critical value that does not allow a
natural flowing well to start without gas-lift. Above the water
cut limit, the right amount of gas lift gas needs to be
injected to start production.
25. Liquid hold up:
This refers to the liquid stored in well and flowlines at
certain production conditions. When gas flows at a greater
velocity than the liquid, slippage takes place and liquid hold
up occurs.
26. Mechanistic models:
These mathematical models describe the multiphase flow
mechanisms (including related fluid properties and physical
relationships) using physical flow equations for each of the
phases within the system.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 8
27. Multi-lateral completions:
These are well completions which have more than one
wellbore branch radiating from the main borehole.
28. Multi-layer completions:
These are well completions that have more than one
producing reservoir layer.
29. Multi-pointing:
This refers to the situation where gas-lift injection gas
enters the production stream from more than one point.
30. Non-Darcy skin:
This refers to a rate dependant skin effect which is due to
turbulent flow conditions taking place near the wellbore.
The fluid flow in this case deviates from Darcy's law, which
assumes laminar flow in the reservoir. Non-Darcy turbulent
flow and associated skin are typically observed in high-rate
gas wells when the flow converging to the wellbore reaches
flow velocities exceeding the Reynolds number for laminar
flow.
31. NORSOK M-506 model:
This refers to a CO2 corrosion model that is commonly used
in Industry.
32. Quasi-dynamic IPR:
This is an inflow production relationship (IPR) model where
variables such as pressure, temperature, permeability, and
skin can be input as time-series.
33. Real-time modelling:
Real-time data captured by a Supervisory Control and Data
Acquisition (SCADA) systems is input in a dynamic
simulator which is used to monitor, advise, and control the
production/injection system to obtain optimum flow
assurance and production. The main objective in
developing the on-line model is to decrease the operational
cost of the system by optimizing production, by improving
the rules used to control the inflow into the wellbore, and by
decreasing the time necessary to model required
alternatives to select an optimum.
34. Riser gas-lift:
This refers to the process where gas-lift injection gas is
injected at the base of the riser.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 9
35. Snake-type wells:
This is a horizontal wellbore profile which has frequent up
and down slope sections.
36. Slugging flow:
This refers to a multiphase flow regime characterized by a
series of liquid plugs (slugs) separated by relatively large
gas bubbles. In severe slugging conditions, the gas bubble
occupies almost the entire cross-sectional area of the pipe.
The resulting flow alternates between high-liquid and highgas composition zones.
37. Steady state simulation:
These simulations are designed to give insight into the
steady-state behavior of the system by using a dynamic
simulator. When opening the well to production, the time
required to obtain steady state conditions is calculated and
the values of the key variables (P-T and rate) are validated.
Also, the simulation runs will indicate if no steady state
conditions are reached.
38. Sub-surface safety valve:
This is a valve installed at a certain depth in the wellbore
that can be closed remotely to isolate the tubing above the
valve and wellhead from reservoir fluids in an emergency or
planned shutdown.
39. Superficial velocity:
This refers to the velocity of a single component (oil, water,
gas) in a multi-component flowing situation, taking into
account the full cross-sectional area of the pipe.
40. Terrain-induced slugging:
This refers to a slugging condition generated by changing
elevations in the pipeline which follow the ground, seabed,
and/or riser. Liquid can accumulate at low points of the
pipeline until sufficient pressure builds up behind it. Once
the liquid is pushed out of the low point, it will form a slug.
41. Thornhill-Craver equation:
This is a commonly accepted equation used to predict the
rate of gas passage through a given orifice size.
42. IFE “Top of Line” Model:
This is a CO2 corrosion model that focuses on the top of a
horizontal pipe.
It considers variations in water
condensation rates which have a larger effect on the
corrosion rate in the top of the line than variations in the
CO2 partial pressure.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 10
43. Transient flow:
This refers to flow where the velocity and pressure change
over time.
44. Unloading:
This refers to the process of displacing initial annular and/or
tubing fluids in the well when gas-lift injection gas is started.
45. Vogel IPR model:
This inflow performance relationship model, developed by
Jack Vogel, is widely accepted and applied in oil wells.
46. Wax gelation:
The deposit formed on the pipe wall is not purely solid wax,
but is in the form of a gel consisting of a network of solid
wax crystals, which traps a large amount of oil inside. This
gel deposit grows in thickness and also ages with time
because of the diffusion of the wax molecules from the oil
flowing toward the cold wall. Gels are defined as a
substantially dilute cross-linked system, which exhibits no
flow when in the steady-state. By weight, gels are mostly
liquid, yet they behave like solids due to a threedimensional cross-linked network within the liquid. It is the
cross links within the fluid that give a gel its structure
(hardness) and contribute to stickiness.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Abbreviations used in this Document, and Their Meanings
1 D Grid
One Dimension Grid
BHP
Bottom Hole Pressure
BHT
Bottom Hole Temperature
CCE
Constant Composition Expansion
CPU
Central Processing Unit
Cv
Valve Flow Coefficient
CVD
Constant Volume Depletion
DTHYD
Difference between Hydrate Formation Temperature and Fluid Temperature
E&P
Exploration and Production
EOS
Equation of State
EOT
End of Tubing
ERD
Extended Reach Drilling
ESP
Electrical Submersible Pumps
FEED
Front End Engineering Design
GL
Gas-Lift
GLV
Gas-Lift Valve
GLM
Gas-Lift Mandrel
GLR
Gas Liquid Ratio
GOR
Gas Oil Ratio
HDI
Hydraulic Diaphragm Insert pump
HIPPS
High Integrity Pressure Protection Systems
HTGC
High Temperature Gas Chromatography
ICD
Inflow Control Devices
ICV
Intelligent Control Valves
ID
Internal Diameter
IPC
Intake Pressure Curve
IPO
Injection Pressure Operated gas-lift valves
IPR
Inflow Performance Relationship
IRDV
Intelligent Remote Downhole Valve
k
Permeability
k-h
Permeability-Thickness
LCM
Lost Circulation Material
Page 11
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
LDHI
Low Dosage Hydrate Inhibitors
MD
Measured Depth
MEG
Mono Ethylene Glycol
MeOH
Methanol
MODU
Mobile Offshore Drilling Unit
n-D
Non-Darcy
NPV
Net Present Value
OD
Outside Diameter
O&G
Oil and Gas
PBR
Polished Bore Receptacle
PR78 SRK-P
Peng Robinson 1978, Soave-Redlich-Kwong, with Peneloux volume correction
Pcf
Casing Pressure
pH
Measure of Acidity or Alkalinity
Piod
Gas-Lift Valve Injection Pressure at Depth
PI
Productivity Index
PL
Plunger Lift
PPO
Production Pressure Operated gas-lift valve
Pres
Reservoir Pressure
Ptf
Tubing Pressure
P-T
Pressure-Temperature
PvoT
Gas-Lift Valve Opening Pressure at Temperature
PVT
Pressure-Volume-Temperature
Pwf
Flowing Bottom Hole Pressure
Qg
Gas flow rate
Qo
Oil flow rate
Qw
Water flow rate
SSD
Sliding Sleeve Door
SCADA
Supervisory Control and Data Acquisition
SSSV
Sub-Surface Safety Valve
SCSSV
Surface Control Sub-surface Safety Valve
STP
Standard Temperature and Pressure 101.3 kPa and 15.56 oC (14.7 psi and 60 °F)
TD
Total Depth
Tf
Fluid Temperature
THP
Tubing Head Pressure
Thyd
Hydrate formation Temperature
Tres
Reservoir Temperature
Trvl
Valve Stem Travel
Page 12
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
TVD
True Vertical Depth
TOL
Top of Line
VPC
Valve Performance Clearinghouse
WAT
Wax Appearance Temperature
WC
Water Cut
WGR
Water Gas Ratio
WHP
Well Head Pressure
WHT
Well Head Temperature
Page 13
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 14
Dynamic Simulation of Gas-Lift Wells and Systems
1. API RP 19G11
Introduction
This API Recommended Practice covers the application of dynamic simulation for gas-lift
wells and systems. Dynamic simulation is an important tool to assist in the design,
operation, surveillance, troubleshooting, and diagnosis of gas-lift processes. Most gas-lift
design and diagnosis programs have used steady-state models. This may lead to
inappropriate designs and inefficient operations because gas-lift wells and systems are
seldom steady. Gas-lift wells usually exhibit dynamic pressure and flow rate fluctuations. It
is important to understand the dynamic behavior of wells and systems so they can be more
appropriately designed, operated, and diagnosed.
Until recently, dynamic simulation systems were not readily available for use in industry, so
the Supplier/Manufacturer and User/Purchaser Companies were required to rely on steadystate models. However, within the last few years, dynamic simulation systems have become
more readily available, and their use has proven valuable in many instances. This is
especially important as gas-lift operations have become more challenging with extended
reach wells, deviated/horizontal wells, multi-lateral wells, deep water and sub-sea
completions, and long sub-sea flow lines and risers. These operations are expensive and it
is essential that they be designed and operated in an optimum fashion.
This document contains nine chapters to assist the gas-lift industry in understanding and
applying dynamic simulation for gas-lift wells and systems:
1. Summary of Recommended Practices for Dynamic Simulation of Gas-Lift Wells
and Systems. This contains a brief summary with cross references to the recommended
practices found in Chapters 2 – 7.
2. Introduction to Dynamic Simulation of Gas-Lift Wells and Systems. This describes
the objectives of the document, defines dynamic simulation and its basic concepts, and
describes the differences between steady-state and dynamic simulation.
3. Typical Gas-Lift Well and System Operations. This describes fifteen different typical
gas-lift well and system configurations and how dynamic simulation may be used to
enhance their design and operation.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 15
4. Recognize When Dynamic Simulation is Beneficial. This describes various typical
gas-lift well and system operating conditions or problems where dynamic simulation can
be used to better understand and design solutions.
5. Information Required for Dynamic Simulation. This describes the information that
needs to be available to successfully use dynamic simulation models.
6. Application of Dynamic Simulation. This describes specific applications where
dynamic simulation can be used to improve gas-lift well and system performance.
7. Information Provided by Dynamic Simulation. This presents some of the specific
information and results that can be provided by dynamic simulation models.
8. Case Histories. This provides a summary of relevant case histories where dynamic
simulation has been successfully employed for gas-lift wells and systems.
9. References. This provides a bibliography of references where dynamic simulation has
been employed for gas-lift wells and systems, as well as for other general production
system applications such as wax, hydrates, and flow assurance. Some references are
also provided to help to understand dynamic simulation principles.
2. Summary of Recommended Practices for Dynamic Simulation
of Gas-Lift Wells and Systems
This chapter contains a summary and description of the recommended practices
contained in this document.
The recommended practices are organized by the chapters where they are presented.
This chapter contains a cross reference to the detailed chapter(s) where each
recommended practice is discussed and described.
After reading this chapter, the reader should understand the recommended practices
that need to be followed to successfully use and deploy dynamic simulation of gas-lift
wells and systems. A reference on where to turn in the document for more detailed
information is provided.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Ch
.
Sect
.
II
Introduction to Dynamic Simulation of Gas-Lift Wells and Systems
a
b
Practice
Number
Page 16
Summary of Recommended Practices
Document Objectives
1
Create best practice recommendations for the application of
dynamic simulation in gas-lift wells and systems in order to
optimize well/system integrity, operations, life cycle design,
and production.
2
A broad range of artificial lift including gas well liquid loading
and natural flowing systems are addressed as appropriate.
3
Most of the dynamic simulation recommendations are not only
specific to gas-lift systems but they can be implemented in
other type of production systems.
4
This document is designed to gain a general understanding of
dynamic simulation, areas of application, and added value and
benefits.
Dynamic Simulation - Definition and Basic Concepts
1
Dynamic simulation is the common term for multiphase flow
transient numerical simulation used for modelling the hydraulic
and heat transfer from the reservoir to the facilities.
2
Use multiphase flow transient numerical simulation techniques
in wells and production systems to facilitate optimal economic
design, operation, maintenance, safety, and environmental
protection.
3
Dynamic simulation should be used during all stages of the
operational well/system life cycle to predict multi-phase flow
behavior and “what-if” analysis.
4
Evaluate well and pipeline flow interaction by dynamic model
integration.
5
Multi-discipline teams or cross-discipline experience is required
to build and integrate the well and production system model
from the reservoir to facilities.
API RP 19G11
Ch
.
Sect
.
c
III
Dynamic Simulation of Gas-Lift Wells and Systems
Page 17
Practice
Number
Summary of Recommended Practices
6
In gas-lift systems, the maximum benefits of dynamic
simulation are obtained when the model is applied for real-time
production optimization.
Difference between Steady-state and Dynamic Simulation Techniques
1
Dynamic simulation is recommended to analyze transient
operations.
2
Validate the model for steady state and transient conditions to
ensure accuracy of the simulation.
3
Use dynamic simulation to determine periods of flow stability
and instability.
4
Use dynamic simulation to define flow regimes and estimate
Pressure/Temperature profiles in the well/system.
5
Use dynamic simulation when combined oil and gas production
systems and conditions as listed in Section II are encountered.
Typical Gas-Lift Well and System Operations
a
b
Continuous Gas-Lift
1
Design continuous gas-lift wells to lift as deep as possible, as
stable as possible, and to obtain optimum gas-lift performance.
2
Use dynamic simulation to confirm the design will allow deep
and stable operation.
3
Use dynamic simulation to diagnose the causes of instability in
continuous gas-lift wells.
4
Use dynamic simulation to check for multi-pointing where more
than one entry point is open, all or part of the time.
5
In gas-lift systems, the maximum benefits of dynamic
simulation are obtained when the model is applied in real-time.
Intermittent Gas-Lift
1
Design intermittent gas-lift wells to inject the optimum amount
API RP 19G11
Ch
.
Sect
.
Dynamic Simulation of Gas-Lift Wells and Systems
Practice
Number
Page 18
Summary of Recommended Practices
of gas per cycle at the optimum cycle frequency.
c
2
Use dynamic simulation to determine if input “choke” control or
time-cycle control is more appropriate to control gas injection.
3
Use dynamic simulation to design and diagnose inefficiencies
in the intermittent gas-lift operation.
Gas-Assisted Plunger Lift
1
d
e
f
Use dynamic simulation to design and diagnose inefficiencies
in the plunger-assisted gas-lift operation.
Dual Gas-Lift
1
Design a dual gas-lift well to unload to the desired operating
valve in both strings.
2
Dynamic simulation will estimate the amount of lift gas entering
each of the tubing strings from the common annulus.
3
Use dynamic simulation to evaluate and troubleshoot the
operation of a dual gas-lift well.
Single-Point Gas-Lift
1
Single point gas-lift is a special form of continuous gas-lift, with
only one possible point of gas entry. No unloading valves.
2
Use dynamic simulation to design and operate single point
injection wells.
3
Use dynamic simulation to troubleshoot and diagnose causes
of instability.
“Auto” Gas-Lift
1
Use dynamic simulation to troubleshoot and diagnose causes
of instability.
2
Use dynamic simulation to determine the optimum injection
rate and/or back pressure.
3
Use dynamic simulation to properly design and operate auto
gas-lift systems.
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1
Use dynamic simulation to evaluate the design and diagnose
problems, pressure fluctuations, or flow rate slugs that may
upset facilities on the platform.
2
Use dynamic simulation to define the economic life of the riser
system and the optimum time to switch to wellhead and/or
downhole injection.
Gas-Lift for Gas Well Deliquification
1
Use dynamic simulation to evaluate the design of the unloading
system.
2
Use dynamic simulation to evaluate the lift gas injection rate to
determine if the total injected plus produced gas will remain at
or above the critical gas flow rate.
3
Use dynamic simulation to assist in the diagnosis of problems
in wells where the well is beginning to experience liquid loading
due to insufficient gas injection.
Gas-Lift Unloading
1
Use dynamic simulation to evaluate the design of unloading
gas-lift mandrel depths and set pressures of the unloading
valves.
2
Use dynamic simulation to evaluate the liquid and gas flow
rates through the gas-lift valves during the unloading process,
to evaluate if valve port or seat damage may occur.
3
Use dynamic simulation to determine if the well will unload to
the desired depth.
4
Run the dynamic simulator with the steady state design, and
determine if the well will unload successfully. If it will not,
reiterate the design and re-evaluate.
Use of Gas-Lift for Well Kick-Off
1
Use dynamic simulation to determine if a gas-lift well can be
started in “normal” operation. If not, a special kick-off process
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must be developed, analyzed, and followed.
k
2
Use dynamic simulation to determine if the well will flow
naturally after it has been kicked off.
3
Use dynamic simulation to predict the well’s parameters for
which kick-off of naturally flowing wells is required after a shutin period.
Use of Gas-Lift for Wellbore Clean-Up
1
l
Gas-Lift System Distribution
1
m
n
1
Use a dynamic simulator to evaluate the potential for hydrate
formation when a pressure drop exists in the system.
2
Use dynamic simulation to evaluate the benefits of dehydrating
the gas.
Use of Non-Hydrocarbon Gases such as CO2 and N2
Use a dynamic simulator to help understand the characteristics
that may be result from the differing properties of nonhydrocarbon gases.
Natural Flowing Gas-Lift Wells
1
IV
Use a dynamic simulator to evaluate changes in the distribution
of gas to the wells served by the system.
Use of Un-Dehydrated Gas
1
o
Use a dynamic simulator to determine the gas-lift injection
pressure and rates needed to remove completion fluids from
the wellbore, and the time required to clean-up the well.
Use dynamic simulation to aid in the evaluation of the optimum
time to switch from natural flow to gas-lift.
Recognize When Dynamic Simulation is Beneficial
a
Use Dynamic Simulation to Determine and Respond when a Well or
System may be Unstable
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1
Use dynamic simulation to help identify the causes of unstable
transient conditions, such as decreasing reservoir pressure,
increased water cut, over-sized tubing for current fluid
production, decreased total gas liquid ratio, or increased back
pressure.
2
Use dynamic simulation to aid in identifying where and when
slugging is initiated.
3
Use dynamic simulation to identify unstable
conditions during the design phase for well tubulars.
4
Use a dynamic simulator to evaluate alternatives to stabilize an
unstable well.
transient
Use Dynamic Simulation to Determine when to use Gas-Lift to ReStart Wells
1
Use dynamic simulation to evaluate the reasons to initiate gaslift, such as high water cut, low bottom-hole pressure, poor well
inflow performance, or high back pressure in the surface
facility.
2
Use a dynamic simulation model to match the well’s current
flowing conditions with the measured field data and run a
sensitivity analysis for a range of different conditions.
3
Use dynamic simulation to determine if a well can be put back
online without the need of gas-lift.
Use Dynamic Simulation to Determine when to Start Gas-Lift in a
Flowing Well
1
Use dynamic simulation to help define the optimum time to
switch from natural flow to gas-lift.
2
Use a dynamic model to predict the optimum injection point
and the required amount of lift gas for optimum well
performance.
Use Dynamic Simulation To Determine The Need To Start Gas-Lift
Due To Liquid Loading In Gas Wells.
1
Use dynamic simulation to predict the reasons for liquid loading
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with water and condensate.
e
f
2
Use dynamic simulation to provide a better understanding of
multiphase flow and its role in liquid loading. The onset of
liquid loading is triggered by film flow reversal rather than
droplet flow reversal.
3
Use dynamic simulation to help obtain realistic values of
reservoir abandonment pressures.
4
Use dynamic simulation to aid in modelling and selection of the
optimum deliquification method: velocity strings, chemical
injection, plunger lift, gas lift, or pumps.
Use Dynamic Simulation To Aid in Optimizing Intelligent And
Complex Well Completions.
1
Use dynamic simulation to aid in optimizing the design of
intelligent wells. Various well completion options can be
compared.
2
Use dynamic simulation to aid hardware selection for extended
reach, maximum contact reservoir wells and multi-laterals.
3
Use dynamic simulation to optimize recovery from complex
intelligent wells.
4
Use dynamic simulation to help reduce well intervention costs
by upfront design to allow well reconfiguration without the need
for physical intervention.
5
Intelligent wells/completions benefit from real-time production
information and control, which is supported by dynamic
simulation.
Use Dynamic Simulation To Aid in Understanding When Cross Flow
And/Or Commingling Occur
1
Use dynamic simulation to aid in understanding transient flow
conditions and cross flow occurrences in multi-layer, multilaterals, and multiple zone horizontal wells. It is possible for
cross flow to occur between zones during well shut-in and
while the well is flowing.
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2
Dynamic simulation may be used to help optimize design and
operation of multi-layer or multi-lateral well completions.
3
It is important to model the well trajectory. Create enough pipe
segments to precisely estimate and optimize commingled
production from each zone of interest.
4
Model each zone as a separate source/well so that fluid
production, cross flow, and fluid movement from each zone can
be evaluated for different flowing bottom-hole pressures.
5
Dynamic simulation may be used to help evaluate commingling
different production zones or producing them separately for
proper reservoir management.
Use Dynamic Simulation To Optimize Gas-Lift Well And System ShutIn And Start-Up Operations
1
Ensure that shut-in and start-up flow assurance dynamic
simulation studies are performed on the full well system to
avoid errors in the flowline-riser-facilities design.
2
The shut-in and start-up conditions need to be included in the
reservoir-to-facility production system model to define the
interactive behavior.
3
Use a dynamic simulator to help configure an automated
control system to address unstable operations caused by shutin, start-up, and the gas-lift operations.
Information Required for Dynamic Simulation
a
b
Fluid Properties
1
Use black oil models only for specific applications, as they are
based on the properties of hydrocarbon mixtures from one
specific region, and are only valid for a specific range of
pressures and temperatures.
2
Use fully compositional fluid models for dynamic simulation.
Wellbore Profile and Well Schematic
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Practice
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1
Accurately input well trajectory. Limiting the number of points to
describe the well profile can lead to errors in slugging
predictions.
2
Accurately input well geometry. Use diameters with associated
depth intervals in the model.
3
Input any relevant well equipment; valves, chokes, nipples,
with their pressure drop characteristics, internal diameters, and
depths.
4
Input an accurate well completion design including all casings
and annular fluids, cement and formation thicknesses, and
heat transfer coefficients for each constitutive material; to
estimate the radial heat losses in the wellbore.
5
The use of the “overall heat transfer coefficient” to estimate
heat losses in the wellbore is not recommended.
Inflow Performance Relationship At Inflow Point
1
Input an accurate, standard inflow performance relationship
(IPR) for the type of reservoir, for design and forecasting
purposes, i.e. “what if” scenarios.
2
Use a quasi-dynamic IPR when the dynamic model is used for
matching measurements. The selected variables, e.g. skin,
non-Darcy skin, and permeability, can be input as time-series
so the impact of the transient behavior can be reflected.
3
Use the distributed IPR approach when necessary for well
clean-up, multi-laterals, and extended reach wells. This
requires dividing the productive interval into segments or zones
and calculating individual IPR’s.
Boundary Conditions
1
Specify reservoir pressure and temperature for every inflow
point and bottom node boundary. These can be input as timeseries if necessary.
2
Specify wellhead pressure and temperature, assuming the
model stops in the wellhead. These can be input as timeseries, if necessary.
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3
Specify the well’s initial conditions and fluid contents and the
associated pressures and temperatures, including soil
temperature gradient, surface-subsea temperature gradient,
and ambient temperature.
4
Specify for the risers, a detailed temperature profile from sea
surface to mud line, including variations in water current
velocities. This is recommended when there is potential for
hydrates or production chemistry problems.
5
Enter any planned changes in the wellhead and surface
injection pressures, or in gas-lift rate as time-series so that
their impact on the transient behavior can be reflected.
Application of Dynamic Simulation
a
Integrated Modelling
1
2
3
Model a single well and validate the model when it is at an
early design stage and/or when the initial troubleshooting is
focused on a particular well.
4
Make the model as simple or as complex as required. For
instance, the annulus can also be included and the countercurrent heat transfer effect of injecting a relatively cold lift gas
and producing a hot reservoir fluid in the tubing can be
evaluated.
5
Use dynamic simulation to assist in proper design of the
casing, tubing, and wellhead to withhold the generated
stresses produced at start-up.
6
Use an integrated dynamic simulation to evaluate interactions
between components in the production system.
Couple the dynamic simulator model with a dynamic near-wellbore
reservoir simulator if a strong reservoir-wellbore interaction exists.
7
b
Define the limits and composition of the model based on the study
objectives.
Gas-lift and naturally flowing wells are parts of systems that need to
be modelled, covering the range from reservoir to facilities.
Real-Time Modelling
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1
Use real-time online dynamic simulation and animation to
generate responses at a frequency consistent with
observations.
2
Use real-time, online dynamic simulation output to evaluate
and improve well shut-in and start-up procedures.
3
Use a real-time online dynamic simulator model to evaluate
hydrate formation potential that may result from well shut-in
and start-up.
4
Use the online dynamic simulator as an advisor and a data
source by creating virtual instruments where no functioning
instrumentation exists.
5
Use online real-time dynamic simulation when a range of
operating behaviours wider than covered by other methods, is
required.
6
Use the real-time online dynamic simulator as a training tool for
personnel involved in design, operation, troubleshooting, and
optimization.
7
Use online real-time dynamic simulation to assist in performing
routine production operations as listed in Chapter 6.
Use Of Dynamic
Management
Simulation
Modelling
For
Gas-Lift
System
1
Use a dynamic simulation model to evaluate if the mandrel
spacing and unloading valve designs will work and unload as
intended.
2
Use dynamic simulation to evaluate the causes of unstable
operation.
3
Use a dynamic simulator to adjust the operating parameters
until the unstable performance of a well can be matched,
demonstrating possible causes.
4
Once the cause(s) of instability have been determined, adjust
operating parameters, and evaluate the changes.
5
A dynamic simulator can assist in finding the best operation of
a gas-lift well, when the true optimum gas injection rate is not
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available.
d
6
Use a dynamic simulator to determine the optimum gas
injection rate and pressure for riser gas-lift.
7
If it isn’t possible to mitigate slugging, use a dynamic simulator
to predict the size and arrival time of slugs so action can be
taken to avoid upsets to the production facilities.
Appropriate
Dynamic
Implementation
Simulation
Techniques
And
Their
1
Use dynamic simulation to assist in understanding flow
behavior for technical, operational, and health, safety,
environment (HSE) integrity during the field life cycle.
2
Steady state techniques are most appropriately for steady state
conditions.
3
Dynamic simulation techniques are most appropriately applied
for dynamic conditions but should apply to steady state.
4
Optimize combined use of both techniques without
compromising the quality of the design and the operational
integrity of the system.
5
Use dynamic simulation to examine conditions of potential risk
and catastrophic failure.
6
Use steady state techniques to provide a system design which
can then be evaluated with dynamic techniques.
7
Use dynamic techniques to take into account time dependant
operating practices.
8
Use dynamic analysis to establish operational guidelines to
avoid production chemistry problems during shut-in, start up,
and ongoing operations.
9
Initially build a dynamic model to analyse the start-up and shutin operations. Define the time required to reach stable flow.
Input the validated stable correlations into steady state
software models to use their capabilities.
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Practice
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Summary of Recommended Practices
10
Use dynamic simulation to optimize the design of individual
components in the production system and integrate them.
11
Build the most simple dynamic simulation model required for
the particular simulation objectives. The part of the total gas-lift
system to be modelled depends on the study objectives
defined in Chapter 6.
12
Use a quasi-dynamic IPR if the interaction between the nearwellbore reservoir and the well plays a dominant role in the
dynamic behavior of the system. Cases where the dynamic
wellbore/reservoir interactions may be strong are listed in
Chapter 6.
13
Integrate the dynamic simulator with geo-science and/or risk
simulation and decision analysis software to obtain a technicaloperative information management system to improve field
development decisions.
Information Provided by Dynamic Simulation
a
Slugging Flow
1
Use a dynamic simulator to properly define any slugging flow
conditions as well as flow stability.
2
Use dynamic simulation to properly define hydrodynamic
slugging conditions which are generated by slip between the
liquid and gas phases.
3
Use dynamic simulation to define terrain and/or well trajectory
induced slugging.
4
Use dynamic simulation to define the severity of slugging
conditions generated by risers, which are an integral part of
offshore and subsea production and well servicing systems.
5
Use dynamic simulation to define where slugs originate, their
causes, and their size and frequency.
6
Use dynamic simulation to understand the potential problems
for stable multiphase flow, as listed in Chapter 7.
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Water Effects On Corrosion And Hydrates
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Summary of Recommended Practices
1
Use dynamic simulation to define water accumulation at any
point in the system, and its impact on hydrodynamic and terrain
induced slugging, for liquid loading conditions and related
internal corrosion susceptibility.
2
Use a dynamic simulator to determine the following
components at each location in the system: gas, vapor,
oil/condensate droplets, water droplets, oil/condensate film,
and water film. If water is present at the surface of the pipe, it
may induce a corrosive environment.
3
Use a dynamic simulator with corrosion models to identify not
only the areas of the well and flowline with the highest risk for
corrosion but also the corrosion rates.
4
Use a dynamic simulator to define the corrosion mitigation plan
which is dependent on the changing operating conditions.
5
Use dynamic simulation to predict inhibitor distribution and
estimate the type and amount of inhibitor required to eliminate
or minimize corrosive condition.
6
Use dynamic simulation to analyse how the flow conditions will
affect the structure and strength of protective corrosion product
layers.
7
Use dynamic simulators to obtain information required to
develop risk-based corrosion susceptibility profiles.
8
Use dynamic simulation to estimate when, where, and under
which conditions hydrates may form in a production system
based on the difference between a hydrate temperature and
fluid temperature.
9
Use dynamic simulation to reduce uncertainty by rigorous
screening of various inhibition options.
10
Use dynamic simulation to compare different hydrate control
methodologies such as insulation, active heating, and
inhibition.
11
Use dynamic simulation to aid in determining the best inhibitor
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injection location.
c
12
Use dynamic simulation to aid in estimating the amount of
inhibitor.
13
Use dynamic simulation to track the amount of inhibitor in the
water and gas phases in the well/pipeline to ensure enough is
available for inhibition purposes.
14
Use dynamic simulation to aid in developing operating
guidelines to ensure the right amounts of injection and
distribution of inhibitors for all operating modes.
15
Use dynamic simulation in the design phase to aid in
developing a production system with an acceptable level of
risk.
Production Chemistry
1
Use dynamic simulation to evaluate production chemistry
issues and develop cost-effective field production strategies
and operating integrity. There are increased risks associated
with long sub-sea tiebacks, dry tree risers, and extended
export pipelines in cold ambient water temperatures.
2
Use dynamic simulation to aid in analyzing the effects of high
wax content crudes. Wax gelation is less common in steadystate flow than wax deposition, but it can have even greater
impact during transient operations such as shutdowns and start
ups.
3
Use dynamic simulation to calculate where and when fluid
temperatures fall below wax appearance temperature (WAT)
and the wax deposition rate.
4
Use dynamic simulation to predict the need for the operating
situations listed in Chapter 7.
5
Use dynamic simulation in the design phase to develop a
production system with an acceptable level of risk.
6
Use dynamic simulation during the design process to provide
key performance indicators for profiling well-pipeline
temperatures and wax build-up.
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7
Use dynamic simulation in real-time, online well-pipeline
monitoring such as pigging operations.
Gas-Lift Valve Performance
1
Use a valve performance model to obtain gas throughput vs.
upstream and downstream pressure.
2
Use a valve performance model to aid in evaluating conditions
during unloading.
3
Use a valve performance model during the design phase to
evaluate the performance of port size of the valve.
4
Use a valve performance model during the simulation phase to
predict performance with the given valve characteristics.
Well Equipment
1
Use dynamic simulation to define where the sub-surface safety
valve (SSSV) should be located.
2
Use wax/hydrate dynamic modelling to define the equipment
location points where wax and hydrates can form.
3
Use dynamic simulation to assist in establishing operational
guidelines to avoid/minimize wax/hydrates deposition by
inhibitor injection and plan remedial wax prevention and
cleaning schedules.
4
Use dynamic simulation
backpressure effect.
5
Use dynamic simulation to evaluate the riser effects and
pressure required to efficiently lift fluids through the riser.
to
evaluate
the
separator
Well Design
1
Use dynamic simulation to aid in designing wells and total
production systems for the field life cycle.
2
Use dynamic simulation to predict slugging flow and estimating
water accumulation.
3
Use dynamic simulation to aid in predicting the amount of lift
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gas required and the optimum injection location; riser base,
wellhead, or downhole.
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3. Introduction to Dynamic Simulation of Gas-Lift Wells and
Systems
Document Objectives
The application of multiphase flow transient numerical simulation (dynamic
simulation) techniques in wells and production systems has become an important
methodology to ensure:

Wells/field life cycle sound engineering design,

Optimal operation guidelines,

Optimization of investment and operating costs,

Production optimization, and

Minimization of risk, safety hazards, and environmental impact.
The development of oil and gas fields continues to progress towards increasingly
hostile environments requiring sub-sea and deepwater facilities and more
complex well completions. The use of long horizontal, multi-layer, multi-lateral,
big-bore, and intelligent wells have become more prevalent and are no longer the
exception. High pressure, high temperature (HP-HT) reservoirs and deepwater,
cooler environments present more complex production chemistry and flow
assurance problems. Therefore, there are requirements to more accurately model
these systems.
The main objective of this document is to create recommended practices for the
application of dynamic simulation in gas-lift wells and systems and present
guidelines to facilitate the application of this technique to optimize well/system
integrity, operations, life cycle design, and production. Although the primary focus
is on gas-lift, the document addresses a broad range of artificial lift and natural
flowing systems and topics (e.g. gas well liquid loading). In principle gas-lift is an
extension of natural flowing systems. Furthermore, most of the dynamic
simulation recommendations are not only specific to gas-lift system issues (e.g.
stable flow, hydrates, waxes, corrosion, liquid loading, and complex wells) but can
be implemented in other types of production systems (e.g. natural flowing wells).
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This document is designed for managers, production technologists, reservoir
engineers, facilities engineers, production engineers, well testing engineers, well
analysts, operators, and researchers who want to gain a general understanding of
dynamic simulation, areas of application, added value, and benefits. This
document also compares transient versus steady state techniques and provides
readers with the required understanding of when and how dynamic simulation
techniques should be applied.
Dynamic Simulation - Definition and Basic Concepts
The term “dynamic simulation” has been used and misused.
“Dynamic
simulation” is defined and used as a short cut for multiphase flow transient
numerical simulation. Some problem-solving schemes inter-relating the solutions
given by steady state techniques at different snapshots in time are sometimes
called dynamic simulation techniques, but these are not truly transient or dynamic
considering that there is not continuous analysis of the multiphase phenomena.
That is, what is happening between the selected time snapshot points is
unknown. It is also important to understand the differences between “dynamic
behavior” which describes changes in real time and “transient behavior” which
describes changes over time.
The dynamic simulation techniques were pioneered by the nuclear industry to
predict two-phase flow transient behavior with the accepted accuracy required to
analyze nuclear reactors since dynamic instabilities could lead to plant collapse.
The computer techniques were adapted to the oil and gas industry in 1980 (first
pipeline simulator was made from a reactor model) and the advance of computer
technology enhanced the current use of this technique.
Dynamic simulation is a proven technique applied for over 25 years by facilities
engineers for pipeline and slug catcher design. The application of multiphase flow
transient numerical simulation in wells is a new practice which requires different
understanding and expertise. Multi-discipline teams or cross-discipline experience
are required to properly build and integrate the well model (with the corresponding
reservoir inflow performance boundary conditions) into the total production
system model.
The development of offshore, subsea, and deepwater fields and the use of more
sophisticated drilling techniques and well completions require more robust
pressure, temperature, flow regime, and liquid hold-up predictions. The unique
features and flow assurance requirements, along with the high associated capital
costs, clearly merit detailed dynamic analysis in wells and integrated production
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systems. The multiphase flow transient conditions must be fully evaluated and
understood for a sound engineering design and safe operations.
Dynamic simulation provides the possibility of building a virtual well model that
can be used to analyse "what if" case scenarios and predict specific results. It is
used to understand transient well/system behavior and determine the optimum
process to eliminate/minimize transient problems that cannot be fully predicted by
using steady state analysis techniques[1]. Furthermore, once the dynamic well
model is validated, it can be used as a virtual gauge and/or a virtual downhole
temperature survey during production/injection operations.
Well dynamic simulation should be used during feasibility and conceptual studies
and at any stage of the well life cycle to "virtually" run through a complete case
scenario and predict the well multi-phase flow behavior (including liquid hold-up,
pressure and temperature trends, and profiles). New field development complex
operational situations require this technique to optimize technical, operational,
and HSE integrity during design and operation of production systems[2}.
Dynamic simulation is capable of modelling the well/system multi-phase flow
behavior from the static initial conditions (zero rates) to the steady state flow
conditions, confirming whether these conditions can be reached. Therefore, the
area of applicability is increased over steady-state techniques. See Table II-1.
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Dynamic Simulation of Gas-Lift Wells and Systems
Table II-1 – Main areas of application of Dynamic Simulation
Dynamic simulation results are tipically used to support project decisions in the following areas:
Flow assurance threat
Wells
Pipelines
Flow delivery through • Verification of planned production
• Pipeline packing / unpacking
field-life
• Maximum pressure and temperature
• Start-up / Shut-in
• Production optimization
• Operation of twin parallel lines
• Complex wells (Intelligent, Multi• Application of multiphase pumps
lateral. Multi-layer, etc.)
• Product composition from comingled
• Artificial lift design – GL, ESP, PL, etc.
fields
• Optimal routing to pipelines
• Component tracking (i.e. MEG)
• Gas-Lift compressors shut-down
• Ability to re-start
• Time to re-establish full flow potential
• Crossflow
• Commingling fluids
• Water accumulation
• Liquid loading
• Watercut limit
• Reservoir depletion
Process Facilities
• Control stability
• Production optimisation
• Hot oil circulation
• Subsea separation
Liquid surges
• Flow stability
• Liquid loading
• Velocity strings
• Optimal use of Gas-Lift
• Slug break-up
• Vessel sizing
• Designing successful pigging operations • Surge control
Hydrates & Wax
• Hydrates potential (when, where)
• Wax potential (when, where)
• Inhibitor deployment
• SSSV placement
• Wax scrapper runs frequency
• Design of insulation / bundle / heating
medium
• Inhibitor deployment
• Water accumulation
• Handling wax volumes
Integrity & Safety
• Production operations
• Well clean-up
• Well testing
• Well control operations
• Well blowout/killing operations
• Workover operations
• Drilling operations
• Water accumulation
• Annular P-T increased when fluids
trapped (no venting)
• Pressurization or depressurization
within material limitations
• Identification of high corrosion risk areas
• Location and conditions of reverse flow
• Flare system requirements and
capabilities
• Identification of leaks from
routine data
• HIPPS systems
Dynamic simulation does not replace steady-state techniques but completes the
areas not fully covered by these methods. The use of steady-state techniques to
describe transient events is not recommended. The earlier dynamic simulation
is adopted in the life of a project, the better design and economic decisions can
be made, speeding-up and enhancing the whole study process[3-4]. See Fig. II-1.
Furthermore, the original dynamic model can be updated and upgraded when
more data is available[5] and can be used in real-time after commissioning[6].
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Dynamic Simulation of Gas-Lift Wells and Systems
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Figure II-1 – Dynamic simulation wheel
Dynamic simulation techniques use a one dimensional (1-D Grid) transient multiphase flow numerical simulator program capable of modelling the hydraulic and
heat transfer effects at any point and time in wells, pipelines, risers, and
networks – from the reservoir to the facilities[7-8]. Equipment such as valves,
chokes, packers, compressors, separators, and controllers can be included in
the model. Annular flow and counter-current heat transfer effects can be
modelled when necessary. Fluid composition is input as a fluid file and a proper
fluid characterization[9] is necessary. The simplistic black-oil input is optional but
only recommended for particular applications.
Several dynamic simulation models exist and have been available for over two
decades. These include the Two-Phase Model (Gas-Liquid), extended ThreePhase Model (Gas-Oil-Water), and Drift-Flux Models which are the most
adopted ones. The Two-Phase and extended Three-Phase models are based on
complex one-dimensional multi-fluid representations of the multiphase
hydrodynamics, whereas Drift-Flux models are based on a drift-flux formulation
which treats the two phases as a mixture. Gas is assumed to be drifting along
with liquid where the gas velocity can be described by a slip relation. Drift-flux
models are simpler models developed to be fast to compute and avoid
convergence problems when the well models are coupled with reservoir
simulators[10].
Two-Phase and extended Three-Phase models[11] have been verified over a
wide range of applicability and they have been accepted by the industry as
usable simulators for transient multiphase flow of oil, water and gas in wells and
pipelines. The Three-Phase (or Two-Phase if three phases are not required)
simulators are able to quantitatively predict complex and varied physical
phenomena such as slugging and compositional tracking in typical well and
pipeline configurations. Therefore, the Three-Phase simulator is used as an
example only for the dynamic simulator descriptions presented below. It is
recommended to evaluate all the available software packages before making a
selection.
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Dynamic Simulation of Gas-Lift Wells and Systems
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The numerical solution scheme shown here is a semi-implicit integration method
which allows for relatively long time steps with efficient run times. A set of
coupled first order, non-linear, one dimensional partial differential equations, with
rather complex coefficients are used:
• Five mass conservation equations
– Gas
– Hydrocarbon bulk
– Hydrocarbon droplets
– Water bulk
– Water droplets
• Two momentum conservation equations
– Gas + droplets
– Liquid bulk
• One energy conservation equation
– Mixture (only one temperature)
• Constitutive equations
The closure laws for mass, momentum, and energy transfer are semimechanistic and require experimental verification. Small and large scale flow
loops were used to verify the example Three-Phase simulator. No flow loop can
represent all possible multiphase flow situations but the test loop combines a
vertical elevation (riser) higher than 50 m (164 ft), working pressures as high as
90 bar (1,300 psi), internal diameters from 25.4 to 304.8 mm (1 to 12 inch), and
a maximum total length of 1000 m (3280.84 ft) with the possibility of changing
the slope in defined sections[12].
The one-dimensional pipe geometry is divided in sections. See Fig. II-2.
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Figure II-2 – Wellbore Model Pipe Sectioning
Each section length has to be longer than half or shorter than twice the length of
the adjacent section. Section length is selected based on a compromise
between accuracy and simulation run time depending on the case under study.
The longer the section length, the smaller the simulation time but the accuracy is
lower. Mass transients generally travel much slower than pressure transients,
therefore to obtain more stable simulation runs, a staggered grid is used:
variables such as pressure, temperature, and liquid hold-up are calculated at the
center of the section, and boundary variables such as flow rates, flow patterns,
and velocities are calculated at the section boundaries. See Fig. II-3.
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Dynamic Simulation of Gas-Lift Wells and Systems
1
2
1
3
2
4
3
5
4
Page 40
6
5
1,2,3,…,5 (inside) : section volumes
1,2,3,…,6 (outside): section boundaries
P, T and liquid Hold-up are calculated at the volume center
Qg, Qo, Qw, flow regime and velocities are calculated at the section boundaries
Figure II-3 – Section Volume and Section Boundaries
To rigorously calculate the radial temperature for each pipe section, a wall is
associated to describe the number of radial concentric layers (casings and
annular space fluid properties) based on the well completion schematic. See
Fig. II-4.
BRANCH: WELL-UPP
WALL:
Tubing-1
MD 1432.2 m
MD 2766.1 m
BRANCH: WELL-LOW
WALL:
Tubing-2
MD 3153.8 m
BRANCH: WELL-LOW
WALL:
Tubing-3
MD 4935.9 m
Steel
Cement
Formation
Figure II-4 – Walls: Well Completion Schematic
Properties include thickness, density, thermal capacity, and conductivity. In
addition, the temperature and outer convective heat transfer coefficients of the
surroundings are required.
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Two basic flow regime classes are modelled. See Fig. II-5:
•
Distributed (bubble and slug flow)
•
Separated (stratified and annular mist flow)
Stratified flow
SEPARATED
(Annular flow)
DISTRIBUTED
Dispersed bubble flow
Slug
flow
Figure II-5 – Dynamic simulator flow regime groups
Transitions between the regime classes are determined on the basis of a
minimum slip concept, in combination with additional criteria. Flow is divided
into gas, vapor, oil, and water droplets, and oil and water film. Changes in fluid
composition in the direction of flow are determined based on pressure and
temperature changes.
Initial conditions should be defined:
•
Start with the well full of drilling fluids (mud, brine, and/or diesel), or
•
Start with the well filled with production fluids; water and oil to a certain fluid
level and gas.
If the well is connected to a flowline, the flowline initial conditions should be
defined:
•
Start with the flowline filled with gas (empty), or
•
Start with the flowline filled with water or any liquids.
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Boundaries conditions should be defined:
•
Reservoir
•
Topsides (i.e. ambient temperature and wind velocities), and
•
Surroundings (i.e. sea floor, sea current velocities, and soil temperatures).
The reservoir boundary input is explicit. The reservoir parameters are given at
steady state reservoir conditions, which is adequate when the “predictive”
approach is used. The available IPR models in the dynamic simulator are:
•
Constant productivity index
•
Forchheimer model (gas wells)
•
Single Forchheimer model (high pressure gas wells)
•
Vogel equation (oil wells in gas saturation drive reservoirs)
•
Vogel combined with PI (oil wells where reservoir pressure is above Bubble
Point)
•
Backpressure (gas wells)
•
Normalized (saturated oil wells)
•
Tabulated IPR curved (any preferred IPR input)
Software models allow for a quasi-dynamic, time-series boundary input (quasitransient IPR input) for the key reservoir properties such as pressure,
temperature, mechanical skin, non-Darcy skin, permeability, and net pay[1]. This
option is relevant when the “matching” approach is used and the model is
validated by matching with measured data. Nevertheless, the best option to
gather all the well-reservoir dynamic interaction is to couple the dynamic well
model to a near-wellbore[13-14-15] or full reservoir dynamic simulator[16], but this
adds complexity to the simulations. The quasi-dynamic IPR input will help to
pre-define the key variables required to match the data.
Some simulators offer different visual outputs and numerous variables can be
selected to analyze the results:
•
Trend plots – show the change in a parameter versus time at a specific
location
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Dynamic Simulation of Gas-Lift Wells and Systems
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•
Profile plots – show the change in a parameter along the flow path over a
period of times, at a specified frequency
•
The viewer – shows a video-like animated representation of a parameter as
it changes continuously with time within a simplistic pipe model. See Fig. II6.
Plot 1 = Initial Conditions
Plot 2 = Brine arrival at surface (Gas in grey)
Plot 3 = LCM (Mud) being produced
Plot 4 = Clean-up completed (residual liquid in rat hole)
Figure II-6: Well Clean-up with LCM Viewer Snap-Shots Sequence
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Dynamic Simulation of Gas-Lift Wells and Systems
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Difference between Steady-State and Dynamic Simulation Techniques
Due to its historical development and the type of operational conditions, the
analysis of multiphase flow phenomena can be divided into two different
techniques:
• Steady State Techniques
• Dynamic Simulation (Transient) Techniques
Steady State techniques can be divided in two different methodologies:
• Empirical Methods
• Mechanistic Methods
The Empirical Methodology (originated in the early 1950’s) is based on
correlations developed from data collected by the researcher. These correlations
are equations used for prediction purposes for a defined range of operating
conditions. Some correlations perform better than others and a number of
different correlations may be needed to predict the hydraulic conditions of the
resulting flow regime. Selecting the best set of correlations affects the accuracy of
the predictions. For a good selection process, the specific conditions for which the
correlations were develop needs to be known. Extrapolation beyond these
conditions may make the process unreliable. Empirical Methods do not address
the complex physical phenomena that occur in multiphase flow.
Since the mid 1970’s, progress has been made to understand the physics of
multiphase flow in wells and flowlines, and several multiphase flow mechanistic
models became available to simulate wells and pipelines under steady state and
transient conditions. Mechanistic models try to mathematically describe the
multiphase flow mechanisms including related fluid properties and physical
relationships.
Mechanistic models may be more accurate and applicable to a wider range of
fluids and operating conditions than empirical models.
Nevertheless. some mechanistic models have been formulated separately for
wells, pipelines, vertical and horizontal flow, one, two or three-phase, and for the
prediction of specific steady state or transient conditions such as the onset of slug
flow and annular flow. Furthermore, as with the empirical correlations, some of
the mechanistic models have been developed and verified using small diameter
pipes/tubing (<101.6 mm) (< 4”), so this has to be also taken into account in big
diameter wells.
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Dynamic Simulation of Gas-Lift Wells and Systems
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Therefore, an evaluation of the existing empirical and mechanistic models needs
to be performed and the specific conditions for which the models were develop
needs to be known. The most popular empirical and mechanistic correlations are
listed in alphabetical order in Table II-2 which includes a brief “recommended
applications” column detailing which are the mechanistic correlations:
Table II-2 – Most Popular Multiphase Flow Correlations
These empirical and mechanistic models are used as correlations in steady state
software packages, as listed in the software’s selection options. One of the
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advantages of dynamic simulation is that it does not use correlations to connect
two nodes in the system. Instead, it solves the set of coupled 1st order, nonlinear, one dimensional partial differential equations at the given boundary
conditions, for every grid section in the direction of flow between the two nodes,
versus time. In this case, grid section length and therefore number of sections
influence the accuracy of the simulation; the longer the section the shorter the
simulation time but the lower the accuracy.
Another relevant advantage of dynamic simulation techniques is that they do not
use the flow regime map to define the type of flow. The flow regime map
approach is not rigorously accurate. Flow regime transitions cannot be reduced to
two defining parameters, gas and liquid velocity. In the Three-Phase dynamic
simulator, P-T and Liquid Hold-up are interrelated. Phase transfer is a function of
P and T. The Three-Phase interface mass transfer model takes into account
condensation, evaporation, and retrograde condensation.
Even though they are case dependant, the limitations of traditional steady state
techniques, when analysing steady state flow cases, are:
• Unable to predict terrain-induced slugging flow induced by risers, flowlines, and
horizontal or deviated wells with terrain ups and downs
• Unable to perform stability analysis
• Unable to evaluate transient gas/condensate, gas well liquid load-up issues
• Use and selection of the best flow correlations: even though correlations and
selection options have been improved.
The risk taken when using simplified techniques is higher if the well completion
design generates terrain induced slugging and even higher if there are phase
changes in the system. Steady state techniques may underestimate maximum
wellhead temperatures, and may give incorrect wellbore temperature gradients or
profiles. They do not capture the effects of fluid vaporization and condensation
on the overall fluid temperature.
The main limitation of traditional steady state techniques is that they do not
provide fully accurate engineering solutions for cases that are transient in nature:
• Flow behavior during well start-up and shut-down
• Stable flow
• Flow behaviour during rate changes
• Flow behaviour during well clean-up
• Flow behaviour during well testing
• Flow behaviour during liquid loading
• Flow behaviour during gas-lift unloading
• Dynamic behaviour of plunger lift
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Dynamic Simulation of Gas-Lift Wells and Systems
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and
• Perform flow assurance studies
- Production chemistry
- Corrosion
- Chemical injection
A good comparison of steady state versus dynamic simulation techniques is flow
stability prediction. As highlighted above, steady state techniques are not
designed to predict stable flow if the production system contains a riser and/or the
wells are horizontal or deviated. In these cases, one of the main applications of
dynamic simulation is to define if the flow is going to be stable in each of the
probable well/system design options. The multiphase flow slugging conditions
must be evaluated and understood for a sound engineering design and safe
operation. An incorrect prediction of stable flow can lead to selection of the
incorrect tubing size. The right tubing size may eliminate the slugging conditions.
To eliminate or minimize slugging conditions, it is necessary to know what is
creating the slugging flow conditions and where they originate. Dynamic
simulation can define and establish the size and frequency of the gas bubble
(slugging severity). See Fig. II-7.
Figure II-7 – Slugging flow: front and tail of the gas bubble
Tracking the development of the individual slugs along the well and flowline is
necessary to estimate the volume of the liquid surges out of the system.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
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The main potential problem areas for stable multiphase flow are:
• Terrain
• Inclination / elevation
• Rate changes
• Condensate–liquid content in gas
• Shut-in / Start-up
• Risers
For subsea and deepwater, the fluid behavior in the well, flowline, and riser may
actually dictate the required artificial lift method, not the wellbore environment
itself.
Ensuring stable flow or minimizing unstable flow is one of the recommended
practices for well production optimization. Dynamic simulation offers a sound
engineering technique to predict slugging, select the best method to eliminate or
minimize slugging, and optimize production.
Dynamic simulation should be applied when the following individual or combined
oil and gas production systems and conditions are encountered:
• Horizontal-inclined wells[17]
• Production-injection systems with risers[18]
• Tubing and annular flow with relevant counter-current heat transfer effects[19]
• Fluid composition that will significantly change in the flow path upstream of the
system output point due to flashing or condensation[20]
• Commingling fluids in multi-layer, multi-lateral wells[21]
• Intelligent well completions using well control and production optimization
equipment[22]
• Gas-lift wells which require prediction of stable flow and optimization[23-24-25-2627-28-29-30]
• Plunger lift used for gas well deliquification[31]
• Gas wells with liquid loading[32-33]
• ESP wells which required prediction of stable flow and optimization[34-35-36]
• Transient conditions such as flow behaviour during well start-up and shutdown[27]
• Flow assurance including production chemistry and corrosion[37-38-39-40]
• Well testing including wellbore storage and segregation effects[41-42-43]
• Well clean-up for removal of drilling and/or completion fluids from the
wellbore[41-43-44-50]
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Dynamic Simulation of Gas-Lift Wells and Systems
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• Well control including blowouts and killing procedures.[45-46]
• Workover evaluation analyzing fluid displacement (annulus-tubing, tubingannulus)[47]
In gas-lift systems, the maximum benefits of dynamic simulation are obtained
when the model is applied in real-time[48-49]
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Dynamic Simulation of Gas-Lift Wells and Systems
Page 50
4. Typical Gas-Lift Well and System Operations
A variety of gas-lift system configurations and operational practices are in use
throughout the industry. Each of these has unique characteristics and requires special
considerations when using dynamic simulation techniques to model well performance.
This chapter provides an overview of each operation, discusses both the steady state
and dynamic aspects of each, and provides recommendations for how dynamic
simulation can be used to address the dynamic aspects these operations.
Continuous gas-lift
Continuous flow gas-lift is one of two major classes of gas-lift systems. In the
continuous gas-lift process, relatively high pressure gas is injected downhole into
the fluid column. This injected gas joins the formation gas to lift the fluid to the
surface by one or more of the following processes:

Reduction of the fluid density and the column weight so the pressure differential
between the reservoir and wellbore will be increased. See Fig. III-1-A.

Expansion of the gas so it pushes liquid ahead of it, which further reduces the
column weight, thereby increasing the differential between the reservoir and the
wellbore. See Fig. III-1-B.

Displacement of liquid slugs by large bubbles of gas acting as pistons. See Fig.
III-1-C.
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Fig. III-1: Continuous Gas-Lift Production Processes
4.1.1
Steady-state aspects
Continuous gas-lift is intended to be a continuous, steady process. These
processes include the gas-lift injection pressure and rate, the gas-lift
injection rate from the annulus into the tubing, the pressure profile in the
tubing, and the pressure drawdown on the formation. However, some or
all of these processes are usually not steady, and they can be very
unstable, leading to significant well problems and loss of production.
4.1.2
Dynamic aspects
Often, due to operational issues, the gas-lift injection rate and pressure
are not stable. In some cases, the injection rate can be controlled and
made to be stable, but unless it is controlled, it will often vary with time and
production processes.
Even if the injection rate is controlled, the injection pressure may fluctuate
due to conditions in the well. This is most often caused by an imbalance
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between the injection rate at the surface and the gas flow rate from the
annulus to the tubing through the gas-lift valve or orifice.
This may be exacerbated if a well is “multi-pointing,” that is if it is injecting
through more than one valve, through a valve and an orifice at the same
time, or through a hole(s) in the tubing and a valve or orifice. This can be
caused by inappropriate gas-lift valve design relative to the current
operating conditions of the well.
Any unstable (dynamic) ituation in a continuous gas-lift well is less efficient
han continuous, stable gas-lift. Therefore, steps are needed to reduce or
eliminate instability.
4.1.3
Dynamic simulation
Dynamic simulation can be used in two primary ways on continuous gaslift wells.
a. Design
Design of continuous gas-lift wells is discussed in API RP 11V6. For
continuous gas-lift design, a design program (or manual process) is
used to determine the spacing of the gas-lift mandrels, the setting of
the gas-lift valves, the sizing of the gas-lift valve or orifice flow path,
and the desired gas-lift injection rate and pressure. Typically, this
design is performed in stages, with the mandrels being spaced when
the well is first drilled and completed, or recompleted after a workover.
The valves are run when it is necessary to place the well on gas-lift, or
when the valves need to be changed to improve operation. The
injection pressure is normally essentially fixed for a given field. But the
injection rate can be, and often is, changed frequently by the field
operator, or by circumstances in the field.
A dynamic simulator can be used to evaluate a design by running the
simulator with the intended mandrel spacing, valve configuration,
injection pressure, and injection rate. The dynamic simulator can give
an indication if the planned design will unload properly and produce
continuous, stable operation or if the well will be unstable. If it will not
unload as intended, or if it will be unstable, the design can be modified
until the predicted performance of the well is stable. If the dynamic
simulator can be included in an optimization program, the program can
automatically modify various parameters such as the valve or orifice
port/choke size, and the gas-lift injection rate, to determine the best
design for continuous, stable operations48-49.
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b. Problem diagnosis
When a continuous gas-lift well is on production, it may not unload as
desired, or it may be unstable as indicated above. A dynamic
simulator can be used to help diagnose the cause(s) of the problem,
and to indicate how the design or operation may need to be changed
to stabilize the well.
In an automation system, a dynamic simulator can be automatically
run on each gas-lift well whenever a problem is detected by the
surveillance system. Problem diagnoses and recommended solutions
can be presented to the operating staff on a routine basis.
Intermittent gas-lift
If a well has a low reservoir pressure or a low producing rate, it can be produced by
a form of gas-lift known as intermittent lift. This is the second major classification of
gas-lift systems. As its name implies, this system produces intermittently or
irregularly and is designed to produce at the rate at which fluid enters the wellbore
from the formation.
In the intermittent flow system, fluid is allowed to accumulate and build up in the
tubing at the bottom of the well. Periodically, a large quantity of high pressure gas
is injected into the tubing very quickly underneath the column of liquid and the liquid
column is pushed rapidly up the tubing to the surface.
This action is similar to
firing a bullet from a rifle by the expansion of gas behind the rifle slug. The
frequency of gas injection in intermittent lift is determined by the amount of time
required for a liquid slug to enter the tubing. The length of the gas injection period
will depend upon the time required to push one slug of liquid to the surface.
Normally, a standing valve is installed beneath the gas-lift valve to prevent pressure
and gas flow back into the low pressure formation. This method of lift is a cyclic
operation and the cycle can be divided into four periods:
Inflow period. During this period, the liquid flows from the formation into the well
bore and collects in the tubing above the standing valve and the gas-lift valve.
The gas-lift valve is closed during this period and the surface tubing pressure is
reduced to a minimum to allow the maximum inflow rate. See Fig. III-2-A.
Lift period. When sufficient liquid has collected in the tubing, the gas-lift valve
opens and injects high pressure gas to lift the slug to the surface. Some fallback
occurs due to liquid coalescing in a film on the wall of the tubing and liquid
droplets in the gas slug which lack sufficient velocity to travel to the surface. See
Fig. III-2-B.
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Production period. Fluid is produced at the surface. A rapid drop in tubing
pressure pulls in gas from the casing. No inflow occurs during this period. See
Fig. III-2-C.
Pressure reduction period. After the gas-lift valve closes and the slug flows
through the wellhead and to the separator, the lift gas pressure is dissipated and
the inflow period begins again. The intermitting cycle is controlled by regulating
the frequency of injection, the gas flow rate during injection, and the total quantity
of gas injected during each lift period. See Fig. III-2-D.
There are two primary means of intermittent gas-lift control, using a choke control or
timer control. In choke control, gas is slowly injected into the casing from the
surface, with the injection rate controlled by a surface choke or control valve. In
timer control, a surface control valve is periodically opened and closed on a time
cycle.
The advantage of choke control is that it causes a minimum impact or upset to the
overall pressure of the surface injection system. The disadvantage is that the
downhole injection process can only be modified by changing the operating gas-lift
valve. The advantage of timer control is that the frequency and volume of each
intermittent gas-lift slug can be controlled at the surface. The disadvantage is that
the sudden rate and pressure changes on the surface can upset other wells in the
system.
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Fig. III-2: Intermittent Lift Cycle
4.2.1
Steady-state aspects
Intermittent gas-lift is, by its very nature, a dynamic process. However, for
it to be successful, each intermittent cycle must be consistent in its
frequency and gas injection volume.
And intermittent gas-lift wells must be unloaded using the same process
as is used for continuous gas-lift wells.
4.2.2
Dynamic aspects
For an intermittent gas-lift well to be successful, its dynamic aspects of
injection frequency and volume per cycle must be correctly operated.
The gas injection frequency must be designed and operated to permit an
optimum amount of liquid inflow from the formation to the tubing during
each cycle. If the frequency is too high, not enough liquid will have
accumulated in the tubing, production will be minimum, and gas will be
wasted. If the frequency is too low, an excessively large slug of liquid will
be produced into the tubing. This can place an excessive amount of back
pressure on the formation, thus inhibiting inflow from the formation to the
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wellbore; and it can be difficult for the gas to lift the excessively large slug
of liquid to the surface.
The gas injection volume per cycle must be correct to lift the volume of
liquid to the surface. If it is too small, the liquid may not reach the surface
and it may fall back to the bottom of the well. If it is too large, gas will be
wasted.
4.2.3
Dynamic simulation
Dynamic simulators can be used in a manner similar to that described for
continuous gas-lift.
a.
Design
Design of intermittent gas-lift wells is discussed in API RP 11V10. A
dynamic simulator can be used to evaluate the design of an
intermittent gas-lift well, determine if it will unload properly, and
determine if it will operate properly from the operating gas-lift valve.
b.
Problem diagnosis
A dynamic simulator can evaluate the current operation of an
intermittent gas-lift well. The simulator can determine if the injection
frequency and gas injection volume per cycle are correct, or if changes
should be made to optimize production per cycle, and the volume of
gas injection per cycle.
Gas-assisted plunger lift
One special application of intermittent flow gas-lift is termed gas-assisted plunger
lift, or plunger assisted intermittent lift. In these applications, the intermittent gas-lift
installation is equipped with a plunger and related accessory equipment. The
plunger traverses the length of the tubing string in a cyclic manner, providing an
interface between the lifting gas and the produced liquid. The plunger sweeps
more of the liquid film from the tubing wall, minimizing the liquid fallback. Although
sand or solids in the tubing could prevent the plunger from operating successfully,
plungers are commonly used to control paraffin deposits. Plungers may not work
well in highly deviated or cork-screwed wells.
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Fig. III-3 shows a down-hole plunger installation with the gas-lift valve located below
the plunger. The surface wellhead equipment shows the lubricator/catcher to hold
the plunger for its short time at the top.
There are at least two issues with plunger lift that need attention. First, the plunger
must be designed so it can successfully pass through the upper gas-lift mandrels as
it rises and falls in the tubing. Second, adding the plunger increases the cost and
complicates the operation of the well, and many operators find that the added
production that can be achieved by the lifting of the plunger is not sufficient to justify
the added cost and complexity.
Fig. III-3: Gas-Assisted Plunger Lift
API RP 19G11
4.3.1
Dynamic Simulation of Gas-Lift Wells and Systems
Page 58
Steady-state aspects
Gas assisted plunger lift is an enhanced form of intermittent gas-lift. The
desired steady aspects of intermittent gas-lift pertain here as well. The
goal is to time the injection cycles to optimize liquid inflow from the
formation and control the injection volume per cycle to optimally lift the
plunger and the liquid above it.
However, this is more difficult than normal intermittent gas-lift because the
release and fall of the plunger must be coordinated with the gas-lift
injection frequency and volume per cycle.
4.3.2
Dynamic aspects
The dynamic aspects are similar to normal intermittent gas-lift, except now
the dynamic aspects of catching, releasing, and timing the fall of the
plunger must be taken into consideration.
4.3.3
Dynamic simulation
As with normal intermittent gas-lift, a dynamic simulator can be used to
assist with design and problem diagnosis. Dynamic simulators do not
offer a plunger option but they have the option to simulate pig runs in
pipelines. Dynamic simulators allow using the pig as a plunger in a
wellbore. Modelling plunger lift wells could be difficult and may not be
justified except when the optimization recommendations can be
extrapolated to a big number of wells.
Dual gas-lift
In certain cases, wells are completed as dual gas-lift producers. This is generally
driven by the desire to reduce drilling and completion costs where multiple
formations are located in close vertical proximity to one another. Such installations
are difficult to operate in conjunction with intermittent gas-lift applications. For this
reason, dual gas-lift installations can be considered a special application of
continuous gas-lift.
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Dual gas-lift is defined as the producing of two zones from the same wellbore by
gas-lift without commingling the well fluids in the wellbore. A variety of wellbore
configurations exist for achieving dual gas-lift. The most common involves the use
of a single bore packer to isolate the upper zone from the lower zone and a dual
bore packer to isolate the upper zone from a common gas-filled annulus. Such a
completion is depicted in Fig. III-4.
Fig. III-4: Schematic of Dual Gas-lift Installation
In an attempt to reduce the interference issues which arise from injecting gas
through a common casing-tubing annulus, dual gas-lift installations are often
equipped with production pressure operated gas-lift valves. However, many other
approaches are also used. This is discussed in detail in API RP 19G9.
API RP 19G11
4.4.1
Dynamic Simulation of Gas-Lift Wells and Systems
Page 60
Steady-state aspects
Operation of a dual gas-lift well is intended to be continuous and stable,
just like a single-string gas-lift well. However, due to the interference that
can occur between the two sides of the dual, it is even more difficult to
obtain stability.
4.4.2
Dynamic Aspects
Dual gas-lift can experience all of the dynamic aspects of single-string
continuous gas-lift. But these are often compounded by the interference
between the two zones. One typical problem is gas being over injected in
one side of the dual while the other side is starved for gas.
4.4.3
Dynamic Simulation
As with single-string continuous gas-lift, dynamic simulation can be used
to assist with design and problem diagnosis.
a. Design
Design of dual gas-lift wells is discussed in API RP 19G9. In principle,
the design issues are similar to those of single-string wells. The
differences are:

Usually one side of the dual is used for unloading. From this
stand-point, it is similar to a single-string continuous gas-lift well.

The amount of gas injection must be shared between the two sides
of the dual. To achieve this, the gas flow passage through the
operating gas-lift valves or orifices must be carefully designed and
controlled.
A dynamic simulator can be used to evaluate a dual gas-lift design, in
a manner similar to that of a single-string gas-lift well. The dynamic
simulator can define the amount of gas-lift gas going into each of the
tubing strings from the total amount of gas injected in the common
annulus and therefore total production can be optimized. The primary
issues are:

Will the well unload to the bottom valve, which is normally installed
slightly above the dual packer?

Will the desired amount of gas be injected into each side of the
dual?

Will this injection be at the desired depth in both sides of the dual?
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Dynamic Simulation of Gas-Lift Wells and Systems

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Will the injection pressure and rate be continuous and stable?
b. Problem diagnosis
A dynamic simulator can be used to diagnose problems in dual gas-lift
wells.

Is gas being injected into both sides of the dual?

Is it being injected at the desired depth?

Is the well stable?
If the well is not performing correctly, what needs to be done to modify
the design or the operation to correct the problem(s)?
Single-point gas-lift
Single-point gas-lift is a special application of continuous gas-lift systems in which a
single point of injection is installed downhole in the well. It can also be applied at
the wellhead or at the base of a riser. Usually the design uses some form of orifice
(no moving parts), with no unloading valves installed above that depth.
Such installations are often preferred in applications where reliability is of prime
importance, as with subsea producers where interventions can be costly or
impractical. By limiting injection to a single depth, these installations eliminate the
possibility of re-opening upper valves during normal operation. Also, the need to
re-enter the well to replace failed unloading valves is eliminated. Using an orifice
as the operating valve also increases the life of the device.
In most applications, a significantly higher operating pressure is required to unload
the well to this single depth. Also, the lack of unloading valves may result in a
shallower operating point and reduced draw-down versus conventional applications.
This depends on compressor capacity economics.
The steady-state aspects, dynamic aspects, and dynamic simulation of a singlepoint gas-lift well are similar to those for a continuous gas-lift well, with the following
exceptions:

There are no unloading valves, so these don’t need to be considered.

There is only one point of injection, so multi-point injection doesn’t need to be
considered.

Often this technique is used for sub sea wells so it can be more difficult to
diagnose problems, since it can be difficult to obtain information on well-head
injection pressure and other parameters.
Dynamic simulation is necessary to properly design and operate gas-lift single point
injection wells and systems due to the reduced system’s flexibility. There is a
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minimum surface injection rate required for the orifice to maintain sufficient annular
backpressure for continuous downhole gas injection. This minimum injection rate
depends on orifice size and flowing tubing pressure which is a function of the
wellhead pressure, tubing size, IPR, reservoir pressure, and water cut.
Auto gas-lift
Auto gas-lift is a term that refers to continuous gas-lift systems that use gas from a
gas-bearing formation to lift fluids from another zone in the same well. The lift gas
is produced downhole and allowed to enter the tubing through some form of gas-lift
valve or flow control device, as depicted in Fig III-5. Because of the dependency
between gas passage and the changing inflow performance of the gas bearing
zone over time, it is often desirable to use intelligent flow control devices as the
injection point in such wells. This allows operators to adjust the size of the orifice to
provide appropriate gas passage as the gas bearing zone is depleted.
Fig. III-5: Schematic of Auto Gas-lift Well
The steady-state aspects, dynamic aspects, and dynamic simulation of an auto
gas-lift well are similar to those items for a continuous gas-lift well, with the
following exceptions:
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Dynamic Simulation of Gas-Lift Wells and Systems
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
There are no unloading valves, so these don’t need to be considered.

There is no surface injection, so this doesn’t need to be considered.

There is only one point of injection, so multi-point injection doesn’t need to be
considered.

If a gas-lift valve or orifice is used to control the rate of gas injection into the
producing well, there is little adjustment that can be performed, other than
possibly controlling the back pressure on the producing well.

If an intelligent flow control device is used to control the rate of gas injection into
the producing well, it may be possible to control this valve to optimize the well’s
production and minimize pressure fluctuations.

Dynamic simulation can be used to help determine the optimum injection rate
and/or back pressure to hold on the well.
Like in single point injection gas-lift, dynamic simulation is necessary to properly
design and operate auto gas-lift systems due to the reduced flexibility.
Riser gas-lift
In some sub-sea installations, gas is injected at the base of the riser to assist with
artificially lifting the well. This may be done in addition to injecting gas downhole or
at the wellhead of the subsea well. Furthermore, if it is too difficult or expensive to
inject gas in the well or at the wellhead, riser gas-lift may be the sole form of gas-lift
used in the system. Depending on the economics, riser gas-lift may be used during
the 1st part of the field life cycle, and after the critical limit for reservoir depletion
and/or water cut increase, gas-lift can be performed at the wellhead or downhole in
the well.
Use of riser gas-lift can reduce the complexity of artificially lifting such wells while
reducing the cost of completing them. In addition, the injection of gas at the base of
the riser may help to mitigate instability problems which are common in subsea
wells containing long flowlines and/or long risers. Risers are terrain slugging
generators. Furthermore, riser gas-lift may benefit several wells connected to the
same riser while wellhead/downhole gas-lift only directly benefits the particular well.
Ideally riser gas-lift is like continuous gas-lift. It may use unloading valves in the
riser, or it may use single-point injection at the base of the riser. A significant issue
is that the liquid and gas that is entering the base of the riser, from the sub-sea
flowline that brings fluid from the wellhead to the riser, may be unstable. There may
be long slugs of liquid followed by long slugs of gas in the flowline. This can
complicate control of gas injection into the riser base.
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Dynamic Simulation of Gas-Lift Wells and Systems
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An important use of dynamic simulation is to understand the pressure and
liquid/gas rate fluctuations in the flowline as they arrive at the riser base. Then, the
simulator can be used to determine how to control the gas injection into the riser to
assist in producing the liquid and gas up the riser and to assist in mitigating the
large pressure and rate fluctuations or surges that can occur in the riser.
Based on reservoir depletion and/or water cut increase, dynamic simulation can be
used to define the length of time that riser gas-lift can economically be applied in
the system, and to select the optimum time to switch to wellhead and/ordownhole
well injection, or to perform both.
Gas-lift for gas well deliquification
Continuous flow gas-lift may be used for deliquifying gas wells that experience
liquid loading. Liquid loading occurs when liquids (normally water but sometimes
condensate as well) accumulate in the wellbore below the end of tubing in the
casing, or in the tubing itself. The liquid, being much heaver than the gas, holds
back pressure on the formation and inhibits gas flow into the wellbore and up the
tubing. Liquid will accumulate if the gas flow velocity is lower than the critical
velocity that is needed to carry the liquid out of the well.
Deliquification is a process used to remove liquids from the wellbore so gas can
freely flow. Many methods are used, including plungers, chemical systems, gas-lift,
pumping systems, and others.
In gas-lift applications, the volume of gas injected is designed such that the
combination of formation gas and injected gas will exceed the critical rate needed to
prevent liquid loading.
While gas-lift may not lower the flowing bottom hole
pressure as much as an optimized pumping system, there are a number of
advantages to using gas-lift for deliquification, including the ability to produce solidladen fluids, the ability to operate at high GLR’s, and insensitivity to well trajectory.
The goal of such systems is to inject gas at a continuous, stable rate that is just
high enough to exceed the critical velocity. Ideally, the gas can be injected below
or near the bottom of the perforated interval so that all or most of the liquid is
removed and kept from holding a back pressure on the formation. While enough
gas is needed to reach the critical velocity, too much gas will be wasteful and may
actually inhibit production due to excessive pressure losses in the production
tubing.
A concern is that the amount of gas to achieve critical flow in the casing below the
end of the tubing will be higher than the amount required in the tubing, since the
cross-sectional area is larger. Therefore, if enough gas is injected to achieve
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Dynamic Simulation of Gas-Lift Wells and Systems
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critical flow in the casing, it may be too much for the tubing. If the right amount is
injected to achieve critical flow in the tubing, it may not be enough to lift liquids out
of the casing below the end of tubing. A potential mitigation strategy is to install a
dip tube below the production packer to act as a velocity string.
A gas-lift system in a gas well may require unloading valves. It may use an
operating gas-lift valve or an orifice for the actual gas injection into the tubing.
A dynamic simulator can be used to help design the unloading process, select the
depth of gas injection, determine the OD of a dip tube, and choose the rate of gas
injection to just reach critical velocity without injecting too much. It can be used to
help diagnose problems in wells where the well may be unstable or is beginning to
experience liquid loading due to insufficient gas injection.
The steady-state aspects, dynamic aspects, and dynamic simulation of gas-lift for
gas well deliquification are explained in detail in Chapter IV-D.
Gas-lift unloading
The initial unloading process of a gas-lift well is the period of the well’s life during
which the health of the artificial lift system is at its greatest risk. This is because the
entire volume of fluids in the casing-tubing annulus must be displaced through the
gas-lift valve ports or orifices, placing the valves at risk of flow cutting and
subsequent failure. In addition, the unloading process is inherently unstable which
can result in large variations in pressures and fluid rates/volumes into the
production system. For these reasons, it is desirable to study this process in great
detail prior to performing the operation in the field.
In most cases, the unloading process is designed using steady-state methods or
programs. The gas-lift mandrels are spaced using these methods. The gas-lift
valves are chosen, sized, and set using these programs. The unloading process is
designed using these processes, or rules of thumb. This is not sufficient to fully
understand the process.
The unloading process is and must be dynamic. First, liquid in the tubing/casing
annulus is displaced through the valves in the well by applying gas pressure to the
annulus. When the top valve is uncovered, gas can flow through it and begin to
lighten the weight of liquid in the tubing. This can allow the level of liquid in the
annulus to be depressed to the second valve. The process of moving to the second
(and subsequent) valves, which requires the closing of the upper valve(s), is
dynamic.
An important role of dynamic simulation is to model the unloading process, both
during its design and subsequently during its operation. During design, the
simulator can help to determine the best depths for each gas-lift mandrel, the best
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Dynamic Simulation of Gas-Lift Wells and Systems
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liquid and gas flow characteristics of each gas-lift valve, and the best closing
pressure of each gas-lift valve. A way to do this is to run the simulator with the
design that has been calculated, and have it determine if the well will unload
successfully with this design. If it will not, the design must be modified until
successful unloading can occur. It is far better to run this process in advance with
the simulator, rather than trying the unloading process in the field and potentially
damaging the well and/or not unloading as desired.
During operation, the simulator can help determine if the unloading process worked
as intended to unload the well to the desired operating depth, without damaging any
of the unloading valves in the process. If an unloading valve is damaged (caused
to leak), the well will not be able to work below this depth and will forever be
inefficient.
Use of gas-lift for well kick-off
After a well has been unloaded and placed on production, it will be necessary to restart the well from time to time, following shut-in periods. This process is commonly
referred to as “kick-off”27.
In gas-lift wells, unless the tubing, a mandrel, a valve, or an orifice are leaking fluid
from the tubing back into the tubing/casing annulus, no fluids need to be displaced
from the annulus through the valves, as in the unloading process. However, kickoff has some similarities to initial unloading. Like the unloading process, kick-off
requires the well to step down to the operating point through a series of unloading
valves. Also, like the unloading process, the kick-off process is inherently unstable.
In such applications, dynamic simulation is useful for:

Determining if the well will flow naturally after it has been kicked-off. Some
wells merely need to be started and then they will flow naturally without the
need for gas injection.

Predicting the water cut limits for kick-off of naturally flowing wells after a shut-in
period. In other words, which wells will need to be kicked off using gas-lift so
they can return to natural flow, and when due to water increase/reservoir
pressure depletion ratio a healthy natural flowing well will need gas-lift kick-off27.
This practice:

–
eliminates deferred production problems due to waiting for a workover rig
–
helps to design natural flowing wells as future gas-lift wells, with optimum
mandrel locations with dummy gas-lift valves which will be changed for the
right gas-lift valves at the optimum time in the well’s life cycle.
Determining the required injection rate schedule to successfully return the well
to production. Many operators merely begin normal operation (injecting gas),
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Dynamic Simulation of Gas-Lift Wells and Systems
Page 67
when a well needs to be kicked off and returned to production. Questions which
should be considered are:
-
Is too much gas being used?
-
Is gas been robed from other gas-lift wells in the system?
-
Is there enough gas to put the well back online?
Use of gas-lift for wellbore clean-up
Wellbore clean-up is defined as the period when drilling debris, frac sand, and
completion fluids need to be produced out of the well, along with produced
hydrocarbons. The minimum rate and time required to clean-up the well are
important. Well clean-up is a transient operation, starting with the well closed (zero
rate) and the wellbore full of drilling fluids, and finishing when the well is at steady
state conditions free of contaminants. Dynamic simulation is required to estimate
optimum injection rate and time for well clean-up.
It may not be necessary or desired to use conventional gas-lift for this process. For
example, it may be desired to not install gas-lift valves in the mandrels during this
process. If normal gas-lift can’t be used, it may be necessary to inject nitrogen at a
high pressure through a special shear orifice or circulating valve installed in the
bottom mandrel.
A dynamic simulator can be used to help determine the gas injection pressure(s)
and rate(s) needed to achieve the desired production rates to clean the debris,
sand, and completion fluids out of the wellbore. The desired production rate will
also depend of the time required to clean-up the well. This information is provided
by the dynamic simulator41-43-44-50.
Gas-lift system distribution
Various configurations of injection gas distribution systems exist in the field.
Because of the interdependency between production system components, the
availability of injection gas and supply pressure can be affected by the operating
regimes of adjacent wells and production equipment in such systems. For this
reason, it is useful to model the performance of gas-lift wells in the context of the
entire gas distribution system.
Often this modelling is performed with steady-state systems, but clearly there are
dynamic effects that occur when wells are added to a distribution system, removed
from the system, or their injection rates are changed. To understand this process, a
field-wide simulator is needed that can model the performance of the entire gas
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Dynamic Simulation of Gas-Lift Wells and Systems
Page 68
distribution system, the source(s) of gas into the system, and the wells which are
served by the system.
This dynamic simulator can help define how to control the distribution of gas to the
wells served by a gas distribution system to optimize total production rate when
there is a change in the supply of gas into the system, or a change in the demand
for gas from the wells served by the system.
This process may be complicated if the injection rate into some wells can not be
adjusted when there is a system upset. This may occur if some wells can not be
changed since they may become unstable, if some wells are duals or intermittent,
or if some are on well test and must be held constant during the test.
Use of un-dehydrated gas
While it is recommended to always inject dry, dehydrated gas, it is not always
possible to do so. Injection of un-dehydrated gas can lead to a number of problems
including the formation of hydrates in the injection system and the flow cutting of
gas-lift valves. Such issues should be studied to determine operating practices
which may mitigate their occurrence.
Of particular importance is the formation of hydrates. These may form wherever a
pressure drop occurs in the system, such as across a surface control valve or
choke. A dynamic simulator can be used to understand the hydrate formation
potential of the wet gas, help diagnose problems that can arise due to hydrate
formation, and recommend procedures to mitigate these problems. More details
are given is Chapter VI-D, on appropriate simulation techniques, and in Chapter VIIB on hydrates. Hydrate formation may be mitigated by dehydrating the gas,
injecting methanol or another chemical in the gas, or heating the gas injection line
or control valve.
Dynamic simulation can be use to evaluate the benefits of dehydrating the gas by
comparing the results of using dehydrated versus wet gas-lift gas in the system.
The annulus can be included in the model and the amount of liquid condensing in
the annulus can be observed, as well as any annular flow effects affecting well
performance.
Use of non-hydrocarbon gases such as CO2 and N2
In certain situations, wells may be gas-lifted using an inert gas such as CO2 and N2.
For example, nitrogen is often used to start wells for initial clean-up and testing
when a high pressure hydrocarbon gas source is not available. Similarly, in a CO2
flood, the nearly pure injection CO2 or the mixture of hydrocarbon gas and CO2
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Dynamic Simulation of Gas-Lift Wells and Systems
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returning to the production station can be used to gas-lift the producing wells. Due
to the specific properties of these gasses, special considerations should be taken
when simulating, analyzing, and designing such installations. Chapter VII-B gives
details on CO2 corrosion.
Naturally Flowing Gas-Lift Wells
In certain situations, when wells can naturally flow initially but it is forecast that gaslift will be required later in the well life cycle (due to water cut increase and/or
reservoir pressure depletion), the wells are completed as gas-lift wells but with
dummy gas-lift valves installed in the mandrels. When economically viable, this
procedure eliminates the need for costly workover operations. A wireline unit is
used to retrieve the dummy valves and install the required gas-lift valves designed
for the producing conditions at the time of the operation.
Dynamic simulation may be used to define the economically optimum time to switch
from natural flow to gas-lift. Furthermore, in areas where the natural flowing well
needs to be shut-in and kicked off frequently (i.e. hurricane prone areas), the kickoff water cut limit can be defined using dynamic simulation and a safe well shut-in
can be performed ensuring that the well can be put back online without the need of
gas-lift. If the water cut is already above the amount where kick-off will be needed,
the optimum gas-lift scenario can be planned in advance.
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5. Recognize When Dynamic Simulation is Beneficial
More and more wells are being placed on artificial lift due to reservoir depletion, native
water production increase, or water flood support increase. Generally more than one
method of lift may be used; and individual methods may be classified from excellent
performance to poor. In a depletion reservoir, high initial production rates may occur
with rates declining quickly due to declining reservoir pressure and changes in inflow
parameters. In this case a preferred artificial lift method may be continuous gas-lift.
Normally, after natural flow, gas-lift is the preferred artificial lift system if enough gas is
available. In offshore and subsea wells, gas-lift is the most used artificial lift system.
To estimate the optimum time to switch from natural flow to gas-lift, and to make gas-lift
work efficiently, a good modelling tool is required. Basically there are two different types
of modelling tools available; steady state and dynamic. The advantage of dynamic
modelling, even though it is more complex, is it is helpful in understanding transient
behavior of fluid flow and flow instability inside the tubing, annulus, and flowline.
Chapter II-C, compares in detail the steady state and dynamic simulation techniques.
Use dynamic simulation to determine and respond when a well or system may
be unstable.
-
How to recognize instability.
There are several potential causes of instability in a naturally flowing well:
decreasing reservoir pressure, increasing water cut, over-sized tubing for the
current fluid production, decreasing total gas-liquid ratio, and increasing back
pressure in the surface gathering system. To recognize and rectify these
problems, a tool is needed to model the well in its current flowing conditions.
The model may either be a steady state or dynamic model but certain flowing
conditions warrant dynamic modelling to understand liquid loading, phase
separation, and gas velocity issues due to multiphase fluid flow up the
production tubing. Usually most completions are not vertical and may be highly
deviated where theoretical correlations are not capable of accurately predicting
the actual fluid flow results.
Even more in-depth analysis may be required for gas-lifted wells as there are
additional reasons for unstable flow due to:
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
inefficient lifting caused by a leak through shallow unloading gas-lift
valves

insufficient injection gas rate for the fluid rate and the tubing size

operating orifice not properly sized thus transmitting large volumes of
gas into the tubing.
Dynamic simulation can help identify the reason(s) for unstable flow and
estimate where and when slugging is originating. Furthermore, dynamic
simulation can establish the size and frequency of the slugging severity.
-
How to recognize the situations where instability may arise.
Well production trends, and surface tubing and casing pressure and
temperature measurements, may indicate the probable onset of instability.
Gradual decline in produced fluid with increased annulus pressure may indicate
liquid loading. See Fig. IV-1.
Fig. IV-1: Well Production Trend – Rate (Green), Pressure (Red), Temperature (Blue)
If tubing pressure starts fluctuating and there is a gradual increase in the
pressure band, this may be an indication of gas separation and liquid fall back in
the tubing. Reduced total gas liquid ratio may indicate that the well needs gaslift assistance to maintain stable flow.
-
Determine how to stabilize unstable wells.
To stabilize a well, it is important to identify the root cause for the instability (e.g.
annular heading).
Use accurate field data to build the dynamic well model and analyse the causes
for instability. There may be one or multiple causes that make the well unstable
and it is important to address all the probable causes and rectify them to make
the well perform efficiently. The dynamic simulator can be used to analyze the
reason(s) for unstable flow and evaluate the best solution(s) to stabilize the well.
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Some of the solutions that can be evaluated are:
–
Reduce tubing size (during well design or workover operation)
–
Increase back pressure (this will reduce maximum production rate)
–
Optimize gas injection (where? how much?)
–
Automate real-time gas-lift (using an online dynamic simulator)
Use dynamic simulation to determine when to use gas-lift to re-start wells.
This can be due to:
- High water cut
- Low bottom-hole pressure
- Poor well inflow performance
- High back pressure in surface facilities
- Other issues.
Fig. IV-2: Well Unloading - Dynamic Simulation
Use a dynamic simulator to match the well’s current flowing conditions with the
measured field data and run sensitivity analyses for a range of different water cuts,
reservoir pressures, and other inflow condition changes that are expected, like
change in the productivity index or skin. Properly matched well performance
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characteristics will validate the model and should give a clue about the onset of
instability due to changes in water cut, reservoir pressure, or other inflow
parameters. See Fig. IV-2. If the well-reservoir interaction is strong, it may be
necessary to couple the well model with a reservoir model to properly predict the
decline rate and water break through with time.
Use dynamic simulation to define the kick-off water cut limit (the water cut above
which unloading is needed) to plan a safe well shut-in. If the water cut is below the
limit, the well can be put back online without gas-lift. If the water cut is above the
kick-off limit, the optimum gas-lift scenario can be planned in advance.
Use dynamic simulation to determine when to start gas-lift in a flowing well.
A dynamic simulator may be used to analyse natural flowing wells for optimization
opportunities and to help determine when to start gas-lift. The purpose of gas-lift is
to achieve reduced flowing bottom-hole pressure so the reservoir can deliver the
desired production rates. A dynamic model can predict the optimum injection point
and the required amount of lift gas for optimum well performance, and to start gaslift. See Fig. IV-3.
Fig. IV-3: Well Dynamic Simulation Output Comparison
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Use dynamic simulation to determine the need to start gas-lift due to liquid
loading in gas wells.
A major issue with gas well production is liquid loading, usually with water but
sometimes with condensate or a combination of water and condensate. Depending
on the reservoir inflow characteristics, the well may experience loading issues
sooner or later in the well’s life cycle, either due to reservoir pressure depletion,
decreased gas rate, or increased liquid production. In Fig. IV-4, it is assumed that
the end of tubing (EOT) does not extend to the mid-perforations so that there is a
section of casing from the EOT through the perforations.
Fig. IV-4: Life history of a gas well.
Initially the well may produce at a high rate so the flow regime is mist flow in the
tubing. However it may be in bubble, transition, or slug flow below the EOT. As
time increases and production declines, the flow regimes from the perforations
to the surface will change as the gas production declines. Flow at the surface
may remain in mist flow until the conditions change sufficiently so the flow
exhibits transition flow. At this point the well production becomes erratic,
progressing to slug flow as the gas rate continues to decline. This transition will
often be accompanied by a marked increase in the decline rate. Eventually, the
unstable slug flow at the surface will transition to a stable, fairly steady, lower
production rate. This event occurs when the gas rate is too low to carry liquids
to the surface and simply bubbles through a stagnant liquid column. If corrective
action is not taken, the well will continue to decline and will eventually die.
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Dynamic simulation can be used to predict the onset of liquid loading. Well
completion design also affects liquid loading, depending on provisions made for
the type of artificial lift, and available infrastructure resources such as electric
power, lift gas, and wellbore accessibility.
- Dynamic simulation can predict the following for a gas well:
-

Onset of liquid loading

When to simulate various deliquification methods

Best deliquification method with the existing completion

Better completion options for recompletion/work-over

When to use a hydrate inhibitor.
Method to predict when the gas well will load and die.
To plan and design for liquid loading, it is necessary to predict when it may
occur. Generally the Turner, et. al. critical velocity concept and steady state
techniques are used to predict the onset of liquid loading. These are
reasonably accurate for near vertical wells. See Fig. IV-5.
Fig. IV-5: Liquid Transport in Vertical Wells
Liquid is lifted by the gas flow as individual particles, and as a liquid film along
the tubing wall by the shear stress at the interface between the gas and the
liquid. Turner, et. al. developed a simple correlation to predict the critical velocity
in near vertical gas wells assuming the droplet model.
The critical velocity is defined as the minimum gas velocity in the production
tubing required to move droplets upward. Two variations of the correlation were
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developed; one for the transport of water and one for condensate. Although
critical velocity is the controlling factor, these correlations are easily converted
into a more useful form for computing a critical flow rate and a critical tubing
diameter. See Fig. IV-6.
Fig. IV-6: Minimum Gas Rate for Unloading the Well
These correlations can be used to compute the critical gas flow rate required to
transport either water or condensate. See Fig. IV-7. When both liquid phases
are present, the water correlation is recommended.
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Fig. IV-7: Completions Effects on Critical Velocity
Fig. IV-8 shows the typical steady state stability analysis using the tubing
performance and IPR reservoir deliverability curves.
Fig. IV-8: Tubing performance curve in relation to well deliverability curve.
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Dynamic Simulation provides an understanding of multiphase flow and the role
of parameters such as pressure-temperature gradients, deviation, and tubing
size, as well as the effect of inflow performance on liquid loading32-33. Transient
multiphase flow modelling offers new insights into the mechanisms of liquid
loading. The onset of liquid loading is triggered by film flow reversal rather than
droplet flow reversal, when the droplet drag force no longer exceeds the droplet
gravity force. Dynamic simulation matches actual liquid loading better than the
Turner model in that it provides a more realistic description of liquid loading.
Dynamic simulation is used to obtain realistic values of reservoir abandonment
pressure based on actual surface data measurements.
To predict when the gas well will load and die, it is required to accurately model
and history match the well with current field data. Run the dynamic model with
time series for expected reservoir pressure decline, gas/liquid fraction changes,
and surface boundary condition changes.
-
Deal with liquid loading in gas wells.
Based on the dynamic simulator’s prediction of onset of liquid loading and the
amount of liquid production, select the optimum tubing internal diameter and/or
apply artificial lift using either plunger lift, chemical, gas-lift, or pumps. Run
simulations to select and optimize the proper deliquification method that is
suitable for the gas well based on economics and available resources. Based
on the uplift predictions and work-over/recompletion costs, decide on the most
suitable deliquification method and apply to the existing completion or add to the
new recompletion design.
Use dynamic simulation to aid in optimizing intelligent and complex well
completions.
Intelligent well completion technology was developed as part of the global
industry trend toward improving reservoir productivity. This technology enables
multiple reservoirs to be intersected by a single well and controlled remotely. The
ability to manage reservoirs remotely also reduces potential well intervention
costs. Although most intelligent well completions have been installed in offshore
wells, service providers have begun installing them on land as well. An intelligent
well is equipped with sensors/monitoring equipment and completion components
that can be remotely adjusted to optimize production. This optimization typically
involves flow control that takes place down hole via remote control from the
surface, without physical intervention.
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While there are exceptions, the key components of a typical intelligent completion
are:
1. Flow control devices, which are usually hydraulically-operated control valves
used to control flows into and out of the reservoir.
2. Feed-through isolation packers that enable hydraulic control lines to be fed
through to subsurface control valves.
3. Down-hole sensors which report pressure, temperature, and flow rates back to
the surface.
4. Control systems comprising hydraulic and/or electrical surface systems used
to monitor and control subsurface conditions.
Production from multiple zones historically required complicated completions with
multiple packers and multiple tubing strings, assuming the wellbore could
accommodate two or three tubing strings. If this was not feasible or cost-effective,
a sequencing of production was implemented, starting with the bottommost
(highest-pressure) zone, and then moving to the upper reservoirs as the lower
ones depleted, to avoid cross-flow. Intelligent well completions enable the
operator to alternately produce the lower and upper reservoirs, accelerating total
production and increasing the net present value of the well.
Furthermore, reduced well intervention costs can make a significant difference,
given the expense of rig time, especially in deepwater and subsea wells, and
deferred production caused by schedule delays. The ability to reconfigure wells
remotely reduces the need for physical intervention.
To deal with intelligent well completions, the dynamic simulator needs to model
down-hole equipment such as inflow control devices, safety shut-down systems,
and hydraulic control valves/devices. See Fig. IV-9. Dynamic models are
capable of using simple control valves to represent and simulate the same effect
of those devices when the particular flow coefficients (Cv) of the devices are
known.
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Fig. IV-9: Remote Well Control Device
Dynamic simulation can help optimize the design of intelligent wells. Several well
completion dynamic model options can be run and results compared. Costly
intelligent control devices can be justified by validating with the dynamic model
the expected improvements that can be provided with and without these devices.
Optimum liner size and the minimum number of control devices can be optimized
by analyzing the multiphase flow along the productive interval, including linerformation annular effects. This is necessary in extended reach, maximum
reservoir contact wells and multi-laterals. The dynamic simulator allows as many
inflow points as required (each of them with a different inflow performance
relationship or productivity index, permeability, skin, gas/oil ratio, and water cut, if
necessary) to describe the flow characteristics along the multi-entry productive
intervals, including water and/or gas conning effects.
The application of dynamic simulation is also relevant to optimize production
operations and maximum recovery from these complex intelligent wells during the
field life cycle. Although normally the ultimate strategic cognitive activity or
intelligence has been provided by the field operator based on expert visualization
and interpretation of the processed data.
A great deal of the logical workflow associated with the data acquisition,
processing, and resultant action normally provided by the operator are the
consequence of the automated control responses provided for the controller and
actuators following a predefined optimization or functional algorithm. This makes
the operator’s work simpler.
This is especially true if the automated responses are coupled to real-time, online
dynamic simulation.
“What-if” and “look-ahead” dynamic multiphase flow
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simulations from the fluids flowing into the well, including the lift gas, can be
performed using actual data provided by the SCADA system connected to the
dynamic simulator. Dynamic coupling with a near wellbore reservoir simulator to
quantify the flow provided from each production interval may be necessary when
the well reservoir interaction is significantly high.
The predictive “look-ahead” simulation will provide the operator with the
predictions regarding future states of production to make operational decisions
and take actions supported by the “what–if” simulations to analyze the
consequence of actions or decisions to improve the production performance of
the wells.
Intelligent wells/completions require real time production information and control
and therefore dynamic simulation is the best type of simulation to optimize these
applications
Use dynamic simulation to aid in understanding when cross flow and/or
commingling occur.
Recent well completions are more complex as they produce from multiple zones
in either vertical, deviated, or horizontal wells. There are possibilities for cross
flow between zones during well shut-in and while the well is flowing with very little
drawdown or the flowing bottom-hole pressure is significantly higher than the
pressure of one of the upper producing zones. Dynamic simulation can be used to
understand transient flow conditions and cross flow occurrences. It is important
to model the well trajectory. Create enough pipe segments to estimate and
optimize commingled production from each zone of interest. Also model each
zone as a separate source/well, with its particular inflow reservoir and fluid
properties, so fluid production, cross flow, and fluid movement from each zone
can be evaluated for different flowing bottom-hole pressure and reservoir
depletion scenarios.
Dynamic simulation can be used to justify commingling different production zones
or increasing the cost of the well completion to produce them separately for
proper reservoir management.
Intelligent well completions enable multiple reservoirs to be accessed with a
single well while avoiding the common problem of cross-flow caused by different
reservoir pressures. In addition, intelligent completions of injection wells enable
greater control of injection and improve the recovery of hydrocarbons from offset
production wells.
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Dynamic Simulation of Gas-Lift Wells and Systems
In multi-lateral wells, there are situations where one lateral may not contribute
when the flowing bottom-hole pressure (Pwf) is higher than the layer pressure of
that lateral near the wellbore.
Figure IV-9 below shows possible cross flow situations during well flowing.
Pwf=2550psia
Lateral - A
Pr=2690psia
60 ft
Lateral - B
Zone - A
Pr=2775psia
Zone - B
Zone - C
Pr=3140psia
Pr=2725psia
3860 ft
Fig. IV-9: Possible Cross-flow Situations during Well Flowing
Psi=2710psia
Lateral - A
Pr=2690psia
Lateral - B
Zone - A
Pr=2775psia
Zone - B
Pr=3140psia
60 ft
Zone - C
Pr=2725psia
3860 ft
Fig. IV-10: Possible Cross-flow Situations during Well Shut-in
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Generally the cross flow is aggressive soon after the well is shut-in and it will
usually cease once the pressures are equalized near the well bore region.
Dynamic simulation may be used to optimized design and production from multilayer and multi-lateral well completions.
Use dynamic simulation to optimize gas-lift well and system shut-in and startup operations.
The application of dynamic simulation to design and operate the shut-in and startup of pipelines and facilities is a standard procedure in flow assurance studies
performed by facilities engineers. In these studies, wells are normally included as
flow sources, or the well completion model is simplified. Therefore flow assurance
in the wellbore upstream of the wellhead is rarely performed and the total system
is not integrated. This can lead to significant errors in the flowline-riser-facilities
design as well as unsafe operations and production optimization problems. The
detailed well description should be included in the final dynamic simulation design
and the total system should be integrated to define the interactive behavior of the
system. Chapter V-D, provides more details on the appropriate ways of
implementing dynamic simulation.
The particular shut-in and start-up conditions associated to the type of artificial lift
system also need to be included. Chapter III-J and K provide details for using
dynamic simulation to optimize well kick-off and well clean-up.
Gas-lift is a widely used artificial lift methods in oil production. However, gas-lift is
an inherently unstable, dynamic process and optimized gas-lift design requires
that gas-lift wells be operated on the up-slope of their tubing performance curve –
Fig. IV-11a.
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Fig-IV-11a: Effect of tubing performance curve on liquid production rate
qL
qinj
Fig-IV-11b: Effect of gas-lift rate (qinj) on liquid production rate
Gravity effects become the dominant factor of gas and liquid two-phase flow in
the tubing and this two-phase vertical flow is often unstable. Unstable production
under gas-lift is often called well heading. This unstable operation leads to
periods of reduced or even no liquid production followed by large slugs of liquid
and gas. Operators usually try to overcome this unstable operation by increasing
the amount of lift gas beyond the optimum rate (Fig-IV-11b), but this practice may
lead to a worsening stability condition.
To better understand gas-lift stability problems, a description of the gas-lift kick-of
process is given below.
1. Starting with an annulus pressure down-hole that is lower than the bottom-
hole tubing pressure, there is no gas flow through the down-hole gas-lift valve
into the tubing. Production rate from the reservoir, if any, is low. As gas is
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injected through the surface gas injection choke or control valve, the annulus
pressure starts to build.
2. Given some time, the annulus pressure exceeds the bottom-hole pressure
and gas is injected into the tubing through the gas-lift valve.
3. The injected gas lightens the fluid in the tubing by effectively reducing its
density and back pressure and the liquid production rate from the reservoir
begins to increase.
4. Gas flows from the annulus into the tubing at an increasing rate. If gas is
supplied at a constant, adequate rate, liquid production can become stable.
Unstable operation
5. If insufficient gas is supplied, the annulus pressure will decrease rapidly and
gas-lift valves will start to open and close intermittently. This depends on
annular pressure build up cycles due to a gas injection rate that can increase
the annular pressure and open the gas-lift valve against the tubing pressure.
6. With decreasing or intermittent gas flow through the gas-lift valve, the liquid
density of the fluid in the tubing increases. Then production rate decreases or
can even stop.
7. During these cyclic periods, the tubing pressure may exceed the annulus
pressure, and gas injection into the tubing stops. Continued gas injection into
the annulus eventually will build the pressure again and more gas will be
injected into the tubing, generating a surge of production. These unstable
production operations are frequently called heading.
To deal with this unstable operating condition generated by the gas-lift process a
good approach is to use dynamic simulation with the automatic control system.
This method of setting an automated control system relies on dynamic, transient
gas-lifted well models by maximizing the lift gas efficiency and capturing the well
and process knowledge developed in the dynamic model48-49.
The concept is to analyze and design stabilizing controllers. If applicable,
estimators can be based on a dynamic model of the system. For this purpose a
simplified dynamic non-linear model based on physical principles of gas-lifted
wells, that is suitable for controller and estimator design, can be developed.
The main purpose with this dynamic model is to describe the interactions between
the annular space and tubing which leads to the unstable behavior at low and
intermediate gas injection rates. It is necessary that the model becomes stable at
high gas injection rates. The idea is to use a simple model basically relying on
three differential equations conserving mass in the tubing and casing, and
algebraic equations of state for approximating energy and impulse balances. At
the cost of a more complicated, yet accurate, model, differential equations
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describing energy balances and impulse balances may also be included. To
summarize, the nonlinear dynamic gas-lifted well model consists of:

Model of the pipes (casing and tubing):
1. Three ordinary differential equations conserving the mass in casing and
tubing.
2. Algebraic equations of state relating pressure, temperature, and liquid and
gas holdup to each other in casing and tubing.
3. Algebraic equations for pressure heads.

Model the gas injection choke: An algebraic equation describing the relation
between the pressure upstream and downstream of the gas injection choke
and the mass flow rate through the choke.

Model the gas injection valve: An algebraic equation describing the relation
between the pressure upstream and downstream of the gas injection valve
and the mass flow rate through the valve. The equation will vary depending on
the type of valve used.

Model the production choke: An algebraic equation describing the relation
between the pressure upstream and downstream of the production choke and
the mass flow rate of gas and liquid through the choke.
The advantages with this simple dynamic model structure are many.
Compactness is one appealing feature since a set of ordinary differential
equations and algebraic equations are used. Secondly, it is able to capture the
main dynamic behavior of gas-lifted well both at low, medium (unstable operating
conditions) and high (stable operating conditions) gas injection rates. Chapter VIB provides more details on real-time dynamic simulation.
Another option to deal with these unstable operating conditions generated by
shut-in, start-up, and the gas-lift process itself is by direct application of a realtime, online dynamic simulator. Chapter IV-D provides details on this type of
application.
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6. Information Required for Dynamic Simulation
This chapter describes the information required to use dynamic simulation for gas-lift
wells and systems. Similar to other transient multiphase flow hydraulic analyses,
studying gas-lifted systems requires input in the following categories:
a. Fluid properties (PVT characteristics).
b. Flow path geometry and equipment.
c. Inflow performance relationship (IPR).
d. Boundary Conditions.
The main difference between steady state and transient simulation is the latter also
provides changes in the hydraulic status of a well from the specified initial conditions.
The input for a transient hydraulic analysis should include the initial pressures,
temperatures, and rates in the system. Any operational event that creates a change in
the system needs to be specified along with its associated time.
Another difference between steady state analysis and transient simulation is dynamic
simulation requires the mathematical input necessary to solve differential equations.
This includes: one dimensional grid section length, and integration and time step data.
Integration data includes start and end times for the integration, maximum and
minimum integration time steps, and CPU limit information. Defaults normally are
provided and suggested by the dynamic simulator and can be modified to speed the
simulation time and/or make the run more mathematically stable. One dimensional grid
section length will define the number of differential sections in the system and therefore
the time required for the simulation run. The longer the section length, the shorter the
simulation time, but the results are less accurate. For example, liquid hold-up
calculation accuracy is reduced when using relatively large section lengths. The shorter
the section length the longer the simulation time, but the higher the accuracy. A
compromise needs to be reached between section length and accuracy.
The rest of this chapter explains the main inputs.
Fluid properties
A successful design and operation of a gas-lift well, requires predicting flowing fluid
characteristics. Most of the transient multi-phase flow simulators give users an
option to choose the amount of detail in defining the fluid properties. The
possibilities are:
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Dynamic Simulation of Gas-Lift Wells and Systems

Black oil correlations

PVT tables

Fully compositional modeling.
Page 88
Using a black oil correlation is a simplistic approach for describing phase behavior
of hydrocarbon mixtures. The word simplistic should not be mistaken as inaccurate.
In-situ fluid properties are calculated by using user specified oil density (API
gravity), gas specific gravity (density), and GOR at standard conditions. Most of the
software packages also provide a module to tune the selected black oil correlation
to better match the fluid properties. A correlation should not be adjusted or tuned
more than 10% as this will reduce the predicting accuracy of the correlation, and an
unsuccessful adjustment is worse than no tuning. Most of the black oil correlations
are based on the properties of hydrocarbon mixtures from one specific region, and
they are only valid in a certain range of pressures and temperatures. It is important
to know the applicability of a black oil correlation in its pressure and temperature
range and hydrocarbon types.
Using a PVT table is another way of specifying fluid properties for transient
hydraulic analysis of gas-lift systems. The transient multi-phase flow simulator does
no fluid property calculations, but it picks the in-situ fluid properties such as phase
fractions and densities from a previously constructed PVT table. To create a PVT
table, a fluid model is prepared in a PVT package. This model includes the
hydrocarbon composition and its measured properties at different pressures and
temperatures. The measured properties are used to tune the composition so the
selected equation of state will reflect the flowing fluid characteristics.
A PVT report normally contains different laboratory data sets. These are:
 The saturation point,
 The separator tests,
 Constant composition expansion (CCE),
 Constant volume depletion (CVD), and
 Viscosity measurements.
The first three sets best describe what the fluid goes through in a gas-lift production
system. These sets should be used to tune the fluid properties, and then apply
viscosity tuning before creating the PVT tables.
The CVD data is related to reservoir engineering applications, and is not applicable
for short term performance analysis of a production system. The question of “is it
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harmful to involve the CVD data” may rise here. It is impossible to obtain tuning
which 100% matches all the different fluid data sets. While trying to get close to one
type of measurement, the accuracy of the model in another type of measurement
will be sacrificed. The aim of the analysis should determine the data to be used in
tuning the fluid model. After these preparations, a PVT table with sufficiently large
pressure and temperature ranges should be generated for use in the transient
hydraulic analysis of the gas-lift well, riser, and pipeline. The same PVT table can
be used for the lift gas, as the produced gas is normally recycled in the gas-lift
systems.
Fully compositional modeling is not normally preferred because it is computationally
demanding (the hydrocarbon composition is flashed at every in-situ P-T), but it is
recommended to achieve accuracy.
There are several occasions that require this capability. One example where fully
compositional PVT modeling is required is in a multi-layer well completion with
commingled production of significantly different reservoir fluids. In this situation the
produced fluid composition will differ from one flowing bottom-hole pressure to
another. Hydrocarbon compositions for different reservoirs need to be known and
tuned with the appropriate data sets as explained above. Furthermore, the dynamic
simulator should be able to track the different fluid compositions in the system, and
the resulting fluid mixes along the producing path. Another relevant example is
when the gas used in the gas-lift system has different composition than the
produced gas. In order to properly evaluate stability in the flow path where there is
a mix of the two gases, the different gas compositions needs to be known and the
resulting mix calculated.
As a rule of thumb, if phase changes are expected in the system (i.e
gas/condensate wells from reservoir to wellhead), a fully compositional model will
give more accurate P-T and liquid hold-up calculations than a black-oil correlation.
Well Profile and Well Schematic
Calculating pressure drop, whether the well is operating in steady or transient state,
requires estimation of pressure losses due to friction, gravity, and acceleration. The
distance traveled by the fluid along the wellbore and in the vertical direction
determines the friction and the gravity components, respectively. The resulting
multiphase flow regime is affected by well deviation. Therefore, an accurate
representation of well trajectory is the first step in constructing a transient model for
a gas-lift well. It is also important to represent the exact profile of horizontal and
deviated wells, because these profiles (ups and downs) can generate terrain
induced slugging. Some software packages accept only horizontal and true vertical
depth couples for specifying the well trajectory. Others work with depth versus
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deviation data. Some software packages limit the number of points to describe the
well profile which can lead to errors in slugging predictions.
Specifying the geometry where the flow takes place is the next step in constructing
a transient flow model. Diameters with associated depth intervals from the
completion diagram are needed in the model. This is important because the
velocities, Reynolds numbers, and consequently the friction in the system are
directly affected by these diameters. In cases where the flow is multiphase, such as
in gas-lift, it even affects the hydrostatic pressure drop because the liquid holdup is
determined from the velocities of the flowing phases.
Any well equipment, such as valves and chokes, must be entered together with
their pressure drop characteristics, openings, and depths. For example, to model
unloading, all unloading valves need to be specified together with their valve
pressure drop characteristics and opening and closing pressures. Some software
packages which were originally designed for gas-lift design and analysis, may
already have a valve database to capture this information.
To obtain accurate P-T calculations along the well profiles and at the wellhead, the
well completion diagram including all casings and annular fluids, cement and
formation thickness, and heat transfer coefficients for each constitutive material,
must be entered in detail. This data is used to estimate the radial heat losses in the
wellbore which is a function of the number of concentric walls. The use of “overall
heat transfer coefficients” to estimate these heat losses is a simpler option
(standard practice in steady state calculations) which is not recommended in
transient simulations because it does not take into account thermal mass and heat
storage effects in the different materials. In risers, a detailed temperature profile
from sea surface to mud line, including variations in water current velocities, is
recommended when there is potential for hydrates or production chemistry
problems. This information is used as a boundary condition and may influence riser
temperature profiles and flow head temperature calculations at the platform or
mobile offshore drilling unit (MODU).
Inflow performance relationship
The IPR defines how much reservoir fluid can be produced at different flowing
bottom-hole pressures and temperatures. It quantifies the flow resistance in the
formation and in the well/reservoir interface. The IPR or PI is a steady state
definition. However, studying any transient phenomena needs to be coupled with a
well’s inflow performance because the production will vary depending on the
changes in flowing bottom-hole pressure.
For an existing well, the IPR can be obtained from multi-rate well test data. The
curve, which connects measured flowing bottom-hole pressures at different rates, is
the IPR. If the well is not on production yet, analytical methods may be used for
predicting the IPR by taking the formation permeability and its thickness, expected
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drainage area, well radius, well/reservoir interface, and the PVT of the reservoir
fluids into account.
The IPR has to be entered in the transient simulator in a required format, which can
either be a table, the linear PI type, a Forchheimer model, or a Vogel model.
Depending on the purpose of the analysis, e.g. for studying the initial startup of a
gas-lift well and its clean-up performance, it is better to use the distributed IPR
approach. This requires dividing the productive interval into segments and
calculating individual IPRs depending on the segment characteristics, as in
permeability. These inflow sources can be input to the transient simulator at their
corresponding depths to accurately visualize the inflow distribution and completion
fluid clean-up performance. The number of the inflow sources depends on the
required level of accuracy. A similar approach can be used in commingled gas-lift
producers. If the well is producing from several different reservoirs, every inflow
zone can be modeled with a separate IPR for a more detailed analysis. Changes in
the reservoirs’ pressures and temperatures due to depth differences also need to
be reflected, as well as changes in GLR and water cut.
As explained in Chapter II-B, some dynamic simulators offer two IPR options, the
standard IPR definition for steady state conditions or the quasi-dynamic IPR
definition where the key reservoir properties can change with time. When the
dynamic model is used for forecasting purposes, i.e. “what if” scenarios, the use of
the standard IPR definition is sufficient since it can give a reliable indication of worst
case scenarios. When the dynamic model is used for matching measurements, the
use of the quasi-dynamic IPR is required, and the selected variables such as skin,
non-Darcy skin, and permeability can be input as time-series so the impact of the
transient behavior can be reflected.
Boundary Conditions
For every inflow source, the reservoir pressure and temperature have to be
specified. The wellhead back pressure and temperature, assuming the model stops
in the wellhead, are also required for the calculations. If the transient model has a
wellhead bean or choke, the wellhead P-T need to be specified downstream of the
wellhead choke. The surface injection P-T together with the amount of injected gas
needs to be input, if the injection model starts at the wellhead. Apart from these
boundary pressures and temperatures, the transient simulators require the well’s
initial fluid content and the associated pressures and temperatures including the soil
temperature gradient, surface-subsea temperature gradient, and ambient
temperature. These are used as the start up conditions for the calculations at time
zero.
Any planned changes in the wellhead and surface injection pressures, or in lift gas
injection rate, have to be entered as time series so that their impact on the transient
behavior can be determined.
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7. Application of Dynamic Simulation
This chapter describes when and how dynamic simulation modelling may be applied.
Integrated modelling
When is it sufficient to only model the wellbore?
Gas-lift is usually a multi-well system and for optimum system design and
operation, the total system needs to be modelled.
It is sufficient to model the wellbore of a single well with a short surface pipeline
when the well is at early stages in the design of the gas-lift system and/or when
the initial troubleshooting efforts are focused on a particular well.
When focusing on one well, the model can be as simple or as complex as
required. The annulus can be included in the model as a flow path and the
counter-current heat transfer effect of injecting a relatively cold lift gas in the
annulus and producing a hot reservoir fluid in the tubing can be evaluated. In the
case of wells where the annulus cannot be vented and fluids are trapped in the
annular space, the increase in annular pressure and temperature when opening
the well to production can be modelled and the maximum annular P-T calculated
based on the expected production rates. This allows proper design of the casing,
tubing, and wellhead to withhold the generated stresses.
Basically, the study objectives will define the limits of the model. Section D in this
Chapter explains in detail the appropriate process to select the parts of the gas-lift
system to be incorporated in the model according to the study objectives.
Sooner or later the use of an integrated dynamic simulation model is
recommended. This will account for any well-flowline-riser interaction effects.
When must an integrated model of reservoir, near wellbore reservoir area,
inflow, outflow, flowline, and surface systems be used?
When using an artificial lift system like gas-lift, the production system has a
restricting flow condition that may prevent it from producing more fluids to the
production facility.
These flow restrictions may be located or generated at any point between the
near well bore reservoir area, the well, the pipeline(s), and the process
equipment. An integrated dynamic simulation model is necessary to fully
understand the system production behavior and to maximize production.
Among those restricting conditions, the mechanisms that will increase the back
pressures in the system, such as slugging, increasing water cuts, lower
temperatures, increased viscosities in heavy oils, and solids depositions should
be considered.
If any of the above flow restrictions are affecting the components in the production
system, e.g. flow branches, wells, and process equipment, these will affect the
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other components of the system. It is necessary to understand these effects to
find or devise a solution that will allow the system to be operated in a safe, stable
manner, and to maximize production.
Furthermore, if there is a strong reservoir-wellbore interaction, the dynamic
simulator may need to be integrated to a dynamic near-wellbore reservoir
simulator model. However, the use of a quasi-dynamic IPR may avoid or
postpone this need. When formation damage, multiple and/or commingling
reservoir production zones, or other reservoir flow restrictions exist; the following
cases may have strong well and near-wellbore interactions:
–
Well kick-off and cleanup
–
Well testing
–
Shut-in/start-up
–
Dynamic water and gas coning
–
Liquid loading
–
Bull heading and injection
–
Cross flow
–
Formation heading and wellbore slugging
Often, after a few months or years of production, the diminishing driving force of
the reservoir to produce the hydrocarbon fluids to the surface demands the use of
some sort of artificial lift. Then the original design of the production system may
be oversized for the now reduced production rates and increased water cuts. The
development of some form of liquid slugging on the surface pipelines may have
an amplified effect in the well or wells and in the reservoir. These system
interactions between different components in the production system may not be
fully understood unless a dynamic integrated simulation model is used.
Section D in this Chapter explains in detail the appropriate process to select the
parts of the gas-lift system to be incorporated in the model according to the study
objectives.
Real-time modelling
Real-time modeling requires simulation of responses at a frequency consistent
with the frequency with which the responses occur in the physical system that.
Animation of well response requires real-time modeling.
Some transient
responses may be rapid and require simulation at higher frequencies to capture
the effect. Rigorous simulation methods may be slower than real-time, so realtime modeling may be less precise.
For a gas-lift well, one might close the production choke while a SCADA system
collects surface measurements such as production rate and pressure, and
injection rate and pressure over time. A dynamic simulator could predict these
measurements at a given time.
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Dynamic Simulation of Gas-Lift Wells and Systems
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Online dynamic simulation tools offer the possibility of running “what-if” simulation
scenarios using current P-T and rate data gathered by the SCADA system and
automatically input to the dynamic simulator. The surface P-T and rates, as well
as the downhole reservoir P-T conditions, may have changed since the last shutin dynamic simulation analysis was performed. Online real-time modeling allows
the model to be re-run using updated field information to evaluate if, for example,
the potential for hydrate conditions have changed when planning a well shut-in.
Guideline procedures for well shut-in may be revised for safer operations.
The online dynamic simulator can also be used as an advisor and a data source
by creating virtual instruments in the system to validate actual instrumentation, to
replace damaged instrumentation, and to locate virtual instruments where there is
no physical instrumentation.
The value of using steady state software in real-time to monitor and optimize oil
and gas production has been recognized by the industry. Online real-time
dynamic simulation software applications offer a wider range of coverage and
protection by including the possibility of modelling most unsafe transient
operations and flow assurance scenarios. And they offer the option of using the
virtual model of the gas-lift system as a training simulator to generate “what-if”
scenarios for personnel involved in design, operation, and system optimization.
The main advantages of online, real-time, dynamic simulation are:
•
Test any operating procedure with current data before performing required
operations
•
Expand the operating envelope with flow assurance limits
•
Enable better testing / production strategies based on most up-to-date
information
•
–
Faster clean-up on start-up / testing
–
Stability / slug monitoring and tracking
–
Optimize gas injection
–
Optimize inhibitor injection including optimum amount of MEG/MeOH
–
Minimize risk of hydrates and blockages
Warn of potential abnormal situations
–
Reduce potential for shutdowns and deferred production
•
Ensure stable operation and optimized production
•
Reduce unplanned shutdowns
•
Improve short-term production forecasting
•
Reduce uncertainty for better decision making
•
Use extensive virtual instrumentation
API RP 19G11
•
Dynamic Simulation of Gas-Lift Wells and Systems
Page 95
Empower a focal-point for multi-discipline knowledge building
Use of dynamic simulation modelling for gas-lift system management
Dynamic system models may have several practical uses in gas-lift.
include:

Assisting with designing gas-lift installations

Confirming or validating that a given design will work properly

Helping to identify problems with a gas-lift system operation

Helping to diagnose the causes of gas-lift operating problems

Helping to troubleshoot or find solutions to specific problems

Helping to optimize a gas-lift system operation
-
Using dynamic simulation in gas-lift design
These
Gas-lift design consists of two components: (1) determining the spacing of
the gas-lift mandrels, and (2) determining the size and settings of the gas-lift
valves and/or orifice. Normally, the mandrels are spaced when the well is first
completed or worked over and/or recompleted.
Most conventional gas-lift design programs use steady-state pressure
traverses for the injection and production pressure profiles. The mandrels are
spaced using these profiles. The mandrels must be spaced so the well can
unload to the deepest operating point, and continuously operate at this depth,
without multi-pointing or working back up the well. This design process is
discussed in API RP 11V6.
But for many gas-lift wells, especially wells with horizontal completion
intervals, the actual pressure profiles may not be steady; they may fluctuate
dynamically as the well unloads and operates.
By using dynamic simulation, mandrels can be spaced so unloading and
continued operation from the deep operating valve/orifice can be assured,
even if the well operates in an unstable, dynamic fashion.
When it is time to place a well on gas-lift, the gas-lift valves and orifice must
be sized and set. The valves must be designed to permit the correct amount
of lift gas injection for unloading, but not so much as to waste gas or prevent
working down to lower unloading mandrels/valves. Steady state design of
injection pressure operated (IPO) gas-lift valves is covered in API RP 11V6.
Design of production pressure operated (PPO) valves is covered in API RP
19G9. Use of dynamic simulation can help assure that the valves are
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Dynamic Simulation of Gas-Lift Wells and Systems
Page 96
selected and set properly to permit effective unloading and operation from the
desired deepest point.
-
Gas-lift design confirmation
Normally, the mandrels are installed when a well is first completed or
recompleted. Normally, this was done using a conventional design program
with steady-state pressure profiles.
In this case, it isn’t possible to use dynamic simulation to space the mandrels,
but the design can be checked with a dynamic simulator to confirm or validate
that it will work properly for unloading and operation from bottom. If the
simulator indicates that the design will not work as desired, then adjustments
can be made in the design pressure, injection rate, or selection of different
types of gas-lift valves.
It is preferable to know in advance if a design is going to work properly, rather
than install an incorrect design and find out later that it didn’t unload or
operate as desired.
It is not normally recommended to do this, due to the potential for leaks and
other problems, but if the dynamic simulator indicates that the well can not
work down due to improper mandrel spacing, it may be possible to insert and
additional unloading valve using a wireline-set pack-off valve.
-
Problem identification and diagnosis
Many gas-lift wells operate in an unstable manner at some time(s) in their life
cycle. This may be due to a change in the injection pressure or rate, the fluid
being produced, the inflow performance from the reservoir to the wellbore, or
a leak in the tubing, mandrels, or valves.
Typical problems include unstable operation due to a too large port size in an
operating valve or orifice, or multi pointing on two or more valves due to
periodical re-opening of an upper unloading valve, leaks in the tubing,
mandrels, or valves, or changes in the inflow performance of the well.
When an operating well is unstable, dynamic simulation can confirm or
diagnose the cause(s) of the instability. This is done by adjusting the
parameters used by the simulator until the predicted well performance, e.g.
tubing and casing pressure fluctuations, or production and injection pressure
profiles, match the observed or measured pressures and profiles. When a
match is achieved, the cause(s) of the instability can be determined.
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Gas-lift troubleshooting
When the causes of ineffective operation have been determined, dynamic
simulation can assist in troubleshooting to determine the best solutions to the
problem. It may be necessary to reset one or more of the unloading valves; it
may be necessary to change the port size in one or more of the valves or the
orifice; or it may be necessary to change the gas-lift injection rate or pressure.
Dynamic simulation can be used, much as it is used in design confirmation, to
check any proposed change in valve setting, or injection rate or pressure, to
verify if the change will accomplish the desired result in gas-lift operation. If
not, the proposed change(s) can be adjusted until they produce the desired
results.
-
Operational optimization
Gas-lift optimization is discussed in API RP 11V5 and 11V8. The objective is
to determine the rate of lift gas injection that will optimize the value of oil and
gas production with consideration for the cost of gas injection, water treating,
and fluid handling.
In an operating gas-lift field, there is rarely the right amount of gas to optimize
all of the wells; there is either too much or too little gas available.
Dynamic simulation can determine the range of gas-lift injection over which a
well can be operated and still continue to lift from bottom and remain at least
relatively stable. Too much gas will be wasteful and my cause upper gas-lift
valves to open due to an increase in the injection pressure at depth. Too little
gas may not provide enough lifting so the well can continue to operate from
the desired depth. This may lead to an unstable, multi-pointing operation.
As gas availability changes in a field, due to changes in compression capacity
or demand from wells in the field, the field control system must adjust the
injection rates so the total injection from the system is equal to the total supply
into the system. Otherwise, the pressure in the distribution system will go too
high or too low. Dynamic simulation can provide the range of injection rates
that can safely be used in each well. If the overall rate is too high, some gas
should be sold or re-cycled to avoid over injection. If the overall rate is too
low, it may be necessary to temporarily shut in some of the wells to avoid
under-injecting all of them.
API RP 19G11
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Dynamic Simulation of Gas-Lift Wells and Systems
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Special considerations
The above discussion focuses on gas-lift wells with mandrels, unloading
valves, and an operating valve or orifice. There are at least two other forms of
gas-lift which are coming into common use: injection through a single point,
and riser gas-lift.
Injection through a single point is possible when the injection pressure is high
enough to inject deep in the well without the need for unloading valves. This
can be stable if there is good correspondence between the injection rate at
the surface and the ability of the downhole injection valve or orifice to transmit
gas from the annulus to the tubing. However, if there is not a good match,
these wells can be unstable and need dynamic simulation to assist with
analysis and correction of the problem. Due to the flexibility that is lost when
there is only one injection point, dynamic simulation is required for design and
optimum operation of single point gas-lift systems. Chapter II-E provides more
information on these systems.
Riser gas-lift is sometimes used when long risers are required to bring
production from the sea floor to the surface. In some cases, the height of lift
in the riser can be as great as or even greater than the height of lift in the
wellbore. Gas-lift is needed to overcome the significant pressure drops
between the sea floor and the surface. There are often problems with
instability in the riser and dynamic simulation can assist with analysis and
correction of the problem. Chapter III-G provides more information on riser
gas-lift.
Appropriate dynamic simulation techniques and their implementation
-
What are the different simulation techniques?
Due to its historical development and the type of operational conditions, the
analysis of multiphase flow phenomena can be divided into two techniques:
• Steady state techniques
• Dynamic simulation or transient techniques
A detailed comparison of these techniques, highlighting pros and cons as well
as areas of application, is presented in Chapter 2-C.
Optimal design and operation of multiphase injection and production systems
rely on understanding multiphase flow behavior. To ensure technical,
operational, and HSE integrity during the field life cycle, dynamic simulation is
required.
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Dynamic Simulation of Gas-Lift Wells and Systems
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What techniques are appropriate for any given situation?
Dynamic simulation techniques can be used to design and/or optimize
multiphase production/injection systems for any given situation including
steady state and transient conditions. Steady state techniques should be used
only for steady state conditions. The application of steady state and/or
dynamic techniques is based on the level of complexity of the
production/injection system and the fluids to be modelled.
The major advantage of steady state techniques is that the models can be
constructed and sensitivities can be run quickly; therefore they are lower cost,
and may require less input. They may be reasonably accurate over a well
defined range of operating conditions. They are easy to use as design and
optimization tools. The common error is the attempt to use these techniques
to describe transient conditions.
Dynamic simulation techniques require experienced personnel and more time
for building models and analysing results. Therefore, this may be a more
costly technique and it may be more difficult to justify.
Both techniques are normally applied and the economic challenge is to
optimize the combined use of them without compromising the quality of the
design and the operational integrity of the system. Risk reduction and
potential catastrophic failures are more difficult to quantify if dynamic
simulation is not used.
When evaluating a number of gas-oil field development options using
parametric studies to identify the steady state operating scenarios with the
most limiting capacity constraints, the use of steady state techniques can be
useful to provide a 1st order approximation. But dynamic techniques are
required to more accurately calculate capacity requirements, and consider
time dependant operating practices, e.g. the effect on system design
diameters and slug catcher size, if a well is quickly opened to the desired
production rate versus slowly increasing the choke size in steps during a
controlled ramp-up. Furthermore, transient analysis is needed to evaluate the
effect of hydrate and or wax formation and establish operational guidelines to
avoid production chemistry problems during shut-in or start up operations.
Another application that efficiently combines the best of both techniques is to
initially build a transient model to analyse the start-up and shut-in operations
and more accurately define the steady state or unstable conditions, and
maximum wellhead pressures, temperatures. and profiles. Once the steady
state conditions have been confirmed and defined by transient simulation, and
wellhead P-T and P-T profiles have been validated, these profiles can be used
as correlations in steady state software models to make use of the quickness
of the steady state technique while obtaining more reliable results.
API RP 19G11
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Dynamic Simulation of Gas-Lift Wells and Systems
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What part of the gas-lift well/system needs to be simulated?
Typically, reservoir, well, surface, and process facilities are optimized as
individual components. The part of the total gas-lift system to be modelled
depends on the objectives of the study. To understand the multiphase flow
behavior of the total production/injection system, and evaluate the interaction
between the tubing, gas injection annulus, flowline, and riser, the total system
needs to be integrated. The advantage of integrated modelling is the ability to
dynamically link these components into one interactive, full-field production
system. Integrated systems can give more realistic results. There are different
levels of model integration and they should be applied following an increasing
order of complexity:
1st integration level that typically uses one software package:
Typically, E&P companies divide the design and optimization of the system in
different areas of expertise. Production technologists look at well design and
optimization, facilities engineers at pipeline-facilities design and optimization,
and operation engineers at production optimization and operating costs.
Therefore, it is not unusual to find a dynamic model of the well from the
reservoir to wellhead that is built by production technologists and a separate
flowline-riser model from the wellhead to separator that is built by facilities
engineers. These models are built to analyse different design and operational
issues and are optimized separately, but when the number of sensitivities
have been reduced to a minimum in both models, they need to be connected
to analyse the interaction between the system components. To do this, it is
necessary to use the same fluid table in both models constructed using with
the P-T extremes of the entire system, i.e. reservoir P-T and separator P-T.
In the case of gas-lift wells and systems, it is recommended to start the
modelling from the simpler case of the well only and upgrade the model to
include the well + flowline + riser based on the results. The order of
complexity of the gas-lift injection system is as follows:
1. Model gas-lift injection gas as a source considering its composition, PT, and rate at the desired injection point. In this type of model,
sensitivities can be run for different gas rates and different injection
points to obtain the optimum rate and position.
2. Model lift gas injection as a source at the wellhead and include the
annulus in the model. This will account for the cross heat transfer
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 101
effects of injecting a cold gas downhole in the annulus and producing a
hot fluid inside the tubing. This type of model will improve the
calculation of the temperature profile and the temperature at each
unloading valve location. It will also take into account other annular
flow effects such as condensation of liquids from the gas composition
since some liquids may be injected with the gas at the desired depth.
This type of model will also consider the interaction between the
production and the gas injection system components.
3. Model gas-lift injection gas as a source at the compressor output,
including the well annulus and the gas injection flowline from the
compressors to the annular wellhead. This type of model will take into
account the behavior of the lift gas in the injection line. The
compressor can also be included in the model.
2nd integration level which typically uses two software packages:
When the interaction between the near wellbore reservoir and the well plays a
dominant role in the description of the dynamic behavior of the complete
system, to properly model the multiphase flow behaviour, the well + flowline +
riser model may need to be integrated to the near-wellbore reservoir model.
Some of the cases where the dynamic wellbore/reservoir interactions may be
strong are:
–
Liquid loading
–
Dynamic water and gas coning
–
Formation heading and wellbore slugging
–
Bull heading and injection cases
–
Cross flow cases
–
Well kick-off and cleanup cases
–
Well testing cases
–
Shut-in/start-up cases
As explained in Chapter 2-B, a quasi-dynamic IPR option where the user can
specify pressure, temperature, water cut, k-h, skin and non-Darcy skin as
time series, can be used when matching interactive dynamic measurements.
A near-wellbore reservoir model can more accurately model the reservoir-well
interaction than the quasi-dynamic IPR.
Nevertheless, the benefits of the quasi-dynamic reservoir input are:
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
–
No software connectivity requirements since all is performed in one
software package
–
Faster runs
–
Value ranges of key variables will be defined faster
–
There will need to be fewer sensitivity runs
–
The analyst will be in a better position to:
•
define the value of using a near-wellbore model
•
define key variables and the value range
Page 102
Depending on the objectives of the study, some models will be more
appropriate than others.
3rd integration level where multiple software packages are used:
Multi-phase flow transient models can be integrated with geo-science
software, and risk simulation and decision analysis software packages, to
obtain a technical-operative information management system and improve
field development decisions. See Fig. VI-1 and VI-2.
Uncertainties across interfaces between surface-subsurface, well location,
producing scenarios, fluid-rock dynamic properties, and probabilistic analysis,
can be introduced and NPV and recovery estimates can be obtained.
Integrated multiphase-flow/geo-science/risk/decision-analysis modelling has
the potential to:
–
Optimize field productivity through the production life cycle
–
Improve reserves recovery
–
Enhance surveillance
–
Enhance troubleshooting
–
Improve decision making
–
Improve risk management
–
Improve work processes
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Fig. VI-1: Integrated Technical Operating Information Management System
PRODUCTION
CONTROL
MANAGEMENT
CENTER
DECISION
MAKING
ON-LINE
MONITORING
AND
PREDICTION
OF
CORROSION
DIAGNOSISPROGNOSIS
OFF-LINE
OPERATOR
TRAINING
SIMULATOR
ON-LINE
OPERATION
&
MAINTENANCE
OPTIMIZATION
PVT-FLUID
TRANPORT
AND
PROCESS
PROPERTIES
PROCESS
DESIGN
ADVANCED
PROCESS
CONTROL
WELL AND
ARTIFICIAL
LIFT SYSTEMS
DESIGN
SAFETY
STUDY
SIMULATOR
Fig VI-2: Integrated Simulators Under a Unified Software Environment
Page 103
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Page 104
The major drawback of integrated systems is the convergence problems
experienced during simulation runs due to different software packages and
explicit connective software.
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Dynamic Simulation of Gas-Lift Wells and Systems
Page 105
8. Information Provided by Dynamic Simulation
This chapter describes the information that can be provided by dynamic simulation of
gas-lift wells and systems.
Slugging flow:
Slug flow can be described as a multi-phase flow pattern in which slugs of liquid are
separated from each other by large bubbles of gas. See Fig. VII-1.
Fig. VII-1: Slug Flow
A liquid film with a varying thickness is present around the gas bubbles. Some gas
can be entrained in the liquid slug body in the form of much smaller bubbles. The
gas and liquid flow rates, with the corresponding pressures and temperatures, and
some other factors, can result in slugging in an oil well with or without gas-lift. How
flow patterns develop in a nearly vertical oil well with changes in pressures and
temperatures is shown in Fig. VII-2.
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Page 106
D
Pressure
Temperature
Depth
C
B
A
Pre s s ure
Te m pe rature
Figure VII-2: Changes in flow patterns in a vertical well with respect to pressures and
temperatures.
Point A in Fig. VII-2 is at the bottom of the hole where the pressures are higher than
the bubble point of the fluid at in-situ temperature. There is a reduction in pressure up
to point B because of the frictional and hydrostatic losses. This is where the fluid is at
the bubble point pressure at the local flowing temperature. Any further reduction in
pressure results in gas liberation leading to the bubble flow regime. Reduction in
pressures continues as the fluid approaches point C. This increases gas liberation
and velocities. The bubble volumes become larger with an increased tendency to
coalesce. The flow pattern changes and becomes hydrodynamic slug flow. Large gas
bubbles are separated from each other by liquid slugs.
Hydrodynamic slugging is generated by slip between the liquid and gas phases.
To determine if slug flow will occur in a pipe segment, the flow pattern map for a
specific deviation needs to be inspected. This approach is not accurate because flow
regime transitions cannot be reduced to two defining parameters, but it is a good
example for explaining hydrodynamic slugging.
Fig. VII-3 is an example flow pattern map for vertical upward flow. This map is not
based on realistic calculations. It is an example to show what a flow pattern map
looks like.
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Page 107
Bubble flow
Annular flow
Liquid Froude
number
Froth flow
Slug/churn flow
(Intermittent flow)
Gas Froude number
Fig. VII-3: Flow pattern map for vertical upward flow.
Hydrodynamic slugging does not represent a major instability if the well is producing
at sufficiently high rates where the system is dominated by friction. See Fig. VII-4 for
cases where the production rates are low, flow is unstable with excessive liquid fall
back, and major slugging occurs. This may create operational problems. In an
extreme case, the well will cease to flow. Such slugging can also be observed in
over-sized risers.
Flowing bottom hole pressure
IPC, no gas-lift
IPC, with gas-lift
IPR
Gross liquid rate
Fig. VII-4: Well production rate indicated by the black dot is in the gravity-dominated area,
which is on the left-hand side of the minimum of the intake pressure curve (IPC).
Producing wells in an unstable regime of major slugging are difficult to operate and
reduce equipment life. This regime represents a state of instability for the phase
fractions at the well outlet and pressures across the system. The retained liquid,
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Page 108
which falls back, increases the hydrostatic pressure in the well and results in a
reduction in production. With the increased pressures at the bottom of the hole, at
some stage the well is able to push the liquid out. While discharging the slug,
pressures in the well start dropping again which leads to an increase in the
production from the reservoir. Depending on the size of the slug, and production from
the other wells in the field, and even the separation efficiency in the separator train,
may be adversely affected due to the temporary excessive liquid rate. Gas-lifting is
one of the preferred ways to avoid slugging in wells and risers if further beaning up to
increase the choke size is not an option. The aim is to change the flow pattern from
intermittent to annular mist, which ensures stable pressures, flow rates, and phase
fractions at the discharge point.
The curve of “IPC, with gas-lift” in Fig. VII-4 illustrates the effect of gas-lift on the
slugging behavior. The point of instability, which is at the minimum of the intake
pressure curve, is shifted towards smaller rates. This offers a longer service life for
the well. Fig. VII-4 can be generated by using any steady state well performance or
multiphase flow simulator. A Dynamic Simulator is required to predict the system’s
behavior and pressure drop after the slugging starts. Transient analysis is required to
estimate “what happens next” once the intersection of the IPR and the IPC curves
occurs in the instable area. This analysis will provide valuable information about how
serious the slugging will be, and whether or not gas-lift will be required to overcome
the instability.
Hydrodynamic slugging conditions are more rigorously predicted by dynamic
simulation. These mathematical models are based on physical mechanisms which
determine the transition between the different flow regimes. In the dynamic simulator,
P-T and liquid hold-up are interrelated. Phase transfer is a function of P and T. The
simulator interface mass transfer model takes into account condensation,
evaporation, and retrograde condensation.
Well trajectory can induce another form of slugging behavior in wells. These are
called terrain slugs and steady state tools do not predict this behavior. In an
undulating trajectory, the heavy liquid phase, e.g. water, may have a tendency
accumulate in the sumps (See Fig. VII-5) under steady state flow conditions.
Increasing liquid level with time in the pipeline dip creates a backpressure upstream
of the accumulation resulting in a reduction in production at these sections. When the
pressure at the upstream end of the liquid body is high enough, the liquid can move
and enter sections which are highly inclined or vertical. The elevated flowing bottomhole pressures at this stage will negatively affect the production until the well starts
discharging the liquid slug. Terrain slugging results in pressure fluctuations, changes
in production rate, and variations in the phase fractions at the well outlet. It is not
desirable. Using a transient multi-phase flow simulator provides an opportunity to
realize if a well with a sophisticated trajectory will act as a slug generator. Or it may
be possible to tune the operational parameters to terminate the slugging behavior.
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Main flow direction
Liquid falling back
Fig. VII-5: A well trajectory which can trigger terrain slugs.
Horizontal and inclined wells can generate terrain induced slugging; and risers
can as well. See Fig. VII-6. Risers are an integral part of offshore and subsea
production systems, and well completion and workover operations. Steady state
techniques do not predict terrain induced slugging. Stable conditions defined by
using steady state analysis may be incorrect in this kind of production systems
where the well/system may be unstable. Dynamic simulation is required to
properly define slugging conditions and stable flow.
A. Slug formation
C. Gas penetration
B.Slug production
D. Gas blow-down
Fig. VII-6: Riser Induced Slugging
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Dynamic simulation can define where slugging originates and what is causing it.
Dynamic simulation can also establish the size and frequency of the gas bubble
and associated slugging severity. See Fig. VII-1.
Tracking development of the individual slugs along the well and flowline
trajectories is necessary to estimate the volume of the liquid surges that flow out
of the system.
The main potential problems that may inhibit stable multiphase flow are:
• Terrain
• Inclination/elevation
• Rate changes
• Condensate–liquid content in gas
• Shut-in/start-up
• Risers
Other problems can occur in gas-lift wells:
• Unloading gas-lift valve leaks
• Incorrect mandrel spacing and unloading valve design
• Annular heading
-
Downhole operating gas-lift valve and surface lift gas control valve/orifice
interaction
-
Annular liquid condensation
• Density wave instability26.
• Non-constant fluid composition in tubing above gas injection point, when
injecting lift gas of different composition than the produced gas
• Compressor pressure fluctuations
• Interference between gas-lift wells in the system
Water effects on corrosion and hydrates:
-
Understand the effects of accumulated water in lines and gas-lift valves.
Hilly terrain, deviation, and changes in flow direction, can induce water hold-up
in wells and flowlines. See Fig. VII-7. In deviated and horizontal wells and
flowlines, local water cuts can exceed 20% to 50% despite low inflow rates from
production zones and/or low production rates measured at surface, even with
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Dynamic Simulation of Gas-Lift Wells and Systems
Page 111
water cut measurements of 1% or less. The amount of water going in and out
the system does not represent the amount accumulated in low points of the
system.
Fig. VII-7: Water accumulation in horizontal wells and flowlines
Liquid Content
The water accumulation in the dips can exist for hours or days or can be
permanent. Established local water cut values will change at different
production scenarios, i.e. wellhead pressures, gas velocities, and gas-lift
injection rates. See Fig. VII-8.
Initial
amount
Final
amount
Gas Production Rate
Fig. VII-8: Well and flowline liquid content as a function of gas production rate
Dynamic simulation describes the multiphase flow behavior and provides the
key flow characteristics to define water accumulation at any point in the system,
and the water accumulation effects on both the hydrodynamic and terrain
induced slugging conditions, liquid loading conditions, and related internal
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Dynamic Simulation of Gas-Lift Wells and Systems
Page 112
corrosion susceptibility, as a function of time and for changing operating
scenarios.
The dynamic simulator provides the resulting trends and profiles for the key
variables:

Pressure

Temperature

Water, oil, gas, water vapor, water droplets, oil droplets and gas bubble
velocities, superficial velocities, and fractions

Water film fraction and velocity where sweet corrosion exists only if a water
film is wetting the pipeline

Flow regime and separated/dispersed flow

Water wetting. Normally it is assumed that water is the continuous phase
when the water cut is larger than 30%. The inversion point is usually
somewhere between 30% and 50%.

Water condensation rate

pH

Partial pressure of CO2

Shear stress between water film and pipe wall

Critical velocities for water loading and erosion, since erosional areas are
more susceptible to corrosion
Figure VII-9 is an example of a profile plot showing the pressure, temperature,
and water condensation rate changes along the system profile at a point in time.
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Dynamic Simulation of Gas-Lift Wells and Systems
0.04
2
Pressure
Condensation rate (g/m s)
Pressure (bar), temperature (°C)
80
Condensation rate
60
40
0.02
Temperature
20
0
0.00
0
10
20
30
40
50
60
Distance (km)
Fig. VII-9: P, T and water condensation rate values along the flowline profile
In gas-lift systems, the amount of injected gas can be simulated as a source
defined by its rate, pressure, density, viscosity, corrosive content, and CO2. The
location of the source can be selected depending on the objectives of the study,
at the:

Downhole injection point (operating GLV)

Wellhead

Compressor output
Multiphase flow resulting trends and profiles (as listed above, including water
accumulation and corrosion ambient conditions) can be obtained and analysed
for the gas-lift injection system, in any of the three cases listed above. Cases 2
and 3 will improve the temperature calculation in the well due to consideration of
the counter current heat transfer effects generated by the cooler gas-lift annular
flow. Cases 2 and 3 will also take into account any interaction between annulus
and production tubing, i.e. slugging generated in the annulus and being
transferred to the tubing. Case 3 will further improve the gas-lift optimization
analysis by providing the amount of condensate generated in the annulusinjection flow line of the gas-lift system and the location and amounts
accumulated and/or being injected into the well. The virtual model in the
dynamic simulator can be as complex as necessary.
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Dynamic Simulation of Gas-Lift Wells and Systems
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Understand the effects of water-induced corrosion.
Most downhole tubular corrosion is associated with the exposure of downhole
steel to low-pH environments, encouraged by the combination of groundwater
with a variety of acid-forming elements. CO2 dissolves in water to form a weak
acid and therefore the solution has a low pH value. A low solution pH
accelerates corrosion. The corrosion will take the form of uniform surface or
weight loss and localized pitting corrosion. The primary factors that affect CO 2
corrosion are the partial pressure of CO2, temperature, and chloride content.
An important aspect of including corrosion models in the dynamic simulator is
the possibility of identifying the areas of the well and flowline with the highest
risk for corrosion problems and the corrosion rates. The location with the
highest corrosion rate can be determined by the temperature and pressure
variation along the pipeline or by flow effects like liquid accumulation, flow
velocity variations, and changes in flow regimes.
It is important to select a dynamic simulator that can break the multiphase flow
at any time and system location into the following components: gas, vapor,
oil/condensate droplets, water droplets, oil/condensate film, and water film. It is
important to know if water or oil wets the steel surface since corrosion takes
place only when water is present at the surface. If water is present as vapor or
droplets, the contact with steel surface is not as relevant as when water is
present as a film. The duration of water as the film contact is also important
because this contact can be transitory and not long enough to be relevant.
The selection of the best corrosion prediction model could generate a debate
that is beyond the content of this chapter. Different oil companies and research
institutions have developed a large number of prediction models for CO2
corrosion of carbon steel in oil and gas wells and pipelines. Many of these
models take flow-related parameters like liquid velocity or water, oil, and gas
production rates into account. However, most of the models are point models,
i.e. they can only be used to predict the corrosion rate at a given location in a
well or pipeline where the temperature, pressure, water chemistry, and flow
conditions are specified. The models either take liquid velocity as input or
assess the flow effect on corrosion by a simplified fluid flow calculation at a
point. To perform a corrosion evaluation for a specific well or flowline, it is
necessary to perform a fluid flow simulation with a dynamic simulator and use
the results from this simulation as input for running a corrosion model at
different points in the well or flowline. It is advantageous to combine fluid flow
models and corrosion models into a single package. This has been done using
the basic corrosion models:
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems

de Waard Model, 1993 and 1995 versions

NORSOK M-506 model

Top of Line Corrosion Model
Page 115
The de Waard model is a widely used CO2 corrosion model. The NORSOK
model is a more recent model. The Top of Line corrosion model is based on
laboratory studies performed in 1990 with emphasis on the effects of variation of
water condensation rate, temperature, and CO2 partial pressure on corrosion at
the top of wet gas pipelines, whereas other models describe corrosion at the
bottom of the line. Fig. VII-10 shows a case comparing de Waard and NORSOK
corrosion rate estimates. The NORSOK model estimated smaller corrosion
rates than the de Waard model for formation water at high temperature with
bicarbonate present. The NORSOK model takes account for protective
corrosion films. With no bicarbonate present, the two models predicted similar
corrosion rates. Fig. VII-11 shows Top of Line corrosion rate analysis results.
10
Corrosion rate / (mm/y)
de Waard model
Norsok model
5
0
0
5000
Position / m
10000
Fig. VII-10: de Waard and NORSOK Corrosion Rates, showing peaks in corrosion rate in
downhill slopes with higher flow velocities
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0.06
Fe
2+
sat.
150
0.04
2+
100
saturation (ppm)
200
TOL corrosion rate
supersaturation
Fe
Corrosion rate (mm/y)
0.08
0.02
50
0.00
0
0
10
20
30
40
50
60
Distance (km)
Fig. VII-11: Top of Line Corrosion Rate (TOL)
The usual dynamic simulator outputs are:
–
Pressure and temperature profile
–
Liquid velocity or wall shear stress
–
Flow regime and separated/dispersed flow
–
Water wetting
–
Water condensation rate
The usual corrosion specific inputs are:
–
CO2 mole fraction in the gas
–
CO2 partial pressure which is the total gas pressure times CO2 mole
fraction
–
Water chemistry: bicarbonate content and ionic strength
–
Glycol concentration and inhibitor efficiency
Calculation of the pH value in the water is based on:
–
CO2 partial pressure, temperature and water chemistry
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The dynamic simulator offers three options for pH calculation:
–
Condensed water without corrosion products for low pH of +/- 4
–
Condensed water saturated with iron carbonate for higher pH
–
Formation water with specified bicarbonate content
Water chemistry in condensing water may be very different from the bulk water
phase:
–
Salts from formation water are not present in the Top of Line model
–
Condensing water will have low pH and high corrosivity
–
Corrosion products accumulate rapidly in the condensing water
–
pH increases until the water is saturated with iron carbonate
–
Corrosion is reduced by formation of protective iron carbonate films
Typical formation water values as a reference are:
–
60 - 600 ppm bicarbonate (1 - 10 mM)
–
0.5 - 2 M ionic strength
–
pH often in the range of 5 - 5.5
Studies in the literature show that for small amounts of H2S, CO2 is the
dominant corrosive species. However, for a ratio of pCO2/pH2S > 200-500,
which represents small amounts of H2S in a CO2 dominant system, H2S can
affect the corrosion rate mainly by formation of more or less protective films
(FeS). For pCO2/pH2S < 200-500, H2S usually dominates the corrosion rate and
there is sour or cracking corrosion. Sour or cracking corrosion is a very different
phenomenon where H+ penetrates the steel and makes it more brittle so it
finally cracks. The corrosion models are not made for H2S corrosion:
–
Not valid for CO2 to H2S ratios below 20
–
Should not be used when the H2S partial pressure is above 0.1 bar (1.45
psi)
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In summary:

The modelling and understanding of multiphase fluid flow and CO2 corrosion
is important for economic and safe design and operation of wells and
flowline systems, and corrosion mitigation plans. Depending on operating
conditions, the corrosion mitigation plan may need to change.

Operating and related multiphase flow conditions may affect corrosion of
well and flowline steel in different ways. It is important to know if water or oil
wets the steel surface since corrosion takes place only when water is
present at the surface. Water wetting depend on the fluids, the flow
conditions, and the water cut.

The multiphase flow characteristics may also affect corrosion if corrosive
species are involved. Higher flow velocities give more turbulence, better
mixing, and thus larger transport. The flow also affects the structure and
strength of protective corrosion product layers, which reduce the transport of
corrosive species towards the steel surface.

Within each flow regime, water and oil may be separated or dispersed. If
they are separated, both water and oil wet the wall, but at different parts of
the wall. Water is heavier and wets the bottom of the pipe but this is not
valid in vertical flow.

Dynamic simulators are unique tools which can provide most of the
information required to develop risk-based corrosion susceptibility profiles.

The whole production system can be modelled including the well annulus
and gas-lift injection lines. Trend and profile results of the key variables are
obtained at any location and time.

An important aspect of including corrosion models in a dynamic simulator is
the possibility of identifying the areas of the well and flowline with the
highest risk for corrosion problems. The location with the highest corrosion
rate can be determined by the temperature and pressure variation along the
pipeline or by flow effects such as liquid accumulation, flow velocity
variations, and changes in flow regime.

The dynamic simulator provides pressure, temperature, shear stress, and
water wetting predictions to calculate CO2 partial pressure, pH, and
corrosion rate profiles along the pipeline. The basic corrosion models are
included in the simulators, but the implemented models can be extended
with other CO2 corrosion models.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems

Page 119
The dynamic simulator can be used to estimate the amount of inhibitor
required to eliminate or minimize corrosive conditions, and to predict
inhibitor distribution and estimate the right type and amount to be used
during transient, steady state, and changing operating conditions.
- Understand the effects of hydrates in lines and gas-lift valves
Gas hydrates are crystalline compounds formed by water and natural gas
molecules at high pressures and low temperatures below approximately 35°C
(95 oF). They are solid ice-like crystals consisting of geometric lattices of water
molecules containing cavities occupied by light hydrocarbons (methane, ethane,
propane) or
other light gaseous compounds (nitrogen, carbon dioxide,
hydrogen sulfide). Unlike ice, they can form at temperatures higher than 0°C
(32 oF). They can take many forms from slushy, sticky lumps to a fine powder.
Hydrates can form in gas, gas-condensate, and black-oil systems and can block
any flowline. Hydrate blockages can form very rapidly when suitable P-T
conditions and compositions are present. Severe P-T changes across chokes
and/or gas-lift injection valves can create hydrates. Transient operations such
as start-up and shut down are very susceptible to hydrate blockages because
the production system is likely to fall into the hydrate region. It is important to
model transient operations for deep wet and dry subsea wellheads and subsea
tiebacks in deep waters, shut-in and restarting from shut-in conditions can
create significant flow assurance problems. Hot fluids from the wellbore will
come in contact with a cold flowline and can form hydrates during restart
operations. Subsea wellhead conditions at the mudline are often within the
hydrate formation region. As the water depth increases, boundary temperatures
decrease and the potential for higher shut-in pressures increases due to
additional liquid head, as well as the probability of hydrate formation.
Clearing hydrate blockages in subsea equipment or flowlines poses safety
concerns and can be time consuming and costly.
Hydrates are the most prevalent flow assurance problem in offshore oil and gas
operations, an order of magnitude worse than waxes.
There are different hydrate control design and remediation options such as
controlling P-T, removing water, and shifting thermodynamic equilibrium with
inhibitors:
•
Insulation for passive thermal control
–
Used for tie-ins and short to medium length pipelines
–
Not normally used for long gas-condensate lines.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
•
•
Page 120
Bundles for active thermal control
–
Complex bundles used for deep offshore
–
Generally used for risers, tie-ins, and short to medium length pipelines.
Active Heating
–
Electrical
– Hot fluid circulation.
•
Depressurization: provide capacity for depressurization and displacement
•
Inhibition
–
Typical for gas-condensate systems
–
Used for oil systems at critical points, e.g. well-heads and wellbore, and
during critical operational phases shut-in, cool-down, start-up.
The most common inhibitors are:
• Thermodynamic inhibitors, i.e. inhibitors that move the melting curve of the
hydrates towards lower temperatures:
–
Alcohols (MeOH)
–
Glycols (Mono Ethylene Glycol – MEG)
• Low Dosage Hydrate Inhibitors (LDHI) modify crystal growth or crystal
structure to avoid blockage.
Water salinity tends to reduce hydrate temperature. To be conservative, the
hydrate inhibitor requirement estimates do not account for the inhibitor effect of
produced water salinity.
A significant effort is required in the design phase to develop a production
system with an acceptable level of risk. At the beginning of the flow assurance
design process, basic design and operating philosophies which cover
hydraulics, deliverability, hydrates and waxes should be clearly set.
To determine the P-T conditions under which hydrates can form, use
thermodynamic models to predict hydrate behaviour by calculating the hydrate
equilibrium curve or hydrate dissociation curve. This is a prediction of
temperature at a given pressure above which hydrates will not form.
The PR78 SRK-P EOS model was used to obtain the hydrates curve for the
fluid shown in Fig. VII-12.
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Dynamic Simulation of Gas-Lift Wells and Systems
Hydrates PT Curve - EOS = PR 78 Peneloux - Gorgon GB5
600
500
Pressure - bara
400
300
200
100
0
-50
-40
-30
-20
-10
0
10
20
30
40
Temperature - deg C
Fig VII-12: Hydrates P-T curve – EOS: PR78 Peneloux
The hydrate curve represents the thermodynamic boundary between hydrate
stability and dissociation. A hydrate formation curve represents the pressure
temperature relationship at which hydrates may form, whereas a hydrate
dissociation curve represents the points where a hydrate crystal, once formed,
will dissociate. The dissociation curve is typically 2 to 3 ºC (3.6 to 5.4 oF) above
the formation curve. The region between these two curves is the zone where
the hydrates are unstable. The hydrate dissociation curve, also termed the
“hydrate curve,” therefore presents a conservative scenario and is used in
studies for hydrate assessment calculations.
-
Understand when, where, and under which conditions hydrates may be
formed.
The cost of thermodynamically inhibiting production systems under steady state
and/or transient operations can be prohibitive. It may not be possible to avoid
the hydrate formation region in all probable operating scenarios. It is therefore
important to estimate the risk of forming a hydrate plug during a restart
operation or in a new field design.
Modelling is an effective way to reduce uncertainty by screening various
options. Dynamic simulation offers a methodology to estimate when, where, and
under which conditions hydrates may be formed in a production system, during
transient and steady state conditions, based on the difference between a
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Dynamic Simulation of Gas-Lift Wells and Systems
hydrate temperature (Thyd) and fluid temperature (Tf) at section pressure. The
model calculates the output variable:
DTHYD = Thyd – Tf
if DTHYD>0 then the section is within the hydrate region.
Plots of the difference between the hydrate formation temperature and the fluid
temperature (DTHYD) at any time are termed subcooling profiles. Positive
temperature numbers in these profile curves indicate the potential for hydrates
formation in these locations. Fig. VII-13 shows an example of hydrate margins
in a riser during well kick-off.
Profile Data (deg. C) – Riser Length (metres) – Time (Minutes)
Black - Time 0 (Static Conditions)
Profile data
Red: Time 1; Green: Time 2; Blue: Time 3; Purple: Time 5; Yellow: Time 10
GB5-A_Mono_CaseA_50MM-0wc_rst: DIFFERENCE BETWEEN HY DRATE AND SECTION TEM.,RISER-BRANCH [C], Time:
GB5-A_Mono_CaseA_50MM-0wc_rst: DIFFERENCE BETWEEN HY DRATE AND SECTION TEM.,RISER-BRANCH [C], Time:
0
1
GB5-A_Mono_CaseA_50MM-0wc_rst: DIFFERENCE BETWEEN HY DRATE AND SECTION TEM.,RISER-BRANCH [C], Time:
GB5-A_Mono_CaseA_50MM-0wc_rst: DIFFERENCE BETWEEN HY DRATE AND SECTION TEM.,RISER-BRANCH [C], Time:
2
3
GB5-A_Mono_CaseA_50MM-0wc_rst: DIFFERENCE BETWEEN HY DRATE AND SECTION TEM.,RISER-BRANCH [C], Time: 5
GB5-A_Mono_CaseA_50MM-0wc_rst: DIFFERENCE BETWEEN HY DRATE AND SECTION TEM.,RISER-BRANCH [C], Time: 10
0
-10
-20
-30
C
-40
-50
-60
-70
-80
-90
-100
0
50
100
150
Length [m]
200
250
300
Fig VII-13: - Hydrate Margin in Riser vs Time during well kick-off – 60 MMscfd, 15 WGR
Dynamic simulation offers application of different hydrate control methodologies
in the virtual model such as insulation, active heating, and inhibition, and
selecting the most effective one for steady state and transient operating
conditions.
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Dynamic Simulation of Gas-Lift Wells and Systems
Fig. VII-14 shows the influence on the amount of MeOH used in the hydrate
dissociation curves and Fig. VII-15 shows the overlap of the worst P-T trends in
the riser profile, during well clean-up (blue), shut-in (purple), end of shut-in
(doted purple), and kick-off (green), indicating the amount of MeOH required to
avoid falling in the hydrates region.
Hydrate Curves with MeOH Inhibition
(kg MeOH / kg Aqueous)
0%wt
1%wt
3500
5%wt
10%wt
15%wt
20%wt
25%wt
30%wt
35%wt
40%wt
45%wt
50%wt
60%wt
Hydrate
Formation
Region
3000
Pressure (psia)
2500
2000
1500
1000
500
0
-5
0
5
10
15
20
25
30
Temperature (C°)
Fig. VII-14: Hydrate Dissociation Curves with MeOH inhibition (0% to 60%)
35
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Dynamic Simulation of Gas-Lift Wells and Systems
Hydrate Curves with MeOH Inhibition - (kg MeOH / kg Aqueous)
0%wt
40%wt
2370min-RISER-kick-off
3500
Hydrate
Formation
Region
3000
10%wt
45%wt
5min-RISER-Clean-up
20%wt
50%wt
2314-RISER-SI-end
30%wt
930min-RISER-Shut-in
Pressure (psia)
2500
2000
1500
1000
500
0
-5
0
5
10
15
20
25
30
35
40
45
Temperature (C°)
Fig. VII-15: Hydrate Inhibition Curves with the overlaps of the worst case P-T trends from
Riser Profile Plots
In addition to the flowline, the well should be included in any hydrate formation study.
Inhibitor injection only protects components in the production system downstream of
the injection point; therefore the location of the injection point is an important
decision. The most common locations are downhole in the well immediately above
the SCSSV, at the tree between master and wing valves, and on the manifold.
Inhibitors can provide protection against hydrate formation if sufficient quantities are
injected, but under injecting may accelerate the kinetics of hydrate formation.
Therefore, it is typical to overdose to be safe. Significant savings can be obtained
using dynamic simulation to estimate the right amount of inhibitor and the times when
inhibitor injection is no longer required. The water production rate needs to be
known. The main uncertainty is the amount of the dissolved salts in the produced
water and their effect on hydrate formation. Salinity in produced water tends to
reduce hydrate temperature, but to be conservative normally the calculated hydrate
inhibitor requirements do not account for the inhibitor effect of produced water
salinity. However, dynamic simulation can include the affects of salinity.
Dynamic simulation allows the tracking of the amount of inhibitor in the well/pipeline
to ensure enough inhibitor is available. Inhibitor can be tracked in both the water and
gas phases. Dynamic simulation gives:
– Inhibitor (MeOH or MEG) concentration along the well / flowline profile
– Time to reach a desired inhibitor concentration
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Page 125
Dynamic simulation allows development of operating guidelines that ensure proper
injection rates and distribution of inhibitors for all operating modes.
An example of MeOH injection tracking is given in the Fig. VII-16. Upon restart, cold
gas enters the flowline due to Joule Thompson cooling on gas expansion. This
cooling is inhibited by injecting MeOH upstream of the wellhead prior to start up and
continuously for the first 3 hours. Additionally, as the cold liquid residing in the
flowline is pressured, it heads towards the hydrate region. This takes some time as
restart is slow, and is worse at high water cuts
Fig. VII-16: Tracking MeOH injection and Hydrates Potential
Dynamic simulation can answer the following questions:
• What is the predicted hydrate dissociation temperature profile? How far are the
conditions from hydrate formation? Where? When?
• When will the temperature fall into the hydrates region?
• How deep below the wellhead will the well experience hydrates problems?
When?
• What’s the best solution for the well flow assurance problems?
–
–
Pressure control
Temperature control
API RP 19G11
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–
–
–
–
–
Dynamic Simulation of Gas-Lift Wells and Systems
Page 126
Remove supply of water
Perform a hot or cold re-start
Preheating the flowline
Flowline depressurization
Insulation
Inhibitor injection? Where? When?
Hydrate remediation schemes can be divided in two:

Reducing pressure in the system to the point where ambient temperatures allow
melting
Active heating

These schemes should be dynamically modelled prior to execution. Dynamic
simulation is a tool to evaluate and design successful hydrate remediation operations.
For instance, the wellbore thermal-hydraulic transient simulation can be useful to
assess the feasibility of injecting hot oil in the tubing-casing annulus for melting
hydrate plugs formed inside the tubing in dry-tree gas-lift wells38,39,47. Dynamic
simulation can provide the required:
 Bleed-off tuning pressure
 Amount of inhibitor
 Time for inhibitor distribution
 Heating temperature and oil injection rate
 Operational guidelines to restart well production
Due to the potentially severe economic impact of forming hydrates plugs, to better
estimate the time required for hydrate plug formation, and to better understand
hydrate kinetics, new hydrate growth, deposition, sloughing, and jamming models are
being developed. E&P companies, universities, and research centers have been
developing models with extensive testing using flow loop data and field data. This is
still considered experimental but some field application results that demonstrate
hydrate rate formation and hydrate mass in pipe are encouraging51.
Production chemistry:
-
Understand the effects of wax and/or paraffin formation and the impact of
each of these on well performance and stability.
Production chemistry issues associated with wells and production/injection
systems are relevant to cost-effective field developments and operating
integrity. Plugging due to wax, paraffin, asphaltene, scale, and hydrates
reduces the ability of the well-flowline production/injection system to deliver the
fluids. In addition, deep water operations amplify the environmental and safety
concerns. The increased risk associated with long sub-sea tiebacks, dry-tree
risers, and extended export pipelines in cold ambient water should be
considered by operators when planning their development scenarios. Under
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Page 127
these severe conditions, it is important to understand multiphase fluid properties
and the design options to prevent or mitigate flow assurance challenges.
Dynamic simulation is a tool to provide understanding of flow behavior and the
resulting internal ambient conditions at any point of the production system.
Waxes, wax deposition, and wax gelation are three potentially important issues
in crude oil and gas condensate systems.
Waxes are high molecular weight, straight, long-chain hydrocarbons (C17 to
C75) that precipitate from the produced fluid. They are crystalline and are
usually characterized by the wax appearance temperature (WAT) and pour
point where the first wax crystals start to precipitate out of solution.
The deposition of n-paraffin waxes will commonly occur along the well/flowline
walls when the temperature of produced fluids falls below the WAT or cloud
point. Deposition rates can be attributed to many factors including paraffin
content, fluid viscosity, flow rates, gas/oil ratio, and the heat transfer coefficient
or U-value.
The problems caused by waxes are twofold:

Wax produces choking or total blockage through increased apparent inner
wall roughness and decreased diameter effects.

Increased apparent fluid viscosity; viscosity can reach the point where the
wax forms a gel and excessive pressure may be required to generate flow.
Wax gelation is less common in steady-state than wax deposition, but it can
have greater impact if, during transient operations like shutdowns and start ups,
fluid temperatures cool below WAT and pour point, allowing the formation of a
solid wax column. This condition can completely block the flowline. During
restart operations there may not be sufficient pressure available to "break" the
gel and allow the well to flow.
When dealing with high wax content crudes, strategies for wax prevention must
be developed.
For waxy crude production systems, the criterion used for thermo-hydraulic
studies is the prediction of the fluid temperature along the system from the
perforations to the facilities needs to be above the WAT. Dynamic simulation
can accurately calculate, if input data and fluid characterization from lab studies
have been properly done, where and when fluid temperatures fall below WAT
and the wax deposition rate as a function of time and space. See Fig. VII-17.
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Fig. VII-17: Wax Deposition Rate Along the Pipe vs. Time
Dynamic simulation can also model realistic pig runs and the results of the run.
The pig-plug model tracks the masses on each side of the pig, calculates the
leakage through the pig, and modifies the forces acting on the control volumes
surrounding it. The pig velocity is set based on the local volumetric flux, taking
into account any pig leakage rate. The influence of the pig on the flow
conditions are through pig and related friction forces, the gravity forces due to
the mass of the pig, and any leakage of the pig.
Dynamic simulation predicts the need of:

Pigging
–
Efficiency of wax removal after pigging
–
Pressure requirements for wax scraping
–
Frequency required for wax removal operations

Thermal insulation required to minimize or eliminate wax formation

Non-Newtonian behavior of viscosity due to wax precipitation into oil phase

Self-regulation of wax deposition due to release of latent heat

Active heating required to minimize or eliminate wax formation

Chemical injection. Diluents can reduce viscosity and cause a depression in
the WAT resulting in a reduction of frictional losses and a decrease in
thermal insulation requirements.

Gas-lift injection as diluent to reduce cloud point and cause WAT
suppression

Investigation of increase in 1st separation pressure results
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Page 129
Dynamic simulation can:


Perform a material balance of wax components
–
Wax in dissolved oil
–
Precipitated wax suspended in oil
–
Precipitated wax deposited on walls.
Describe the dynamics of wax formation/dissipation
–
Wax precipitation
–
Molecular diffusion and shear stripping
–
Wax melting.
Wax deposition rate analysis is done using one model, or running sensitivities to
the following multiphase flow wax deposition models:
1.
Rygg, Rydahl & Rønningsen (RRR)
The RRR model considers a laminar velocity sub-layer in turbulent flow.
Wax deposition is estimated from the diffusion of wax from the bulk flow
towards the wall as a result of temperature gradients and shear dispersion
effects. Varying inner pipe wall friction due to wax deposition is also
included. It may under-predict wax deposition rate for single phase oil
cases.
2. HEAT ANOLOGY, University of Tulsa
The heat analogy model was introduced to extend the wax deposition
model to handle laminar flow. Deposition rate reduction due to shear
stripping and rate enhancement due to entrapment of oil and other
mechanisms not accounted for by the classical Fick's mass diffusion
theory, were incorporated through the use of dimensionless variables
and empirical constants derived from the wax deposition data. The
kinetic model, although semi-empirical, predicts wax thickness with an
acceptable accuracy, especially at high oil superficial velocity, and provides
an insight for future model development.
3. MATZAIN
The Matzain model considers a concentration boundary layer as for laminar
flow. It has a diffusion enhancement effect which is not directly related to
the shear stripping part of the Matzain/Tulsa model where shear stripping
effect itself may be tuned.
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A typical wax analysis should include:
•
Fluids and wax characterisation measured in the laboratory
–
Compositional analyses (HTGC)
–
WAT
–
Pour point
–
Wax content
–
Viscosity
–
Deposition rate or diffusion coefficient
–
Deposit analysis including yield strength, trapped oil
–
Gel strength
–
Impact of inhibitors
–
Impact of diluents
•
Thermal hydraulics analysis, e.g. insulation, cooldown
•
Wax deposition rate analysis
•
Pig-ability analysis
•
Gel restart-ability analysis
A wax thermo-hydraulic study strategy should include the following steps:
•
Define/understand the characteristics of fluids, wax, and gel
•
Keep the fluid hot by insulating or direct heating of the well-pipeline
•
Alter wax characteristics by blending with less waxy fluids or use wax or gel
inhibitors
•
Quantify the extent of wax buildup to establish frequency of wax removal
operation
•
Remove wax frequently by pigging, melting, or removal by chemicals
•
Quantify cool down to gel formation by displacing the fluids to avoid
plugging.
Dynamic modelling can also provide indicators for profiling well-pipeline
temperatures and wax buildup. This tool can assist the operator in making
economic decisions and exploring multiple design options. Current modelling
technology includes real-time, online well-pipeline monitoring and advisory
systems that help manage a series of flow assurance issues including pigging
operations and any “what-if” scenarios.
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Gas-lift valve performance:
-
Understand information and models for dynamic gas-lift valve and
orifice performance; how and when to use them.
Gas-lift valve performance relates to the valve’s flow performance. Many
other criteria, such as reliability, robustness, corrosion resistance, and ease
of maintenance are also performance factors but in this section, the subject
will be focused on flow performance.
The purpose of a gas-lift valve is to open at a predefined pressure and allow
gas to flow from the annulus to the production string. The valve should then
close at a predefined pressure, shutting off flow from the annulus into the
tubing. The pressures at which the valve opens and closes are determined
by performing a gas-lift design. Each well is different and therefore each
valve will have a different opening and closing pressure.
The flow performance of a gas-lift valve is a function of the valve design and
application conditions. There are two major categories of gas-lift valve
designs: Injection Pressure Operated (IPO) and Production Pressure
Operated (PPO). An IPO valve is designed to have opening and closing
pressures that are most sensitive to annulus pressure. PPO valves are
designed to have opening and closing pressures that are most sensitive to
production pressure. The flow performance of IPO and PPO valves are
markedly different.
The single most important factor effecting flow performance of a gas-lift
valve is the port size. In most cases, the larger the port, the greater the flow
rate. This is true for both IPO and PPO valves. The next most important
factor is the ratio of injection pressure (Piod) to opening pressure (Pvot); the
higher this ratio, the greater the flow rate. Finally, load rate and stem travel
of the valve have a significant effect on performance. The port size and
ratio of Piod to Pvot are application dependent. They are not a function of
the valve design. The load rate and stem travel are a function of valve
design.
For many years the flow performance of a gas-lift valve was determined
using the Thornhill-Craver equation53. This equation was developed to
predict the flow performance of wellhead beans or chokes. These chokes
were used to control the flow of gas from the gas injection line into the
annulus. The beans were cylindrical, about 6-7 inches long, and had a hole
drilled through the center. The size of the hole determined the choke size.
Many tests were performed to determine the flow rate at different pressures
and the equation is quite accurate for this type of choke.
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The Thornhill-Craver equation existed long before the industry had the
ability to test gas-lift valves and, as a result, was used as the best
approximation of the flow performance of gas-lift valves. Most gas-lift
design programs continue to use Thornhill-Craver to compute flow through
gas-lift valves, even though it was never intended for use with gas-lift
valves. Recent testing of IPO and PPO gas-lift valves has shown that the
Thornhill-Craver equation will over estimate gas-lift valve flow rate by a
factor of two to three. When used to estimate the flow through orifice valves,
Thornhill-Craver will over estimate by about 20-30%.
Fig. VII-18 shows the difference in performance of a 1-inch IPO valve using
both the Thornhill-Craver equation and a tested performance model. The
model is tested by the Valve Performance Clearinghouse (VPC); an industry
consortium for testing gas-lift valves.
800
1 Inch IPO with 12/64ths
VPC
PvoT= 917 Pcf= 900
Temp=125
600
Flowrate (Mscf/d)
400
1 Inch IPO with 12/64ths
Thornhill
PvoT= 917 Pcf= 900
Temp=125
200
0
0
200
400
600
800
1000
Downstream Pressure - (psig)
Fig. VII-18: Thornhill-Craver equation and VPC model Valve Performance Comparison
As noted, the flow performance using the Thornhill-Craver equation shows
typical orifice flow characteristics. The tested performance model shows the
valve flow rate increasing as differential pressure increases and then
decreasing and finally closing. The Thornhill-Craver equation predicts flow
rates much higher than is actually possible.
Fig. VII-19 shows the same valve when the ratio of Piod to Pvot has been
increased sufficiently to ensure the IPO valve will operate as an orifice.
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800
1 Inch IPO with 12/64ths
VPC
PvoT= 917 Pcf= 950
Temp=125
600
Flowrate (Mscf/d)
1 Inch IPO with 12/64ths
VPC
PvoT= 917 Pcf= 1000
Temp=125
400
200
1 Inch IPO with 12/64ths
Thornhill
PvoT= 917 Pcf= 950
Temp=125
0
0
200
400
600
800
1000
Downstream Pressure - (psig)
Fig. VII-19: Thornhill-Craver equation and VPC model Orifice Performance Comparison
In this case, the 1-inch IPO valve has flow performance similar to ThornhillCraver. These two examples show the importance of the ratio of Piod/Pvot
to valve performance. With a Pvot of 917 psi, when Piod is 900 psi
(Piod/Pvot = 900/917 = 0.981), the valve has a peak flow rate of 6,732 m3/d
(225 Mscfd) and throttles closed as production pressure decreases. When
the ratio is 1.036, the valve performs as an orifice with a peak flow rate of
6,732 m3/d (500 Mscfd).
This difference in flow behavior is caused by a valve property referred to as
load rate. Load rate is a measure of the gas-lift valve’s ability to expose a
full open port. Historical models of valve behavior and those employed in
most gas-lift design programs postulate that when the injection pressure
(Piod) reaches the opening pressure (Pvot), the valve will be fully open and
function as an orifice. Load rate prevents this from happening.
The nitrogen charge in the dome and the bellows act as a spring that
attempts to hold the valve in a closed position. As with all springs,
increased force is required to compress the spring. For gas-lift valves,
increased pressure is required to compress the bellows and allow the valve
to expose a fully open port. The higher the load rate, the higher the ratio of
Piod/Pvot required to cause the valve to fully open.
Fig. VII-20 shows the difference in performance for a 1-inch IPO valve with
different load rates. The performance curve with the lower flow rate
corresponds with the valve with a higher load rate.
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500
1 Inch IPO with 12/64ths
VPC
PvoT= 917 Pcf= 915
Temp=125
400
300
Flowrate (Mscf/d)
200
1 Inch IPO with 12/64ths
VPC
PvoT= 917 Pcf= 915
Temp=125
100
0
0
200
400
600
800
1000
Downstream Pressure - (psig)
Fig. VII-20: VPC model Performance Comparison with Different Load Rates
The amount the bellows can be compressed is referred to as stem travel.
The bellows compresses in a nearly linear manner until the bellows
convolutions begin stacking.
At this time the load rate increases
dramatically. The distance the bellows compresses in the linear portion is
referred to as the stem travel. Stem travel must be sufficient to fully expose
the port. This amount differs depending on the port size.
Fig. VII-21 shows a valve with a 16/64ths port and varying amounts of stem
travel.
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1 Inch IPO with 16/64ths VPC
Pcf= 875psig PvoT= 917psig Temp 125F
400
Trvl .04
300
Trvl .034
Flowrate (Mscf/d)
200
Trvl .028
100
Trvl .022
Trvl .016
0
0
200
400
600
800
1000
Downstream Pressure - (psig)
Fig. VII-21: Stem Travel Valve Performance Comparison
One last variable affecting flow performance is the size of the valve. 1-1/2inch valves have much higher flow rates than 1-inch valves with the same
port size. Fig. VII-22 compares a 1-inch and 1-1/2-inch IPO valve with the
same port size and configured to have the same opening and closing
pressures.
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800
1 Inch IPO with 12/64ths
VPC
PvoT= 917 Pcf= 900
Temp=125
600
Flowrate (Mscf/d)
400
Camco R-20 with 12/64ths
VPC
PvoT= 920 Pcf= 913
Temp=125
200
0
0
200
400
600
800
1000
Downstream Pressure - (psig)
Fig. VII-22: Valve Size Performance Comparison
The flow performance of a gas-lift valve is markedly different from the
Thornhill-Craver equation. The amount of gas flowing through a valve has a
significant effect on how a gas-lift well performs. A simulator must have
good gas-lift valve performance models to give accurate result. Several
valve performance models are available.
TUALP Model
The Tulsa University Artificial Lift Project (TUALP) performed many tests on
gas-lift valves in the 1980’s and ‘90’s. The results of these tests and the
models were published as graduate student theses and are available from
the Tulsa University Library. These models are statistical and attempt to
predict performance by adjusting the coefficients in the parabola equation.
The models do not account for valve properties such as load rate and stem
travel. The models have an accuracy of about 30-40% within the range of
pressures used for the tests. Beyond this range the accuracy drops off
significantly.
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Winkler-Eads Model
This model uses the Thornhill-Craver equation with a modification. Normally
the Thornhill-Craver equation uses the full area of the port but this model
uses only that amount of the port open to flow. This is calculated using the
force balance equation for the valve, and the load rate. It assumes the area
open to flow is equal to the surface area of the frustum of a right cone. This
model is entirely theoretical and does not require testing of the gas-lift valve.
As such, it will not account for specific valve design characteristics. The
model is accurate to within 15-25% for valves with port sizes less than
12/64ths inch. The description of the model with equations is available54.
API Simplified Model
This model is a combination of theoretical and tested valve performance
factors. The model uses the ISA method of testing valves to determine the
flow coefficient (Cv) and combines this with the force balance equation for
the valve. The model has an accuracy of 15-25% for all port sizes and
pressure ranges. This model was first published in API Recommended
Practice 11V2. It is also available in ISO 17078.2.
Valve Performance Clearinghouse (VPC™)
This model is a combination of theoretical and tested valve performance
factors. The model uses the ISA method of testing valves to determine the
flow coefficient (Cv) and actual flow performance tests of the valve. This is
combined with the force balance equation using a tested load rate of the
valve to determine the amount of stem travel. A correlation is then
developed using actual test data to predict flow performance. The model
has an accuracy of 10-15% for all valves, all port sizes, and all pressure
ranges.
Most of the current gas-lift design programs now have the ability to enable
the VPC™ models.
Shell Valve/Choke Model
Shell Oil Company places chokes downstream of the port in IPO valves and
finds that the flow performance of the valve is superior to a valve without
chokes. This seems counter-intuitive but anecdotal evidence has proven it
to be true. The VPC™ conducted tests and verified that in some cases, a
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downstream choke in an IPO valve actually increases the flow rate. See
Fig. VII-23. This model has an accuracy of about 10-15%.
Fig. VII-23: Comparison of Valve Performance with a choke (Green Line) and without a
choke (Blue Line).
Summary
The unloading sequence of a gas-lift well is important. If the gas-lift design
is unable to unload to the orifice valve at the desired depth, the well will
under perform with injection through one or more upper valves and possibly
with multipointing.
Unloading gas-lift valves do not perform as well as Thornhill-Craver predicts.
This is particularly true for 1-inch valves. The ability to design a gas-lift well
that performs as expected is directly connected to the ability to predict flow
performance of the unloading gas-lift valves. With respect to gas-lift
simulators, the accuracy of the results depends on use of a good valve
performance model.
How to use the models
All of the models use equations or correlations to compute flow rate. The
degree of complexity of the equations or correlations is a function of the
model used. In all cases, it is best to use a computer to solve the equations.
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The models will predict a single flow rate for a specific set of conditions. To
develop a full performance curve as shown in the graphs above, the annulus
pressure (Piod) is held constant while the production pressure (Ptf) is
iterated from a value equal to Piod and decreased to atmospheric or until
the valve closes. This type of curve shows typical performance but is not
realistic for an actual unloading scenario. During unloading, and sometimes
during lifting, the annulus pressure and production pressure are constantly
changing.
To give accurate results, a simulator must invoke the model at each point in
time for the specific conditions existing at that time. Use of a pre-calculated
performance curve as shown in the graphs above to predict valve flow rate
during the entire unloading sequence will lead to simulator errors and could
give false results.
When to use the models
Valve performance models are used during two distinct phases. Once
during the design phase, and during the simulation phase. The design
phase is a static condition and the simulation phase is dynamic. In the
design phase, valve performance models are used to determine a port size
for the valve. In the simulation phase, the valve characteristics are given
and the model is used to predict or analyze performance.
Well equipment:
-
The effects of down-hole pressure restrictions such as safety valves,
corrosion, scale, and wax deposits, and the effects of tight spots or holes in
the tubing.
Ensure that dynamic simulation flow assurance studies are performed in the
well. Normally, facilities engineers only perform flow assurance studies
downstream of the sub-sea well and do not include the wellbore.
In well completions, there will be a slight reduction in internal diameter and
less roughness in the down-hole safety valve, SSD, ICV, ICD, PBR, and
nipple profiles that affect the fluid flow pattern and frictional pressure drop.
Include all such down-hole equipment while using dynamic modelling tools to
predict the effect of this equipment on the fluid flow.
In the upper part of the well closest to sub-sea temperature conditions, the
temperature can fall below hydrate and/or wax deposition conditions. The
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SSSV should be located in a zone were no hydrate formation or wax
deposition is expected as this could compromise its closure. Use hydrate and
wax modelling as appropriate to see the impact of hydrate and wax
deposition, and to plan remedial hydrate and wax prevention and wax
cleaning schedules.
Figures VII-24, VII-25a and VII-25b show an SSSV and the effect of scale
deposition in a gas-lift mandrel.
Fig. VII-24: Subsurface Safety Valve
Fig. VII-25 a: Scale deposits
b: GL Mandrel cut-a-way
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Typically, the major pressure drop will be in the choke used to control flow at
surface and downhole (ICV, ICD, GLV, etc.). P-T conditions downstream may
fall in the hydrate formation or wax deposition zones.
-
The effects of risers and the effects of surface equipment such as flow
lines, manifolds, separators, and separator back-pressure.
The gases and liquids may exist as a homogeneous mixture or the liquid may
be in slugs with gas pushing behind it. The liquid and gas may also flow
parallel to each other or other combinations of flow patterns may be present.
Fig. VII-26 illustrates some common vertical and horizontal multiphase flow
patterns. Each of these flow patterns will produce a different pressure drop
over a given distance. Well/Flowline geometry will affect multiphase flow
patterns. See Fig. VII-27. In addition to flow pattern, factors affecting the
pressure loss in multiphase flow include:

Inside diameter of flowing conduit

Wall roughness

Inclination

Liquid density

Gas density

Liquid viscosity

Gas viscosity

Superficial liquid velocity

Superficial gas velocity (See Fig. VII-28)

Liquid surface tension

Wall contact angle

Gravity acceleration

Pressure gradient
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Fig. VII-26: Common vertical and horizontal multiphase flow patterns
Fig. VII-27: Well/Flowline Common Geometries
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Fig. VII-28: Effect of critical velocity in horizontal/inclined flow.
Since the pressure drop is caused by a complex interaction of many factors,
one of the major problems in analyzing flowing wells and designing gas-lift
installations has been the prediction of flowing pressure at depth. It is
important to understand the pressure drop in the horizontal flow line to
determine the back pressure at the well head. This problem has been the
subject of numerous studies. A dynamic simulator is required to understand
multiphase flow behavior.
Extra pressure is required to lift fluids through a riser. Furthermore, risers are
terrain induced slugging generators. Dynamic simulation is required to
properly model terrain slugging.
Well design:
-
The effects of well design and the associated dynamic effects on well
operations includes:
The type of well completion, well profile, and well location play a major role in
designing gas-lift components and systems. Figures VII-29 a, b and c show
common vertical, horizontal, and multi-lateral well completions.
Dynamic modeling with the current well fluid properties, well/flowline
geometry, well completion and flowline data, and flow restrictions should be
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Dynamic Simulation of Gas-Lift Wells and Systems
used to simulate the effect of gas-lift at different locations. Chapter VII-D,
provide more detail information on dynamic modelling implementation.
o Vertical wells
wells
o Horizontal wells
Fig. VII-29: a- Vertical well profile
b - Horizontal Well profile
o Multi-lateral
c - Multilateral well profiles
Slug flow and water accumulation are typical problems associated to
horizontal wells:
•
Horizontal wells allow a reduced drawdown to obtain a desired rate,
thereby maintaining the reservoir pressure above the bubble point for
longer periods of time, thus reducing GORs and improving recovery. But
gas velocity may be too slow and lead to slug flow. The addition of gas-lift
gas increases the superficial gas velocity and changes the multiphase flow
to a more stable flow regime.
API RP 19G11
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•
Page 145
Horizontal wells producing below bubble point pressure can act as
downhole separators generating slug flow. The terrain can also be
originating slug flow.
Dynamic simulation is the optimum method for predicting slugging flow and
estimating water accumulation, as explained in detail in Sections VII-A and B.
To properly model the production from horizontal wells, several inflow points
should be included in the dynamic model. Each inflow point can have different
reservoir properties and IPRs. Free gas and/or water sources can also be
included to model gas and water coning respectively.
In the case of intelligent wells with multiple production zones such as
multilayer and/or multilateral legs that allow remote selective production,
dynamic simulation brings the additional benefit of virtually testing each zone
individually or in combination to establish maximum total production potential
prior to any actual operation. Well clean-up operations can be improved by
simulating how layers and legs can be produced separately to generate the
maximum drawdown. During production, gas and/or water coning can be
avoided and slugging minimized by optimizing the opening of each ICV.
Dynamic simulation can help justify the use of intelligent completions by
demonstrating the added value during the well completion design stages. The
well may not be producing from half of the reservoir section without intelligent
completions.
In multi-lateral or multi-layer wells producing from different reservoirs with
different fluid compositions, dynamic simulation offers the possibility of
tracking the different fluids and estimating the resulting mixture composition
along the production/injection path. Dynamic simulation can also predict
cross-flow between formations during static or producing conditions. Chapter
VI-E describes the application of dynamic simulation in complex and intelligent
wells in detail.
-
When and where to inject gas in a well: in the vertical, in the knee, in a
rat hole, in the horizontal section.
Gas-lift is by nature a transient artificial lift system. Dynamic simulation can
define the amount of gas-lift gas and the optimum gas injection point.
Fig. VII-30 shows where to inject lift gas for more effective fluid flow and how
to avoid liquid hold up and loading in a riser section.
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Fig. VII-30: Vertical well profile
More in-depth analysis is required to determine when to start gas-lift, where to
inject gas, and how much lift gas is required for optimum well performance.
Dynamic modelling may be used and various scenarios run to simulate
injecting at different locations in the well tubular or riser sections with the
expected fluid rate, to understand the impact of gas-lift and optimize total well
production and lift gas utilization.
In offshore wells producing to a platform, gas-lift optimization may be obtained
initially by injecting gas in the base of the riser rather that going all the way
through a sub-sea flowline to the wellhead with the pressurized lift gas. The
cost savings can be significant. Later in the field life, when reservoir depletion
occurs and water cut increases, gas-lift injection through the tubing-casing
annulus may be the optimal scenario. Dynamic simulation can compare the
different scenarios and define the optimum approach. It can also forecast the
optimum time to switch producing scenarios and methods.
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9. Case Histories
This is a summary of pertinent case histories where dynamic simulation has been used
to address and solve real world gas-lift well and system situations. Chapter IX provides
a list of papers with actual case applications and evaluations.
Case History 1: Penguins Gas-Lift
The Penguins field in the North Sea was discovered in 1974. Several exploration
wells were drilled until 1991 to understand the field and acreage. Numerous field
development options were considered; it was concluded that a 65 km (40.4 miles)
sub sea tie-back to the Brent Charlie platform was the most economic option. The
key technical justifications for this choice were that processing capacity was
available, product evacuation routes were established, and gas-lift compression
was already in use for the platform wells.
The field comprises a cluster of reservoirs and is located north of the Brent Charlie
platform, UKCS and has 9 production wells. See Fig. VIII-1. These wells produce
via a single 35.6 cm (14 inch) commingled flowline. Initially the field produced
naturally from 2003 to 2007, at which time some wells started to require artificial lift.
Fig. VIII-1: Penguins Field Schematic Layout in Relation to the Brent Charlie Platform
Based on the reservoir fluid type, it was foreseen that artificial lift would be required
in a number of wells to ensure ultimate recovery; therefore these wells were
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completed with a single gas-lift mandrel (GLM) with a shear orifice valve preinstalled.
As the wells depleted, the black oil wells began to struggle to flow, to the point were
the gassier condensate wells had to be choked back severely to avoid killing the
black oil wells. Eventually, one well ceased production when other wells were
flowing. The other wells were also having kick-off problems and required the
pipeline to be bled down to below normal operating pressure of 35 – 40 barg (507.6
– 580.2 psig) to allow them to restart. Hence optimization of the field production
became more and more complex over time.
In 2005 the gas-lift project was approved, using a 10.2 cm (4 inch) supply line from
the Brent Charlie platform, and modifying an existing injection compressor to
provide the required rate of 500 Km3/d (18 MMscf/d) of lift gas at pressures up to
280 barg (4061 psig).
As the project on-stream date drew closer, it was realized that the commissioning
phase posed some challenges and required detailed planning. Commissioning
challenges that were evaluated included:

Avoiding hydrates or other temperature related integrity limits due to Joule
Thomson effects through various valves/restrictions in the system.

Staying within velocity limits of orifice valves in the side pocket mandrels.

Minimizing risk of slugging of wells and/or pipeline during commissioning and
steady state flow which could result in a platform trip at Brent Charlie.

Minimizing time taken for commissioning process and hence production
deferment.

Determining measurable indicators as to when the gas-lift line, jumpers, and
annuli were cleared/unloaded.
Following the commissioning phase, challenges that existed in field operations
were:

Managing liquid slugs during future start-up of the system.

Maintaining stability of the wells under conditions of continuous gas-lift.
Engineering assessments and achieving the desired targets were primarily carried
out by utilizing both a commercial dynamic transient simulator and steady-state
modelling software.
The main objective of the studies carried out using transient simulations for the
Penguins field is to provide high-level guidance and procedures for the various
operational aspects of interest for the gas-lift system. To obtain an all-purpose
model, the complete Penguins system including the wells, the 35.6 cm (14 inch)
production pipeline and the 10.2 cm (4 inch) gas-lift pipeline, was built. For each of
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the wells, the inflow and outflow were modelled using parameters including
reservoir pressure, PI, and fluid PVT. This model was validated against field data
and was determined to be representative of the Penguins system.
In the interest of computational expense and time, subsequent simulation work was
done using simplified models reduced from the full system model. The full system
model includes the production and gas-lift lines and all the wells, gas-lift annuli, and
jumpers. Typical model run times were reduced from the order of days to hours.
The phases of clearing MEG from the gas-lift line and crossovers, and the
unloading of the base oil from the annuli were modelled in an iterative fashion to
determine the required procedures to remain within the system limitations.
The main step requiring iteration was the shearing of the gas-lift orifice in each well.
Initial runs of the model resulted in velocities across the orifice that far exceeded
the 1 bbl/min limitation and also showed temperatures at the gas-lift choke that
reached –30 oC (-22 oF). The process control for this step was to reduce the
pressure in the gas-lift line. Iterations were run on each well to find a balance that
allowed the process to stay comfortably within the system limits of temperature and
velocity, while minimizing overall time for commissioning.
Further to the initial commissioning, subsequent field start-up guidelines were
derived from transient simulation. Scenarios developed for analysis were based on
attempts to generate the largest perceivable slug sizes arriving at the Brent Charlie
facilities. These were established with the most aggressive start up scenarios
foreseeable under the limits of operation. The sequences generate liquid arrival
rates within the handling capacity of the platform facilities.
Well stability was a concern as this may cause undesired interruptions in
production. Transient simulation has been used to investigate stability for each of
the gas-lifted wells under conditions of continuous gas-lift.
The results of the
dynamic simulations have been used to create stability maps whereby regions of
unstable well production have been identified.
Commissioning of the gas-lift line and the 5 wells was efficiently and successfully
executed as a result of the good planning and guidance provided by transient
modelling.
Dynamic simulations using transient modelling were helpful in providing guidance
and procedures for the commissioning process, predicting pressure, temperature,
velocity transients, and the associated integrity risks.
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Case History 2: Transient Gas-Lift Analysis in ERD and non-ERD Wells
Introduction
A transient multiphase flow simulator was used to investigate gas-lift stability in
several extended reach (ERD) and non-ERD well types. Models have been built for
8 different cases:



17.8 cm (7 inch) ERD well model
-
Injection pressure 110 bar (1595 psia)
-
Injection pressure 140 bar (2031 psia)
17.8 cm (7 inch) non-ERD well
-
Injection pressure 110 bar (1595 psia)
-
Injection pressure 140 bar (2031 psia)
14.0 cm (5.5 inch) ERD well
- Injection pressure 110 bar (1595 psia)
- Injection pressure 140 bar (2031 psia)

14.0 cm (5.5 inch) non-ERD well
-
Injection pressure 110 bar (1595 psia)
-
Injection pressure 140 bar (2031 psia)
Gas-lift stability was evaluated using a commercial transient simulator for each of
these cases at water cuts of 0, 40, 60, 80, and 95%. A tubing head pressure of 16
bar (232 psia) and a reservoir pressure of 175 bar (2538 psia) were assumed.
Conclusions

For nearly all cases, flow is predicted to be stable with the exception of water
cuts greater than 80-90%.

The injection pressure did not have a significant impact on the stability of the
flow. However, since the injection depths were slightly deeper for the higher
injection pressure cases, the flow was slightly more stable in the 110 bar (1595
psia) injection pressure cases.

For the ERD wells (deep injection), there is not a significant difference between
the 17.8 and 14.0 cm (7 and 5.5 inch) tubing in terms of flow stability at low
water cuts. As expected, the 14.0 cm (5.5 inch) tubing wells are more stable at
higher water cuts.
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For the non-ERD wells (shallow injection), the 17.8 cm (7 inch) tubing provides
the greatest stability with gas-lift (case 3 is stable at all water cuts and gas
injection rates).
Recommendations


ERD Wells
-
If 113,280 m3/d (4 MMscf/d) injection rate is available, 14.0 cm (5.5 inch)
tubing in the ERD wells will allow for stable production at water cuts up to
80% for both 110 bar (1,595 psia) and 140 bar (2031 psia) injection
pressures. While the 17.8 cm (7 inch) tubing will allow for higher production
rates, the flow will be unstable at 80 % watercut with 140 bar (2031 psia)
injection pressure.
-
If 226,560 m3/d (8 MMscf/d) injection rate is available, 14.0 cm (5.5 inch)
tubing in the ERD wells will allow for stable production at all water cuts.
While the 17.8 cm (7 inch) tubing will allow for higher production rates, the
flow will be unstable at 95 % water cut.
17.8 cm (7 inch) tubing in the non-ERD wells will allow for higher production
flow rates without gas injection. Also, at gas injection rates of 4 and 8 MMscf/d,
production will be stable at all water cuts. This is not the case with 14.0 cm (5.5
inch) tubing.
Models Used
A commercial transient simulator was used for all transient gas-lift simulations. Fig.
VIII-2 shows a schematic of the model.
P
Annulus
P
Tubing
Well
Fig. VIII-2: Dynamic Model of Well Including Annulus
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A well module was used for inflow from the reservoir. The IPR was matched to a
commercial steady-state simulator model provided by the project team. Constant
pressure boundaries at the tubing head and casing head were used. The choke on
the annulus branch was controlled to provide a constant gas flow rate. The gas-lift
valve was modelled as a valve with ID of 20.6375 mm (0.8125”).
Using the constant pressure boundary for the gas injection provided for a proper
stability analysis. The model also incorporated the effect of the gas-lift gas flowing
down the annulus of the well.
A PVT package was used to simulate the production and gas-lift fluids. As no PVT
data was given, the data used to characterize the PVT in the commercial steadystate simulator model was used. The PVT package was able to replicate the
measured PVT to within a few percent. The gas-lift gas was modelled as a 0.7
gravity gas comprised of methane, ethane, and propane.
The profiles used for each well are given in Fig, VIII-3. These profiles were taken
from the simulator models.
0
5.5" ERD and 7.0" ERD
5.5" NONERD
7.0" NONERD
500
TVD (m)
1000
1500
2000
2500
3000
0
1000
2000
3000
4000
Horizontal Distance (m)
Fig. VIII-3: Profile of each well
5000
6000
7000
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Note that the 14.0 cm and 17.8 cm (5.5 and 7 inch) ERD wells are highly deviated
and step out nearly twice as far as the non-ERD wells. Table VIII-1 gives more
detail for each of the cases.
Table VIII-1. Details of each case
Case
Wells
Tubing
OD (in)
Injection
MD (m)
Injection
Pressure (bara)
1
7” ERD
7
4941
110
2
7” ERD
7
6350
140
3
7” non-ERD
7
3508
110
4
7” non-ERD
7
4100
140
5
5.5” ERD
5.5
4878
110
6
5.5” ERD
5.5
6350
140
7
5.5” non-ERD
5.5
2698
110
8
5.5” non-ERD
5.5
3200
140
Comparison of the transient simulator and the steady-state simulators
Before the full array of simulations was performed, a comparison of three different
programs was made to ensure that the transient simulator was suitable for gas-lift
simulations. Predictions for the dynamic simulator were compared with steady-state
predictions from steady-state simulators. Fig. VIII-4 shows the comparison for Case
5. The dynamic simulator predictions are within 5% of the steady-state simulator,
which is reasonable.
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Dynamic Simulation of Gas-Lift Wells and Systems
11100
10900
Simulator X
Simulator Y
Simulator Z
Oil Rate (stb/d)
10700
10500
10300
5.5" ERD Well
0% Watercut
1595 psia Injection
232 psia THP
2538 psia Pres
10100
9900
9700
9500
0
1
2
3
4
5
6
7
8
Gas Injection Rate (mmscf/d)
Fig. VIII-4: Comparison of Dynamic Simulator X and Steady-State Simulators Y and Z
Predictions from two steady-state simulators for Cases 1, 3, 5, and 7 at 0% water
cut. Table VIII-2 shows the comparisons.
Table VIII-2. Comparison of Simulators X and Y for Cases 1, 3, 5, and 7 at 0% WC
Oil Rate (stb/d)
Gas Rate
Case #1
Case #3
Case #5
Case #7
(mmscf/d)
X
Y
X
Y
X
Y
X
Y
0
16432
17125
18388
18487
10276
10850
13236
14298
1
16574
17351
18580
18604
10333
10916
13342
14370
2
-
17529
18725
18687
10314
10959
13401
14399
4
16713
17779
18898
18806
10190
10971
13422
14417
8
16586
17967
18916
18809
9793
10732
13252
14203
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Differences between the two programs are expected due to: (1) slight differences in
the PVT properties of the fluids and (2) different flow correlations used in the tubing
and casing annulus. However, the two programs are fairly consistent with one
another.
Results
Figures VIII-5 through VIII-12 show the predicted oil rate versus gas injection rate
for each of the eight cases. Note that the shaded region in the plots represents
regions of unstable or transient flow.
20000
18000
0% Watercut
16000
Oil Rate (stb/d)
14000
Simulator X - Solid Lines
Simulator Y - Dashed Lines
12000
10000
CASE #1
7" ERD Well
110 bar Injection
16 bar THP
175 bar Pres
40% Watercut
8000
60% Watercut
6000
4000
80% Watercut
2000
95% Watercut
0
0
1
2
Transient
Flow
3
4
5
6
Gas Injection Rate (mmscf/d)
Fig. VIII-5: Simulation results for Case 1
7
8
9
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Dynamic Simulation of Gas-Lift Wells and Systems
18000
0% Watercut
16000
14000
Oil Rate (stb/d)
12000
Simulator X Predictions
CASE #2
7" ERD Well
140 bar Injection
16 bar THP
175 bar Pres
40% Watercut
10000
8000
60% Watercut
6000
4000
80% Watercut
2000
Transient
Flow
0
0
1
2
95% Watercut
3
4
5
6
7
8
9
Gas Injection Rate (mmscf/d)
Fig. VIII-6: Simulation results for Case 2
20000
0% Watercut
18000
CASE #3
7" NONERD Well
110 bar Injection
16 bar THP
175 bar Pres
16000
Simulator X - Solid Lines
Simulator Y - Dashed Lines
Oil Rate (stb/d)
14000
12000
40% Watercut
10000
8000
60% Watercut
6000
4000
80% Watercut
2000
95% Watercut
0
0
1
2
3
4
5
6
Gas Injection Rate (mmscf/d)
Fig. VIII-7: Simulation results for Case 3
7
8
9
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Dynamic Simulation of Gas-Lift Wells and Systems
20000
0% Watercut
18000
16000
Simulator X Predictions
Oil Rate (stb/d)
14000
12000
CASE #4
7" NONERD Well
140 bar Injection
16 bar THP
175 bar Pres
40% Watercut
10000
8000
60% Watercut
6000
80% Watercut
4000
2000
95% Watercut
Transient Flow
0
0
1
2
3
4
5
6
7
8
9
Gas Injection Rate (mmscf/d)
Fig. VIII-8: Simulation results for Case 4
12000
0% Watercut
10000
Simulator X - Solid Lines
Simulator Y - Dashed Lines
Oil Rate (stb/d)
8000
6000
CASE #5
5.5" ERD Well
110 bar Injection
16 bar THP
175 bar Pres
40% Watercut
60% Watercut
4000
80% Watercut
2000
Transient Flow
95% Watercut
0
0
1
2
3
4
5
6
Gas Injection Rate (mmscf/d)
Fig. VIII-9: Simulation results for Case 5
7
8
9
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Dynamic Simulation of Gas-Lift Wells and Systems
10000
Oil Rate (stb/d)
8000
Simulator X Predictions
0% Watercut
CASE #6
5.5" ERD Well
140 bar Injection
16 bar THP
175 bar Pres
40% Watercut
6000
60% Watercut
4000
80% Watercut
2000
95% Watercut
Transient Flow
0
0
1
2
3
4
5
6
7
8
9
Gas Injection Rate (mmscf/d)
Fig. VIII-10: Simulation results for Case 6
16000
14000
Oil Rate (stb/d)
10000
0% Watercut
CASE #7
5.5" NONERD Well
110 bar Injection
16 bar THP
175 bar Pres
12000
Simulator X - Solid Lines
Simulator Y - Dashed Lines
8000
40% Watercut
6000
60% Watercut
4000
80% Watercut
2000
95% Watercut
Transient Flow
0
0
1
2
3
4
5
6
Gas Injection Rate (mmscf/d)
Fig. VIII-11: Simulation results for Case 7
7
8
9
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Dynamic Simulation of Gas-Lift Wells and Systems
14000
0% Watercut
12000
Simulator X Predictions
10000
Oil Rate (stb/d)
CASE #8
5.5" NONERD Well
140 bar Injection
16 bar THP
175 bar Pres
8000
40% Watercut
6000
60% Watercut
4000
80% Watercut
2000
95% Watercut
Transient Flow
0
0
1
2
3
4
5
6
7
8
9
Gas Injection Rate (mmscf/d)
Fig. VIII-12: Simulation results for Case 8
For nearly all cases, the flow is predicted to be stable with the exception of water
cuts greater than 80-90%. The injection pressure did not have a significant impact
on the stability of the flow. However, since the injection depths were slightly deeper
for the higher injection pressure cases, the flow was slightly more stable in the 110
bar (1,595 psia) injection pressure cases.
Flow Stability
Effect of Gas Injection Rate: For the majority of the cases, the results of the
dynamic simulations show steady-state behavior quite similar to that of the steadystate simulator. However, at higher water cuts and lower gas injection rates, the
dynamic simulator predicts the flow to be either unstable or transient whereas the
steady-state simulator predicts the flow to be stable. Although this happens in many
of the cases run, Case 5 at 95% water cut gives a more illustrative example of
unstable flow. Table VIII-3 shows the dynamic and steady-state results for Case 5
at 95% watercut.
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Dynamic Simulation of Gas-Lift Wells and Systems
Table VIII-3. Comparison of Simulator X and Y for Case 5 at 95% WC (shaded cells are for
transient flow)
X
Y
Gas Rate Oil Rate
Oil Rate
(mmscf/d)
(stb/d)
(stb/d)
0
0
0
1
0
132
2
85
219
4
271
319
8
358
383
Figures VIII-13 through VIII-15 show total liquid flow rates vs. time for 2, 4, and 8 mmscf/d.
25000
CASE #5
5.5" ERD Well
95% Watercut
2 mmscf/d Gas Rate
110 bar Injection
16 bar THP
175 bar Pres
Total Liquid Rate (stb/d)
20000
Simulator X
Simulator Y
15000
10000
5000
0
0
5000
10000
15000
20000
25000
30000
35000
Time (s)
Fig. VIII-13: Comparison of Simulator X and Y at 2 MMscf/d gas rate
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Dynamic Simulation of Gas-Lift Wells and Systems
10000
Simulator X
Simulator Y
9000
Total Liquid Rate (stb/d)
8000
7000
6000
5000
CASE #5
5.5" ERD Well
95% Watercut
4 mmscf/d Gas Rate
110 bar Injection
16 bar THP
175 bar Pres
4000
3000
2000
1000
0
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
Time (s)
Fig. VIII-14: Comparison of Simulator X and Y at 4 MMscf/d gas rate
10000
Simulator X
Simulator Y
9000
Total Liquid Rate (stb/d)
8000
7000
6000
5000
CASE #5
5.5" ERD Well
95% Watercut
8 mmscf/d Gas Rate
110 bar Injection
16 bar THP
175 bar Pres
4000
3000
2000
1000
0
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
Time (s)
Fig. VIII-15: Comparison of Simulator X and Y at 8 MMscf/d gas rate
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As can be seen, the steady-state simulator model predicts a steady liquid flow rate
due to the nature of the program, whereas the dynamic simulator predicts the true
transient behavior. In this case, severe slugging is expected at 2 MMscf/d with the
slugging being partially mitigated by increasing the injection rate to 4 MMscf/d.
Similar behavior is shown for several of the other cases which are highlighted as
transient flow in Figures VIII-5-12 and Tables VIII-1-3.
Figures VIII-13 and VIII-14 give ample reason for using a transient multi-phase flow
simulator as a final check on the stability of a gas-lift design.
Effect of Tubing Head Pressure: What follows is a description of the transient
behavior via dynamic simulations due to changes in the tubing head pressure (4
MMscf/d injection rate and 95% water cut case). Fig. VIII-16 gives an overview of
how the slug frequency and size changes with wellhead pressure (THP).
S-S
Region
1
Surging Region
Intermittent
Slugging
Region
Oscillating
Region
Severe Slugging
Region
180
0.8
160
140
0.6
120
100
0.4
80
Slug Size (stb)
Slug Frequency (1/hour)
200
60
Slug Frequency
Slug Size
0.2
4 mmscf/d gas rate
95% Watercut
0
40
20
0
0
5
10
15
20
25
Tubing Head Pressure (bar)
Fig. VIII-16: Overview of Slug Frequency and Size versus THP
Transitioning from low to high tubing head pressure, the behavior of the flow starts
as steady-state behavior and transitions to a surging flow (Fig. VIII-17a). At ~10 bar
(150 psia) THP, the flow turns to an intermittent slugging, which then transitions to
an oscillating flow (Fig. VIII-17b). The oscillating flow transitions to a severe
slugging region beyond ~21 bar (310 psia) (Fig. VIII-17c).
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14000
THP - 1 bar
THP - 5.2 bar
Total Liquid Rate (stb/d)
12000
10000
8000
6000
4000
2000
0
0
5000
10000
15000
20000
25000
30000
Time (s)
Fig. VIII-17a: Rate versus time for THP of 1 and 5.2 bar
35000
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Dynamic Simulation of Gas-Lift Wells and Systems
14000
THP - 13.8 bar
12000
Total Liquid Rate (stb/d)
THP - 18.6 bar
10000
8000
6000
4000
2000
0
0
5000
10000
15000
20000
25000
30000
35000
Time (s)
Fig. VIII-17b: Rate versus time for THP of 13.8 and 18.6 bar
14000
THP - 20.7 bar
12000
Total Liquid Rate (stb/d)
THP - 370 25.5
10000
8000
6000
4000
2000
0
0
5000
10000
15000
20000
25000
30000
Time (s)
Fig. VIII-17c. Rate versus time for THP of 20.7 and 25.5 bar
35000
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Dynamic Simulation of Gas-Lift Wells and Systems
9000
8000
Liquid Rate (stb/d)
7000
6000
5000
4000
3000
2000
1000
0
0
5
10
15
20
25
Tubing Head Pressure (bar)
Fig. VIII-18: Average Daily Liquid Rate versus Tubing Head Pressure
As expected, the average daily liquid rate reduces as tubing head pressure
increases, as shown in Fig. VIII-18. However, only using by transient simulation
tools can the actual dynamics of the system be investigated.
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Dynamic Simulation of Gas-Lift Wells and Systems
Effect of Orifice Port Size: Here is a plot showing the effect of orifice port size for
the 95% water cut and 4 MMscf/d injection rate case (Fig, VIII-19). Note that, if not
properly accounted for, the orifice port size could either restrict gas flow or cause
unwanted transients in the well.
20000
18000
CASE #5
5.5" ERD Well
95% Watercut
4 mmscf/d Gas Rate
110 bar Injection
16 bar THP
175 bar Pres
Total Liquid Rate (stb/d)
16000
14000
12000
0.25" Valve
0.5" Valve
1" Valve
1.5" Valve
10000
8000
6000
4000
2000
0
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
Time (s)
Fig. 19: Effect of Orifice Port Size on Flow Stability
The results given in Fig, VIII-19 show the importance of reviewing all production
scenarios when designing a gas-lift system; including orifice port size.
API RP 19G11
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Dynamic Simulation of Gas-Lift Wells and Systems
Page 167
References
This is a comprehensive bibliography or set of references for text books, papers, and
magazine articles that describe use of dynamic simulation technology for gas-lift wells and
systems, and for other related general production system applications such as wax,
hydrates, and flow assurance. Some references are provided to help understand dynamic
simulation.
A list of informative references is included after the bibliography.
Bibliography
1. Mantecon, J.C.: ”The Virtual Well: Guidelines for the Application of Dynamic
Simulation to Optimize Well Operations, Life Cycle design and Production", SPE
paper 109829, presented at the 2007 SPE Annual Technology Conference and
Exhibition held in Anaheim, California, USA, 30-3 November 2007.
2. Lancy, M.F.: ”Dynamic Simulation of the Europa and Mars Expansion Projects: A
New Approach to Coupled Subsea and Topsides Modelling”, SPE paper 56704,
presented at the 1999 SPE Annual Technology Conference and Exhibition held in
Houston, Texas, 3-6 October 1999.
3. Gayton, P.W., Miller, S.D., and Napalowski, R.: “Innovative Development Engineering
Techniques”, SPE paper 65202, presented at the SPE European Petroleum
Conference held in Paris, France, 24-25 October 2000.
4. Schoppa, W., Jayawardena, S., Agbaje, T., Ebere, D., and Iyer, S. “Bonga Flow
Assurance Benchmarking via Field Surveillance”, OTC paper 18949, presented at the
2007 Offshore Technology Conference held in Houston, Texas, U.S.A., 30 April - 3
May 2007.
5. Zakarian, E, Larrey, D.: “A systematic Investigation of Girassol Deep Water Field
Operational Data to Increase Confidence in Multiphase Simulation”, IPTC paper
11379, presented at the Internationl Petroleum Technology Conference held in Dubai,
4-6 Dec 2007.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 168
6. Gudimetla, R., Carrol, A., Havre, K. and Canon, J.: ”Gulf of Mexico Field of The
Future Subsea Flow Assurance”, OTC paper 18388, presented at Offshore
Technology Conference held in Houston, Texas, U.S.A., 1-4 May 2006.
7. Costa, D., Vu, V-K, Barnay, G.C., Larrey, D., McClimans, O.T. and Sand, E.B.:
“Investigation of a Subsea Separation Station Operating Envelope using Subsurface to Topsides Integrated Dynamic Simulations”, OTC paper 18709, presented
at Offshore Technology Conference held in Houston, Texas, 30 April-3 May 2007.
8. Bell, G.M., Chin, Y.D., and Hanrahan, S.: “State of Art of Ultra Deepwater Production
Technologies”, OTC paper 17615, presented at Offshore Technology Conference
held in Houston, Texas, USA, 2-5 May 2005.
9. Tagore, A., Utgard, M., Ramachandran, K., Alwazzan, A. and McDermott, J.R..:
“Fluid Characterization: Impact on Deepwater Field Development”, SPE paper
115777, presented at the 2008 SPE Annual Technology Conference and Exhibition
held in Denver, Colorado, USA, 21-24 September 2008.
10. Shi, H., Holmes, J., Aziz, K., Durlofsky, L., K., Diaz, L., Alkeya, B., and Oddie, G.:
“Drift-Flux Modelling of Two Phase Flow in Wellbores”, SPE paper 84228, SPE
Journal Vol 10 #1, March 2005.
11. Bendiksen, K. H. et al., “The Dynamic Two-Fluid Model OLGA: Theory and
Application, SPE Production Engineering, May 1991.
12. Falcone, G., Teodoriu, C., Reinicke, K.M., Bello, O.O., and Clausthal, T.U.:
“Multiphase Flow Modelling Based on Experimental testing: A comprehensive
Overview of Research Facilities Worlwide and the need for Future Developments”,
SPE paper 110116, presented at the 2007 SPE Annual Technology Conference and
Exhibition held in Anaheim, California, USA, 30-3 November 2007.
13. Sturm, W.L., Belfroid, S.P.C., van Wolfswinkel, D., Peters, M., Verhelst, F.: “Dynamic
Reservoir Well Interaction”, SPE paper 90108, presented at SPE Annual Technical
Conference and Exhibition held in Houston, Texas, U.S.A., 26-29 September 2004.
14. Sagen, J., Sira, T., Ek, A., Selberg, S., Chaib, M. and Eidsmoen, H.: “A Coupled
Dynamic Reservoir and Pipeline Model – Development and Initial Experience”, 13th
International Multiphase Conference on Multiphase Production Technology 07’,
Edinburg, UK, 13-15 June, 2007.
15. Hu, B., Sagen. G., Chupin, G., Haugset, T., Arild, E., Sommersel, T., Xu, Z., and
Mantecon, J.: “Integrated Wellbore-Reservoir Dynamic Simulation: SPE paper
109162, presented at the 2007 SPE Asia Pacific Oil & Gas Conference and
Exhibition held in Jakarta, Indonesia, 30 Oct -1 Nov 2007.
16. Ballard, A.L., Adeyeye, D., Litvak, M., Wang, C.H., and Stein, M.H., Cecil, D. and
Dotson, B.D.: “Predicting Highly Unstable Tight Gas Well Performance”, SPE paper
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 169
96256, presented at the 2005 SPE annual Technology Conference and Exhibition
held in Dallas, Texas, U.S.A., 9-12 October 2005.
17. Kerem, M., Proot, M. and Oudeman, P.: “Analyzing Underperformance of Tortuous
Horizontal Wells: Validation with Field Data”, SPE paper 102678, presented at the
2006 SPE Annual Technical Conference and Exhibition held in San Antonio, Texas,
24-27 September 2006.
18. Meng, W., Zhang, J.J., and Brown, R.J.: “Modelling and Mitigation of Severe Riser
Slugging: A Case Study”, SPE paper 71564, presented at the 2001 SPE Annual
Technology Conference and Exhibition held in Louisiana, New Orleans, 30 Sep – 3
October 2001.
19. Ascencio-Cendejas, F., Reyes-Venegas, O. and Nass, M.A.: “Thermal Design of
Wells Producing Highly Viscous Oils in Offshore Fields in the Gulf of Mexico”, SPE
paper 103903, presented at the First International Oil Conference and Exhibition in
Mexico held in Cancun, 31 August – 2 September 2006.
20. Tang Y., and Huang, W.: “A Combined Well Completion and Flow Dynamic Modeling
for a Dual-Lateral Well Load-up Investigation”, paper IPTC 11332, at the International
Petroleum Technology Conference held in Dubai, U.A.E., 4–6 December 2007.
21. Leemhuis, A., Nennie, E., Belfroid, S., Alberts, G., Peters E., and Joosten, G.: “Gas
Conning Control for Smart Wells Using a Dymanic Coupled Well-Resevoir Simulator”,
SPE paper 112234, presented at the 2008 Intelligent Energy Conference and
Exhibition held in Amsterdam, 25-27 Feb 2008.
22. Duncan, G.J. and Beldring, B.: “A Novel Approach to Gas-Lift Design for 40,000 BPD
Subsea Producers”, SPE paper 77727, presented at the SPE Annual Technology
Conference and Exhibition held in San Antonio, Texas, 29 September – 2 October
2002.
23. Eikrem, G.O., Foss, B., Imsland, L., Hu, B. And Golan, M.: “Stabilization of GasLifted Wells”, Proceedings of the 15th IFAC World Congress on Automatic Control,
Barcelona, Spain, 2002
24. Gaspari, E.F., Oliveira, G.P., Monteiro, M.R., and Dourado, R.J.: “Evaluating
Transient Multiphase Model Performance for the Brazilian Offshore Environment”,
OTC paper 17956, presented 2006 Offshore Technology Conference held in
Houston, Texas, U.S.A., 1-4 May 2006.
25. Hu, B. and Golan, M.: “Gas-lift Instability Resulted Production Loss and Its Remedy
by Feedback Control: Dynamic Simulation Results”, SPE paper 84917, presented at
the SPE International Improved Oil Recovery Conference in Asia Pacific held in Kuala
Lumpur, Malaysia, 20-21 October 2003.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
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26. Hu, B. and Golan, M.: “Occurrence of Density Wave Instability in Gas-Lifted Wells”,
4th North American Conference on Multiphase Technology, Banff, Canada, 3-4 June
2004.
27. Mantecon, J.C., Andersen, I., Freeman, D. and Adams, M.: “Impact of Dynamic
Simulation on Establishing Watercut Limits for Well Kick-off”, SPE paper 88543,
presented at the SPE Asia Pacific Oil and Gas Conference and Exhibition held in
Perth, Australia, 18-20 October 2004.
28. Øverland, A.M. and Ramstad, H.J.: “Yme Marginal Field, 12 Km Subsea Gas-Lift
Experience”, SPE paper 71539, presented at the SPE Annual Technology
Conference and Exhibition held in New Orleans, U.S.A., 30 September – 3 October
2001.
29. Song, S., and Peoples, K.: “Impacts Of Transient Analysis on Kuito Production
Operations”, OTC paper 15186, presented 2003 Offshore Technology Conference
held in Houston, Texas, U.S.A., 5-8 May 2003.
30. Tang, Y., Schmidt, Z., Blais, R.N., Doty, D.R.: “Transient Dynamic Characteristics of
the Gas-Lift Unloading Process”, SPE Journal, (Sep. 1999), 268-278.
31. Tang, Y.: “A New Method of Plunger Lift Dynamic Analysis and Optimal Design for
Gas Well Deliquification”, paper SPE 116764, presented at the 2008 SPE Annual
Technical Conference and Exhibition held in Denver, Colorado, U.S.A., 21-24
September 2008
32. Veeken, K., Hu, B., and Schiferli, W.: “Multiphase Flow Modelling of Liquid Loading”,
presented at the Gas Well Deliquification Workshop, Denver, Colorado, 23-26
February 2009.
33. Veeken, K., Hu, B., and Schiferli, W.: “Transient Multiphase Flow Modeling of Gas
Well Liquid Loading”, paper SPE 123357, presented at the 2009 SPE Annual
Offshore Europe Oil & Gas Conference and Exhibition held in Aberdeen, U.K., 8–11
September 2009.
34. Tang Y., Wolff, M., Condon, P., and Ogden, K.: “A Dynamic Wellbore Modeling for
Sinusoidal Horizontal Well Performance With High Water Cut”, paper SPE 109262,
presented at the 2007 SPE Annual Technical Conference and Exhibition held in
Anaheim, California, U.S.A., 11–14 November 2007.
35. Noonan, S.G., Kendrick, M.A., Matthews, P.N., Sebastiao, N., Ayling, I. and Wilson,
B.L.: “Impact of Transient Flow Conditions on Electric Submersible Pumps in
Sinusoidal Well Profiles: A Case Study”, SPE paper 84234, presented at the SPE
Annual Technical Conference and Exhibition held in Denver, Colorado, U.S.A., 5-8
October 2003.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
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36. Barrett, N. and King, D.: “Oil/Water Slugging of Horizontal Wells – Symptom, Cause
and Design”, SPE paper 49160, presented at the 1998 SPE Annual Technical
Conference and Exhibition held in New Orleans, Louisiana, 27-30 September 1998.
37. Sisco, R., Kirby, M.: “Chemical Distribution During Normal and Transient Conditions”,
IPTC paper 10706, presented at the International Petroleum Technology Conference
held in Doha, Qatar, 21-23 Nov 2005.
38. Harun, A.F., Krawietz, T.E. and Erdogmus, M.: “Hydrate Remediation in Deepwater
Gulf of Mexico Dry-Tree Wells: Lessons Learned”, OTC paper 17814, presented at
the 2006 Offshore Technology Conference held in Houston, Texas, U.S.A., 1-4 May
2006.
39. Harun, A.F., Krawietz, T.E. and Erdogmus, M.: “Transient Simulation Assist Hydrate
Remediation Efforts in Deepwater Gulf of Mexico Dry-Tree Wells”, SPE paper
100750, presented at the 2006 SPE Asia Pacific Oil & Gas Conference and Exhibition
held in Adelaide, Australia, 11-13 September 2006.
40. Lunde, G.G., Vannes, K., McClimans, O.T., Burns, C., and Wittmeyer, K.: “Advanced
Flow Assurance System for The Ormen Lange Subsea Gas Development”, OTC
paper 20084, presented at the 2009 Offshore Technology Conference held in
Houston, Texas, U.S.A., 4-7 May 2009.
41. Teng, D., Maloney, B. and Mantecon, J.C.: “Well Testing by Design: Transient
Modelling for Predicting Behaviour in Extreme Wells”, SPE paper 101872, presented
at the 2006 SPE Asia Pacific Oil & Gas Conference and Exhibition held in Adelaide,
Australia, 11-13 September 2006.
42. Harun, A.F.:”Planning and Executing Lost Distance Subsea Tie-back Oil Well
Testing”, IPTC paper 1193, presented at 2007 International Petroleum Technology
Conference, Dubai, 4-6 December, 2007.
43. Mantecon, J.C., and Hollams, R.R.F.:”Use of Dynamic Simulation to Refine Well
Testing Procedures and Optimize The Data Required for Deconvolution Techniques”.
OTC paper 19767, presented at the 2009 Offshore Technology Conference held in
Houston, Texas, U.S.A., 4-7 May 2009.
44. Hu, B., Uv, E.H., and Xu, Z.G.:”Modelling and Simulation of Co-flow of Reservoir
Fluids and Drilling/Completion Mud in The Ultra-Long Multilateral Horizontal
Wellbores”, presented at the 14th International Conference Multiphase Production
Technology, Cannes, France, 17-19 June 2009.
45. Rygg, O.R., Friedemann, J.D. and Nossen, Jan: “Advanced Well Flow Model Used
for Production, Drilling and Well Control Applications”, 1996 IADC Well Control
Conference for Europe, Aberdeen, 22-24 May, 1996.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 172
46. Rygg, O.R.: “The Necessity of Modelling in Contingency Planning and Emergency
Well Control Response”, 2005 IADC International Well Control Conference &
Exhibition, Singapore, 8-9 November, 2005.
47. Harun, A.F., Fung, G. and Erdogmus, M.: “Experience in AA-LDHI Usage for a
Deepwater Gulf of Mexico Dry-Tree Oil Well: Pushing the Technology Limit”, SPE
paper 100796, presented at the 2006 SPE Asia Pacific Oil & Gas Conference and
Exhibition held in Adelaide, Australia, 11-13 September 2006.
48. Dalsom, M., Halvorsen, E. and Slupphaug, O.: ”Active Feedback Control of Unstable
Wells at the Brage Field”, SPE paper 77650, presented at the SPE Annual
Technology Conference and Exhibition held in San Antonio, Texas, 29 September – 2
October 2002.
49. Jansen, B., Dalsmo, M., Nøkleberg, L., Havre, K., Kristiansen, V. and Lemetayer, P.:
”Automatic Control of Unstable Gas-Lifted Wells”, SPE paper 56832, presented at the
1999 SPE Annual Technology Conference and Exhibition held in Houston, Texas, 36 October 1999.
50. Krogh, E., Mjaaland, S., Sletfjerding, E.: “Dynamic Flow Simulation of Well Clean-up
Operation at the Asgard Field”, SPE paper 124653, presented at the 2009 SPE
Annual Technology Conference and Exhibition held in New Orleans, USA, 4-7
October 2009.
51. Davis, S., Boxall, J., Koh, C., Sloan, E., Hemmingsen, P., Kinnari, K., and Xu, G.:
”Predicting Hydrate Plug Formation in a Subsea Tieback”, SPE paper 115763,
presented at the 2008 SPE Annual Technology Conference and Exhibition held in
Denver, USA, 21-24 September 2008.
52. Salman, Y., Wittfeld, C., Lee, A., Yick, C., and Derkinderen, W.: “Use of Dynamic
Simulation To Assist Commissioning and Operating a 65-Km Subsea-Tieback Gas-lift
System”, SPE paper 121187, published in the SPE Production & Operations
magazine, November 2009.
53. Acuna, H.G., Schmidt, Z.X., Doty, D.R. “Modelling of Gas Rates Through 1”,
Nitrogen-Charged Gas-Lift Valves”, SPE Annual Technology Conference and
Exhibition held in Washington D.C., USA, 4-7 October 1992.
54. Decker, K. “Gas-Lift Valve Performance Testing,” SPE 21636, SPE Production
Operations Symposium, 21-23 March 1993, Oklahoma City, Oklahoma.
API RP 19G11
Dynamic Simulation of Gas-Lift Wells and Systems
Page 173
Informative References
API RP 11V5 Operation, Maintenance and Troubleshooting of Gas Lift Installations
API RP 11V6 Design of Continuous Flow Gas Lift Installations Using Injection Pressure
Operated Valves
API RP 11V8 Gas Lift Systems Design and Performance Predictions
API RP 19G9 Operation, Maintenance and Troubleshooting and Design/Re-Design of Dual
Gas Lift Systems
API RP 11V10 Design of Intermittent and Chamber Gas Lift Wells and Systems
ISO 17078-1 Petroleum and natural gas industries -- Drilling and production equipment -Part 1: Side-pocket mandrels
ISO 17078-2 Petroleum and natural gas industries -- Drilling and production equipment -Part 2: Flow-control devices for side-pocket mandrels
ISO 17078-3 Petroleum and natural gas industries -- Drilling and production equipment -Part 3: Running tools, pulling tools and kick-over tools and latches for sidepocket mandrels
ISO 17078-4 Petroleum and natural gas industries -- Drilling and production equipment -Part 4: Practices for side pocket mandrels and related equipment