Gullfaks Field Development Plan
by
Muhammad Nazrin Bin Sohaili
Hing Chai Shing
Raihana Bt Radzlan
Lai Yen Hua
Ilangkabilan Manaharan
Nikita Mazurenko
Mohammad Sazwan Ismail
Sarah Adiba Mohammed Yussof
Muhammad Hizbullah Mawardi
Final Report submitted in partial fulfilment of
the requirements for the
Bachelor of Engineering (Hons)
(Petroleum Engineering)
MAY 2013
Universiti Teknologi PETRONAS
Bandar Seri Iskandar
31750 Tronoh
Perak Darul Ridzuan
i
Gullfaks Field Development Plan
by
Muhammad Nazrin Bin Sohaili
Hing Chai Shing
Raihana Bt Radzlan
Lai Yen Hua
Ilangkabilan Manaharan
Nikita Mazurenko
Mohammad Sazwan Ismail
Sarah Adiba Mohammed Yussof
Muhammad Hizbullah Mawardi
Final Report submitted in partial fulfilment of
the requirements for the
Bachelor of Engineering (Hons)
(Petroleum Engineering)
Approved by,
_____________________
(AP. Dr. Chow Weng Sum)
UNIVERSITI TEKNOLOGI PETRONAS
TRONOH, PERAK
ii
May 2013
CERTIFICATION OF ORIGINALITY
This is to certify that we are responsible for the work submitted in this project, that the
original work is our own except as specified in the references and acknowledgements, and
that the original work contained herein have not been undertaken or done by unspecified
sources or persons.
_________________________________
______________________________
MUHAMMAD NAZRIN SOHAILI
NIKITA MAZURENKO
_________________________________
______________________________
HING CHAI SHING
MOHAMMAD SAZWAN ISMAIL
_________________________________
______________________________
RAIHANA RADZLAN
LAI YEN HUA
_________________________________
______________________________
SARAH ADIBA MOHAMMED
MUHAMMAD HIZBULLAH
YUSSOF
MAWARDI
iii
_________________________________
ILANGKABILAN MANAHARAN
iv
ACKNOWLEDGEMENT
First of all, we would like to express our joyful and gratitude for being able to complete
this report of Field Development Project as part of the final semester requirement. Special
thanks to our beloved FDP Supervisors AP. Dr. Chow Weng Sum, AP. Dr. Muhannad
Thalib Shuker, and Dr. Sonny Irawan for their kind guidance and assistance towards
completing this report. We have being able to learn and acquire so much knowledge and
skills which related to this project. This might be useful for our future career survival and
enhancement as a professional petroleum engineer.
We also would like to express our deepest appreciation to our FDP Coordinator Ms. Raja
Rajeshwari Suppiah for her precious encouragement, tolerance and support from the
beginning until the final stage of this project. Nevertheless, we would like to thank
Schlumberger for providing us the Petrel 2012 software in order to complete and workout
our project.
Finally, heartiest appreciation and congratulation are triumphed to all group members for
their hard work, contribution and cooperation as a team whilst completing this report. Too,
not to forget to extend our greatest gratitude to other parties and colleagues who involve
directly or indirectly in completing this report.
v
EXECUTIVE SUMMARY
The objective of this project is to develop the plan for the management of the
natural resources in the Gullfaks field. The aim of the Field Development Project (FDP)
is to carry out a technical study of the proposed development utilizing the latest technology
available that focus on geology, petrophysics and reservoir. The scope of study for
Gullfaks FDP revolves around the plan to produce the hydrocarbon commercially, by
identifying the cumulative reserve and recoverable reserves that will ease the management
in making decision of the proposed development of Gullfaks Field.
Thus, the methodology of this FDP has been further broken down into 3 phases
namely (1) Geology and Geophysics and Petrophysics, (2) as well as (3) Reservoir
Engineering. For Phase 1, the depositional environment, the geological setting and
reservoir geology have been studied and the stratigraphy shows that Gullfaks Field
consists of clastic sediments of dominantly shaly sand deposition. The estimated Stock
Tank Oil Initially in Place (STOIIP) of Gullfaks Field is 420 x 10-6 SM3 while the
estimated Gas Initially in Place (GIIP) is 495 x 10-6 SM3. Simulation modeling was carried
out thoroughly using PETREL software. Reservoir simulation concludes the best strategy
to develop the field is via natural depletion.
Interpretation of the cross section also shows that there is a general erosional
unconformity. Volumetric estimation has been done by using the PETREL. Several risks
and uncertainties have also been discussed as these uncertainties posted a great challenge
for Gullfaks Field development option. The fluid contacts have been identified based on
MDT and log plot and several lithology crossplots have been plotted to further justify that
this is a shaly sand formation.
vi
In summary, through the reservoir simulation studies done, it is proposed that the
optimum development of Gullfaks field involves 5 producers well and 2 injectors well for
pressure maintenance of the aquifer. It is also proposed that the water injection to be
started right from the start of production for maximum recovery. Based on the optimum
dynamic model, the recovery for 5 years and 10 years forecast are 60844700 sm3 and
92995192 sm3 respectively. The EUR for 5 years and 10 years production are 14.5% and
22.1% respectively.
vii
Table of Contents
List of Figures .................................................................................................................... 1
List of Table ....................................................................................................................... 4
INTRODUCTION ............................................................................................................. 5
1.1. Background of project ............................................................................................. 5
1.2. Gullfaks Field .......................................................................................................... 6
1.3. Exploration History ................................................................................................. 8
1.4. Problem statement ................................................................................................. 10
1.5. Objectives .............................................................................................................. 10
1.6. Scope of work ....................................................................................................... 10
1.7. Gantt Chart ............................................................................................................ 11
1.8. Project Team ......................................................................................................... 12
DATA INVENTORY AND QUALITY CONTROL ...................................................... 14
2.1. Introduction ........................................................................................................... 14
2.2 Workflow ............................................................................................................... 14
2.2.1 Data Acquisition and Sorting .......................................................................... 14
2.2.2 Data Checklist ................................................................................................. 15
2.2.3 Data Digitizing ................................................................................................ 16
2.2.4 Data Quality Check ......................................................................................... 17
GEOLOGY & GEOPHYSICS ......................................................................................... 18
3.1. Geology Settings ................................................................................................... 18
3.1.1. Regional setting.............................................................................................. 20
3.1.2. Depositional Environment ............................................................................. 21
3.1.3. Structural setting ............................................................................................ 23
viii
3.2. Modeling Process .................................................................................................. 25
3.2.1 Make surface from Bitmap/Image .................................................................. 25
3.2.2 Make simple grid............................................................................................. 26
3.2.3 Import exploration wells ................................................................................. 26
3.2.4 Import well logs .............................................................................................. 26
3.2.5 Import well tops .............................................................................................. 26
3.2.6 Make zones: Create Isochores ......................................................................... 26
3.2.7 Make zones...................................................................................................... 27
3.2.8 Make layering.................................................................................................. 27
3.2.9 Property modelling .......................................................................................... 28
3.3. Modeling Properties .............................................................................................. 30
3.4. Modeling Results .................................................................................................. 46
3.4.1. Volumetric Result .......................................................................................... 46
3.5. Petrophysics .......................................................................................................... 49
3.5.1. Lithology Study.............................................................................................. 49
3.5.2. Log Interpretation........................................................................................... 53
3.5.3. Well Log Correlation ..................................................................................... 57
3.5.4. Zone of Interest .............................................................................................. 63
3.5.5 Pressure Plot .................................................................................................... 69
3.5.6 Volume of Shale Calculation .......................................................................... 71
RESERVOIR ENGINEERING ....................................................................................... 78
4.1 Reservoir Data ........................................................................................................ 78
4.1.1. Summary of Results ....................................................................................... 78
4.1.2. Separator Sample ........................................................................................... 79
ix
4.1.3. Compositional Analysis of Separator Oil, Separator Gas Samples and
Calculated Wellstream Composition........................................................................ 79
4.1.4. Constant Composition Expansion, CCE Experiments ................................... 81
4.1.5. Differential Liberation, DL Experiments ....................................................... 82
4.1.6 Separators Experiments ................................................................................... 83
4.1.7 Swelling Test (CO2) ....................................................................................... 83
4.1.8 Swelling Test (N2) .......................................................................................... 84
4.1.9 Well / Sampling Information .......................................................................... 84
4.2 Well Test Data........................................................................................................ 86
4.3 Reservoir Simulation.............................................................................................. 89
4.4.1 Objectives of Simulation Study ...................................................................... 89
4.4.2 Reservoir Model Set Up .................................................................................. 89
4.4.3 Base Case Model ............................................................................................. 94
4.4.4 Reservoir Development Planning ................................................................... 95
4.4.5 Sensitivity Analysis....................................................................................... 100
4.4.6 Optimum Model ............................................................................................ 103
4.4.7 Production Forecast....................................................................................... 106
4.4.8 Enhanced Oil Recovery (EOR) Considerations ............................................ 107
4.5 Reservoir Management ........................................................................................ 112
4.5.1 Reservoir Management Challenges and Strategies ....................................... 113
CONCLUSION .............................................................................................................. 116
REFERENCES............................................................................................................... 117
x
List of Figures
Figure 1: Location of Gullfaks field................................................................................... 5
Figure 2: Gullfaks Field Location. (Hesjedal, 2013) ......................................................... 6
Figure 3: Gullfaks Field Location ...................................................................................... 7
Figure 4: The detailed map of the Gullfaks exploration wells and the fault blocks involved.
Modified after Erichsen et al. (1987). ................................................................................ 9
Figure 5: Organization Chart of Group ............................................................................ 13
Figure 6: Workflow for data processing, analysis and integration .................................. 14
Figure 7: Composite log display of Gullfaks reservoir (Hesjedal, 2013) ........................ 19
Figure 8: Regional map of the Gullfaks-Statfjord area, and a profile .............................. 20
Figure 9: Gamma ray log of well B8 to interpret the depositional environment. ............ 22
Figure 10: The areal distribution of the domino system, the horst complex and the
accommodation zone on the top Statfjord fault map. ...................................................... 24
Figure 11: Workflow of static modelling ......................................................................... 25
Figure 12: Chronology of the surface making from image file ....................................... 26
Figure 13: Porosity illustration......................................................................................... 30
Figure 14: Fluid flow through porous media ................................................................... 31
Figure 15: Archimedes’ principle of mass displacement in a liquid (buoyancy) ............ 33
Figure 16: Bulk Volume .................................................................................................. 34
Figure 17: Pore Volume ................................................................................................... 36
Figure 18: Net Volume..................................................................................................... 37
Figure 19: STOIIP in 3D simulation model ..................................................................... 38
Figure 20: GIIP ................................................................................................................ 40
Figure 21: GIIP 3D .......................................................................................................... 40
Figure 22: GOC, GWC, OWC ......................................................................................... 41
Figure 23: Top view of the model .................................................................................... 42
Figure 24: Side view of the reservoir model .................................................................... 43
Figure 25: Porosity Model ............................................................................................... 44
Figure 26: Permeability Model ........................................................................................ 45
Figure 27: Wells correlated in Northeast-Southwest direction. ....................................... 57
1
Figure 28: Well tops correlations using Gamma Ray logs from well B8, B9, C5 and C6.
.......................................................................................................................................... 58
Figure 29: Wells correlated in North-South direction ..................................................... 59
Figure 30: Well tops correlations using Gamma Ray logs from well A10, A15, A16, B8
and B9. ............................................................................................................................. 60
Figure 31: Wells correlated in Northeast-Southwest direction. ....................................... 61
Figure 32: Well tops correlations using Gamma Ray logs from well C2, C3, C4, C5 and
C6. .................................................................................................................................... 62
Figure 33: The Oil Zone located above Base Cretaceous layer for C6 Well. .................. 63
Figure 34: The Oil Zone located above Base Cretaceous layer for C5 Well. .................. 64
Figure 35: The Oil Zone located within investigated layers for B8 Well. ....................... 65
Figure 36: The Oil Zone located within investigated layers for B9 Well. ....................... 65
Figure 37: Pressure plot for well A10 .............................................................................. 69
Figure 38: Pressure plot for well B9. ............................................................................... 70
Figure 39: Identification of shale formation using GR log .............................................. 71
Figure 40: Oil Density...................................................................................................... 84
Figure 41: Oil Formation Volume Factor ........................................................................ 85
Figure 42: Multi rate well ................................................................................................ 88
Figure 43: Single rate well ............................................................................................... 88
Figure 44: Workflow of dynamic modelling ................................................................... 90
Figure 45: Format for creating observed data file ............................................................ 92
Figure 46: Base case model of dynamic modelling ......................................................... 94
Figure 47: Graph of Field Oil Production Cumulative .................................................... 96
Figure 48: Chart of Cumulative Oil Production for Individual wells .............................. 96
Figure 49: Creaming curve............................................................................................... 97
Figure 50: Water Aquifer in Gullfaks field ...................................................................... 98
Figure 51: Water Aquifer in Gullfaks field ...................................................................... 99
Figure 52 Comparison of Field Oil Production Cumulative between Base Case and Year
Two ................................................................................................................................ 101
Figure 53 Comparison of Field Oil Production Cumulative between Waterflood at January
2014 and July 2014 ........................................................................................................ 102
2
Figure 54: Production forecast for well A10.................................................................. 103
Figure 55: Production forecast for well A15.................................................................. 104
Figure 56: Production forecast for well A16.................................................................. 104
Figure 57: Production forecast for well B8 .................................................................... 105
Figure 58: Production forecast for well B9 .................................................................... 105
Figure 59: Field production forecast for 5 years ............................................................ 106
Figure 60: CO2 injection (left) and EOR production well (right). ................................ 108
Figure 61: Assumption of future oil prices .................................................................... 108
3
List of Table
Table 1: The work schedule of Gullfaks Field Development Project ............................. 11
Table 2: Data Checklist .................................................................................................... 15
Table 3: Type of data and description .............................................................................. 16
Table 4: Summary of the horizons and zones that has been created ................................ 27
Table 5: Permeability value and its classification ............................................................ 32
Table 6: Interval depths and properties ............................................................................ 46
Table 7: Oil and gas interval result .................................................................................. 47
Table 8: Details result of each zone ................................................................................. 48
Table 9: Volume of Shale for Well C6 ............................................................................ 73
Table 10: Volume of Shale for Well C5 .......................................................................... 74
Table 11: Volume of Shale for Well B9 .......................................................................... 75
Table 12: Volume of Shale for Well B8 .......................................................................... 76
Table 13: Net Pay for Well A16 ...................................................................................... 77
Table 14: Compositional analysis of the separator oil and gas samples .......................... 80
Table 15: Summary of CCE Test results.......................................................................... 81
Table 16: Reservoir conditions ........................................................................................ 86
Table 17: Perforation depth data for three of the wells .................................................... 86
Table 18: Formation Characteristic .................................................................................. 87
Table 19: Well Characteristics ......................................................................................... 87
Table 20: Optimization of Number of Wells per Reservoir ............................................. 97
Table 21: Sensitivity analysis for water injection ............................................................ 99
Table 22: Expected Ultimate Recovery and recovery factor ......................................... 106
Table 23: Oil Gravity and Amount of Depth Needed .................................................... 109
Table 24: CO2- miscible flooding and Immiscible CO2 flooding .................................. 110
4
CHAPTER 1
INTRODUCTION
1.1. Background of project
Gullfaks Field is operated by Statoil and located in the North Sea of Norwegian sector.
The field is situated in block 34/10, approximately 175km Northwest of Bergen. The field
is situated in the central part of the East Shetland basin. Research made on the basin shows
that the field is located on the western flank of the Viking Graben, where it occupies the
eastern half of a 10-25km wide, NNE-SSW-trending fault block, called the Gullfaks fault.
This fault block is one of series of large (first order) fault blocks that are easily identified
on regional seismic lines across the North Sea.
Figure 1: Location of Gullfaks field
5
1.2. Gullfaks Field
In 1978, Block 34/10 of Gullfaks Field development license was awarded to Statoil
(operator), Norsk Hydro and Saga Petroleum. It is said that they’re the first fully
Norwegian joint venture corporation. The field is situated in the Norwegian Sector of the
North Sea, approximately 175km northwest of Bergen and covers an area of 55km2 which
occupies the eastern half of the 10-25km wide Gullfaks fault block (Fossen and
Hesthammer, 2000). Refer Figure 2 and Figure 3 below.
Figure 2: Gullfaks Field Location. (Hesjedal, 2013)
6
Figure 3: Gullfaks Field Location
7
1.3. Exploration History
According to (Tollefsen, Graue, & Svinddal, 1992), in total, there was 14 exploration
wells were drilled in Gullfaks Field. 160m oil column and water bearing encountered in
Brent Group and Cook and Statfjord formation, respectively by the first exploration well,
34/10-01 well. Then exploration well 34/10-03 managed to proven the oil-water contact
(OWC) in the Brent Group. Whereas well 34/10-04 to 34/10-06 confirms the OWC and
eventually appraised the western part of the field.
The eastern part of Gullfaks Field were utilizing the use of 3D seismic during exploration
and appraisal drilling. As a result of improved seismic method and data quality, the
exploration well 34/10-07 managed to discover a deeper hydrocarbon system in the Cook
formation. While a new oil system and a deep OWC was successfully proven through well
34/10-10 and well 34/10-11. The exploration phase ended in 1983. Refer Figure 4 for the
detailed map of the Gullfaks field.
8
Figure 4: The detailed map of the Gullfaks exploration wells and the fault blocks involved. Modified after
Erichsen et al. (1987).
9
1.4. Problem statement
Gullfaks Field is an oil and gas field which consists of three production platforms Gullfaks
A, Gullfaks B, and Gullfaks C. The field was discovered in 1979, in block 34/10, at water
depth of 135 meters. Due to time constraints, limited data and number of uncertainties, it
was a tough challenge to achieve the objective of the development. The FDP report covers
the following phases:

Geology and formation evaluation

Reservoir development plan
1.5. Objectives
The main objective of the Gullfaks Field FDP project is to develop a technical and
economics study of the proposed development using the latest technology available. Our
justification for the results and choice of steps involved will be based on producing a
reasonable and reliable FDP Report. Objectives in creating the best possible FDP will be
considering the following points:

Maximizing hydrocarbon production

Maximizing recoverable hydrocarbons
1.6. Scope of work
The general scope of works for the Gullfaks Field Development Project is:

To determine the Gross Rock volume, Net to Gross (NTG), porosity and saturation
distribution profile, types of fluids and their contacts, Stock Tank Oil Initially in
Place (STOIIP) and Gas Initially in Place (GIIP).

To develop the static model of Gullfaks Field.

To prepare a dynamic model and perform simulation to achieve highest recovery
factor (RF) and economic return of the field.
10
1.7. Gantt Chart
Table 1: The work schedule of Gullfaks Field Development Project
Task Name
W4
W5
FDP Kickoff and Data Handover
Phase 1: G&G and Petrophysics
Phase 2: Reservoir Engineering
Report Submission
Oral Presentation
11
W6
W7
W8
W9
W10 W11
W12 W13 W14
1.8. Project Team
Group 2 consist of 9 members who task assigned to develop and come out with a final report
for Field Development Plan of Gullfaks Field.
Below are the full name of the team members and the organization structure is shown in
Figure 5
1. Muhammad Nazrin Bin Sohaili (Team Leader)
2. Hing Chai Shing
3. Raihana Bt Radzlan
4. Lai Yen Hua
5. Ilangkabilan Manaharan
6. Nikita Mazurenko
7. Mohammad Sazwan Ismail
8. Sarah Adiba Mohammed Yussof
9. Muhammad Hizbullah Mawardi
A total of 10 weeks were allocated for the project. The project was initiated in 14th June 2013
by data distribution by FDP Coordinator and the team managed to complete the FDP by week
13 as shown in the work schedule in Table 1.
12
Team Leader
(Muhd Nazrin)
Geology &
Geophysics
Petrophysics
Raihana (leader)
Sarah
Kabilan
Nazrin
Reservoir
Engineering
Sarah (leader)
Raihana
Nazrin
Hin Chai Shing
Lai Yen Hua
Figure 5: Organization Chart of Group
13
Hin Chai Shing
(leader)
Kabilan
Lai Yen Hua
Hizbullah
Nikita
Sazwan
CHAPTER 2
DATA INVENTORY AND QUALITY CONTROL
2.1. Introduction
A systematic data inventory was formed to ensure all the resources and information are
fully utilized and maximized in each of the development phases. This is very important
for considerations of the uncertainties and risk that will be undertaken based on the data
that is available.
2.2 Workflow
Data Acquisition and Sorting
Data Checklist and Inventory Setup
Data Digitizing
Data Quality Check
Figure 6: Workflow for data processing, analysis and integration
2.2.1 Data Acquisition and Sorting
The data provided came from the exploration and appraisal wells of Gullfaks Field data
were sorted according to the wells and sand units for checklist and inventory setup. Raw
and processed data were separated to run quality check for use in further interpretation
and processing
14
2.2.2 Data Checklist
Table 2: Data Checklist
A-10 A-15 A-16 B-8
B-9
C-2
C-3
C-4
C-5
C-6
Seismic Data
Well Log Data
/
/
/
/
/
/
/
/
/
/
Well Deviation Survey
/
/
/
/
/
/
/
/
/
/
Surface Contour Map
/
/
/
/
/
/
/
/
/
/
Core Analysis
/
PVT Fluid Data
/
/
/
/
/
/
/
/
/
/
MDT/RFT Data
/
/
/
/
/
/
/
/
/
/
Well Test Data
/
/
/
/
/
/
/
/
/
/
Well Drilling Data
During data acquisition, seismic data was not provided. This will be one the cause of uncertainties especially in the Geology phase as
seismic control is important in interpreting important structural features for instance fault, unconformity, and anticline features
15
The data obtained from the acquisition phase are as the following:
Table 3: Type of data and description
Type of data
Well Log Data
Description
Gamma Ray, SP Log, Neutron Log, Neutron
Density Log, Resistivity Log, Caliper Log
Deviation Survey
Surface
Well Trajectories, Well Coordinates
Contour Well Marker, Well Position, Sand Area and
Map
Thickness, Contour Lines
Core Data (Special Horizontal Porosity and Permeability, Capillary
Core
Analysis Pressure (Mercury Capillary Injection Pressure),
SCAL)
Formation Resistivity Measurement, Relative
Permeability, Rock Compressibility
PVT Fluid Studies
Constant Compaction Experiment, Differential
Liberation Experiment, Multi-stage Separator Test,
Gas Chromatography
Modular
Dynamic Fluid Pressure Gradient, Fluid Contacts
Tester/Repeat
Formation Test Data
Well Test Data
Zonal Permeability, Boundary/ Drive Mechanism
Identification, Hydrocarbon Fluid Contacts, Skin
Factor
Well Drilling Data
Rock Cuttings, Mud Program, Casing Setup, Drill
Stem Test, Well Completion Diagram
2.2.3 Data Digitizing
The data provided are either in written report and figures or images. These data are digitized
and extracted as part of the data inventory so the values or information can be used as input
16
in the engineering software involved or arranged in another desired format. Data digitized
contributes a big boost in further reducing the uncertainties as well as constructing the model
that best describe Gullfaks Field reservoir by taking into consideration all the data that were
available.
2.2.4 Data Quality Check
Data accuracy and reliability are important in ensuring the interpretations are done
correctly, as inaccurate or wrong data could possibly jeopardize the whole development
planning. The goal of quality assurance and quality control (QA/QC) is to identify and
implement sampling and analytical methodologies which reduces the error of analytical
data.
There are two methods used for Gullfaks field data quality control:
a) Data Verification
Verification ensures that the requirements stated in the planned data acquisition are
implemented as prescribed. Problems that occur during implementation should be
reported to show the degree of errors related to the data being obtained. Corrective actions
undertaken should be reviewed for adequacy and appropriateness and documented in
response to the data acquisition. These assessments may include but are not limited to
inspections, QC checks, surveillance, technical reviews, performance evaluations, and
audits. To ensure that conditions requiring corrective actions are identified and addressed
promptly, data verification activities should be initiated as part of data collection.
b) Data Validation
Validation activities ensure that the results of data collection fulfils the requirement
needed. The data once validated, the data usability is checked to ensure the quality of the
data produced is good for use. Corrective actions may improve data quality and reduce
uncertainty
17
CHAPTER 3
GEOLOGY & GEOPHYSICS
3.1. Geology Settings
The reservoir units are sandstones of early and middle Jurassic age, around 2000m sub
sea and measure several hundred meters thick. Reservoir quality is generally very high,
with permeability ranging from few tens of mD to several Darcys depending on layer and
location. Figure below shows a cross section indicating the quality and variability of
the reservoirs.
The reservoirs are over pressured, with an initial pressure of 310 bar at datum depth of
1850 m below mean sea level, and a temperature of 70 degrees C. The oil is
undersaturated, with a saturation pressure of approximately 245 bar, depending on
formation depth and location. The GOR ranges between 90 and 180, with stock tank oil
gravity around 860 kg/m3. Structurally, the field is very complex and can be divided into
three regions: the so-called 'Domino Area' with rotated fault blocks in the west, and a
Horst area in the east; in between is a complex 'Adaptation Zone', characterized by folding
structures. The north-south faults that divide up the field have thrown up to 300 meters.
In the western part the faults slope typically around 28 degrees downward to the east,
whereas in the eastern horst they slope 60-65 degrees downwards to the west. The field is
further cut by smaller faults, with throws of zero to few tens of meters, both in the
dominant north-south as well as east-west direction. Many of these lesser faults have
slopes of 50-80 degrees. This results in complex reservoir communication and drainage
patterns, and is a major challenge in optimally placing wells in the reservoir.
18
Figure 7: Composite log display of Gullfaks reservoir (Hesjedal, 2013)
19
3.1.1. Regional setting
The Gullfaks Field is located on the western flank of the Viking Graben Figure 8, where
it occupies the eastern half of a 10-25 km wide, NNE-SSW-trending fault block named
the Gullfaks fault block in this article.
Figure 8: Regional map of the Gullfaks-Statfjord area, and a profile
20
The Gullfaks fault block is one of a series of large (first-order) fault blocks that are easily
identified on regional seismic lines across the North Sea. The general trend of these larger
faults in the northern North Sea is N-S to NNE-SSW, reflecting the overall E-W extension
across the rift. The extensional history of the North Sea dates back to the Devonian
extensional phase shortly after the Caledonian collision. Onshore kinematic studies
support the idea of plate-scale divergent movements in the Devonian. The main
subsequent rifting phases are commonly referred to as the Permo-Triassic and late Jurassic
phases. Whereas the extension involved in the Permo- Triassic event is significant, the
late Jurassic deformation of the Jurassic sequence is more obvious on commercial seismic
lines, and best known from well data. The pre- sent study is concerned with deformation
of Late Triassic-Jurassic layers in the Gullfaks area, and thus with the late Jurassic
extension phase.
3.1.2. Depositional Environment
There are three main reservoirs in the Gullfaks field, namely the Statfjord
Formation, Cook Formation and the Brent Group. This project focused on Brent Group
which is divided into several major stratigraphic units including the Tarbert, Ness and
Etive formations. The Middle Jurassic deposits of the Brent Group are represented by the
deltaic sediments with deposition strongly controlled by regressive and transgressive
cycles. The formation occurred during the late phase of post-rift subsidence following the
Late Permian/Early Triassic rifting. This petroleum system is a sequence of sandstones,
siltstones, shales and coals. The Brent Group comprised a major regressive (Rannoch,
Etive and Ness Formations) and transgressive (Ness and Tarbert Formations) clastic
wedge. The following figure shows the Gamma Ray log of well B8.
21
Figure 9: Gamma ray log of well B8 to interpret the depositional environment.
From the gamma ray response, Figure 9, the depositional environment of Tarbert
formation is interpreted as a marginal marine, reworked delta plain deposits in the onset
of marine transgression. The boundary between Tarbert and Ness formations was
distinguished using the marine transgressive event that separates these two different
phases of delta building. The Tarbert formation is interpreted as purely controlled by the
marine environment. The lithology of the formation varies from shale, siltstones and coal
beds to medium-to coarse-gained sands in which calcite cementation is found.
22
The Ness Formation is interpreted as a floodplain deposit with isolated fluvial
sandstone which suggests a delta plain. The boundary between Etive and Ness Formation
is assigned by the first occurrence of a coal bed above the clean sands. The Ness Formation
can be divided into two parts, which are Upper Ness and Lower Ness with relative sea
level change as the main criterion of division. The lower unit interpreted as low-sinuosity
distributary channels consisting of interbedded coals, mudstones, and sandstones,
occasionally with thick sandstone channel deposits. Additionally several coarseningupward sequences of sandstone with good reservoir quality propose the crevasse splay,
crevasse channels and overbank flooding. The Upper Ness unit might be described as
domination of silistone/claystone and coal deposits with some lacustrine deposits.
The Etive formation is interpreted as a barrier bar complex. On the basis of lowangle large scale cross-stratification, grain size, heavy mineral concentration and parallel
lamination a high energy beach environment was proposed. The formation consisting
primarily of medium-to coarse-grained sandstones with lower part reflecting upwardfining sequences that may represent channel fill deposits. These sequences are interpreted
as tidal inlets in the barrier bar system.
3.1.3. Structural setting
The Gullfaks Field is characterized by two structurally contrasting compartments: a
western domino system with typical domino-style fault block geometry, and a deeply
eroded eastern horst complex of elevated sub-horizontal layers and steep faults. These two
regions are significantly different as far as structural development is concerned, and will
be treated separately below. Between the western and eastern regions is a transitional
accommodation zone (graben system) which is identified as a modified fold structure. The
distribution of these structurally different areas is shown in figure below, which displays
an east- stepping occurrence of the accommodation zone as one goes from the north to the
south. The stepping occurs across E-W transfer faults with high displacement gradients
(rapidly decreasing displacement to the west). These E-W faults thus separate domains of
contrasting dips. Refer Figure 10
23
Figure 10: The areal distribution of the domino system, the horst complex
and the accommodation zone on the top Statfjord fault map.
24
3.2. Modeling Process
Make surface from Bitmap/Image
Make a simple grid
Import exploration wells
Import well logs
Import well tops
Make zone : Create Isochores
Make zones
Make Layering
Property modelling
Figure 11: Workflow of static modelling
3.2.1 Make surface from Bitmap/Image
The first step in petrel workflow is to import the image file. Then, a coordinate is set and
the origin for x.y and z axis is selected in order to have a right position of the model. The
imported image is then edited by using the polygon to eliminate out the outer white surface
area (original image file). In order to have a better view of the surface, the colour and the
surface is exaggerated in z-direction. Last but not least, the z-elevation is adjusted so that
the surface stay in the right position after edited. The steps are then repeated for top tarbert,
top ness and top etive.
25
Figure 12: Chronology of the surface making from image file
[Image file - Polygon - Surface in 3D view - Colour adjusting]
3.2.2 Make simple grid
In this stage, all the surfaces are inserted and the 40m grid increment is set in x and y axis
for all the surface geometry
3.2.3 Import exploration wells
All well data is imported and placed under a new well folder in the input pane. True
Vertical Depth (TVD) is set as the scale.
3.2.4 Import well logs
The imported well log data is then matched with the respective well name. The facies and
fluvial template also are changed to ensure that the model created have the same
characteristic required.
3.2.5 Import well tops
Those well tops data are imported and placed under the new folder of well tops in the
input pane.
3.2.6 Make zones: Create Isochores
To create isochore points, for instance, the Top Tarbert well top (from well tops folder) is
highlighted first and then the Base Cretaceous (from stratigraphy folder) is clicked. As a
result, a new point data is generated at the input pane. Those points created can be
displayed in 3D window and the size can be adjusted for better view. The elevation and
thickness deltas also are checked and adjusted to ensure that it is a good quality results.
This can be done by viewing the statistic tabs under the Z and thickness attributes. After
that, a thickness map is formed from the point data. To create a thickness map, a thickness
26
attributes is selected rather than Z attribute. Hence, the thickness map with the isochore
points can be displayed and observed in the 3D window.
3.2.7 Make zones
This is the process of inserting geological zones in the stratigraphic intervals above, in
between and below the horizons that has been created in the 3D Grid model. The zones
are typically created based on isochore grids, constant values or built proportionally from
existing horizons. Well tops also is used for well adjustment of the horizons that will be
created. [Base CretaceousTop Tarbert Top Ness Top Etive]
Table 4: Summary of the horizons and zones that has been created
Name
Interval
Description
Base Cretaceous
Horizon
Top Tarbert
Horizon
Zone (Isochore)
Top Tarbert 2
Horizon
1
Top Tarbert 1
Zone (Isochore)
Horizon
Zone (Isochore)
Top Ness
Horizon
Zone (Isochore)
Top Ness 1
2
Horizon
Zone (Isochore)
Top Etive
Horizon
3.2.8 Make layering
Layering is built along the pillars with the minimum cell of 3 is selected. 10 number of
layers is selected for all zones under the zone division.
27
3.2.9 Property modelling
3.2.9.1 Scale-up well logs
The Scale up well logs process averages the values to the cells in the 3D grid that are
penetrated by the wells and gives the cell one single value per upscaled log. These cells
are later used as a starting point for Property modeling
3.2.9.2 Petrophysical modelling

Deterministic modelling
a. The 3D grid model is activated and the Petrophysical modelling is opened
b. Use existing property and Porosity_model properties are selected as the
properties to be modelled.
c. Same settings is selected for all zones
d. Moving average method is selected and the setting is set as default
e. The statistic for the porosity property is then checked

Stochastic modelling
a. The 3D model is activated and Porosity_model under petrophysical
modelling is selected.
b. Sequential Gaussian Simulation is selected for all zones and Exponential
Variogram type is selected. 3500 is set as Major range and 1500 as Minor
range, 10 as Vertical range and 25 degree as Azimuth.
c. The porosity model can be view in 3D window.
3.2.9.3 Scale up properties
a. A new simple grid with a grid increment of 100 in X and Y direction is created
and procedures for zones and layering is run.
b. The properties of the fine grid (initial 3D grid model) is dropped into the input,
and also the Porosity_model as well as Permeability_model.
c. Directional averaging is selected in the permeability model and the scale up
properties is run.
28
3.2.9.5 Geometry modelling

Bulk volume property
a. The 3D Grid model is activated and new property on Geometrical
modelling is created. Cell volume is selected as method
b. Bulk volume is used as property template and the statistic of the bulk
volume property is checked.

Cell angle property
a. In Geometry modelling, create new property is selected and the Cell angle
is chooses as method.
b. Value filter is created and the angles that should be filtered is specified by
using minimum value of 20.

Sw calculations : Create above contact property
a. ‘Create new property’ is reselected and ‘Above contact’ is used as method.
The ‘contact level’ is set to constant value (OWC) with a negative sign.
b.
Then, ‘By center of the part of the cell above contact’ is selected as
method.

Property calculator
a. Create a new property
Calculator is selected, the properties template is changed to Net/Gross and
NG=0.8 is typed into the white formula. The calculation is ensured on the
entire grid
b. Calculating values
The calculator can be used as a normal calculator or for returns of single
values using properties and/or log.
29
3.3. Modeling Properties
When it comes to evaluating conventional reservoirs, petrophysicists are normally
concerned with two key parameters: porosity and permeability. Porosity is the volumetric
void space in the rock, whereas permeability is the measurement of a rock’s ability to
allow fluids to pass through it.
Figure 13: Porosity illustration
Porosity, according to Schlumberger Oilfield Glossary, porosity is defined as the
percentage of pore volume or void space, or that volume within rock that can contain
fluids. Porosity can be relic of deposition (primary porosity, such as space between grains
that were not compacted together completely) or can develop through alteration of the
rock (secondary porosity, such as when feldspar grains or fossils are preferentially
dissolved from sandstones). Refer Figure 13. All in all, porosity can be generated by the
development of fractures, in which case it is called fracture porosity.
Effective porosity is the interconnected pore volume pore volume in a rock that
contributes to fluid flow in a reservoir. It excludes isolated pores. Total porosity is the
total void space in the rock whether or not it contributes to fluid flow. Thus, effective
porosity is typically less than total porosity.
For porosity measurements, density tools emit medium-energy gamma rays into the
borehole wall. The gamma rays collide with electrons in the formation, lose energy and
scatter after successive collisions. The number of collisions is related to the number of
electrons per unit volume, which is also known as the electron density. The electron
density for most minerals and fluids encountered in oil and gas wells is directly
proportional to their bulk density, ρbulk.
30
The bulk density measure by the tool, ρlog, results from the combined effects of the fluid
porosity and the rock or matrix, and is used to compute density porosity (Φdensity):
Φ𝑑𝑒𝑛𝑠𝑖𝑡𝑦 =
𝜌𝑚𝑎𝑡𝑟𝑖𝑥 − 𝜌𝑙𝑜𝑔
𝜌𝑚𝑎𝑡𝑟𝑖𝑥 − 𝜌𝑓𝑙𝑢𝑖𝑑
According to Schlumberger Oilfield Glossary, permeability is defined as the ability, or
measurement of a rock’s ability, to transmit fluids, typically measure in darcies or
milllidarcies. The term was basically defined by Henry Darcy, who showed that the
common mathematics of heat transfer could be modified to adequately describe fluid flow
in porous media.
Figure 14: Fluid flow through porous media
Darcy’s formula can be expressed as
𝑄=
where:
𝑘 𝐴 (𝑃𝑖 − 𝑃𝑜 )
𝜇𝐿
Q = the flow rate, cm3/s
Po = the outlet fluid pressure, dynes/cm2
Pi = the inlet fluid pressure, dynes/cm2
𝜇 = the dynamic viscosity of the fluid, Pa.s
L = the length of the tube, cm
k
= the permeability of the sample, darcy
A = the area of the sample, cm2
31
Formations that transmit fluids steadily, such as sandstones, are describes as permeable
and tend to have many large, well-connected pores. An impermeable formation, such as
shaled ans siltstones, tends to be finer grained or of a mixed grain size, with smaller, fewer
or less interconnected pores.
Absolute permeability is the measurement of the permeability conducted when a single
fluid is present in the rock. Effective permeability is the ability to preferentially flow or
transmit a particular fluid through a tock when other immiscible fluids are present in the
reservoir. One of the examples is the effective permeability of gas in a gas-water reservoir.
The relative saturations of the fluids as well as the nature of the reservoir affect the
effective permeability.
Relative permeability is the ratio of effective permeability of a particular fluid at a
particular saturation to absolute permeability of that fluid at total saturation. Calculation
of relative permeability allows for comparison of the different abilities of fluids to flow in
the presence of each other, since the presence of more than one fluid generally inhibits
flow.
Some generalizations can be made as follows:

The higher the porosity, the higher the permeability

The smaller the grains, the smaller the pores and pore throats, the lower the
permeability

The smaller the grain size, the larger the exposed surface area to the flowing fluid,
which leads to larger friction between the fluid and the rock, and hence lower
permeability
Usually the reservoir rocks permeability can be classified as below;
Table 5: Permeability value and its classification
Permeability value (mD)
Classification
<10
Fair
10 – 100
High
100 – 1000
Very high
>1000
Exceptional
32
Bulk Volume - is not an intrinsic property of a material and it represents the volume per
unit mass of a dry material plus the volume of the air between its particles.
General formula to calculate Bulk Volume is:
Bulk Volume of a Rock = Grain Volume + Pore Volume
Vb = Vg + Vp
There are 3 ways to measure bulk volume:

Direct measurement of the dimensions of a regular solid
Bulk Volume = Pi * Length * Radius squared
Vb = PI * L * D^2 / 4
This method is less accurate due to the roughness of the surfaces of the solid and
imperfections in shape.

Fluid displacement using Archimedes Principle
This technique utilizes the Archimedes’ principle of mass displacement in a liquid
(buoyancy).Refer Figure 15:
a. The core is first cleaned, dried, and weighed in air (WTdry)
b. The core sample is then saturated with a wetting fluid and weighed (WTsat)
(the core may be coated with paraffin to prevent evaporation)
c. The sample is then submerged in the same fluid and its submerged weight is
measured (WTsub)
d. The bulk volume is the difference between the last two weights divided by the
density of the fluid.
e. The porosity is the difference between the first two weights divided by the density
of the fluid.
Figure 15: Archimedes’ principle of mass displacement in a
liquid (buoyancy)
33

Fluid displacement using calibrated container (pycmometer)
The bulk volume can be determined also by the volume of the displaced fluid. Fluids that
are normally used are water, which can easily be evaporated afterwards, and mercury,
which normally does not enter the pore space in a core sample due to its non-wetting
capability and its large interfacial tension against air. Laboratory measurements using this
technique are very accurate.
Bulk Volume = Volume of Displaced Fluid = Weight Displaced Fluid / Density Displaced
Fluid
Vb = WTdisp / DENSfl
The Figure 16 below demonstrates the graphical representation on Bulk Volume that has
been obtained in Petrel Software, while completing the Geology and Geosciences phase
of the field in Norway named Gullfaks.
Figure 16: Bulk Volume
34
Pore Volume - is the difference between the bulk volume and the volume of the solid
mineral framework, and by mathematical relations the determination of any two of these
quantities permits the calculation of the porosity. However, where the pore volume is
essentially calculated as the difference between the bulk volume and mineral volume,
relatively small percentage errors in either or both of these can result in larger errors in
the calculated value of porosity. This condition becomes more severe as the pore fraction
becomes smaller and consequently the values of bulk volume and mineral volume
approach each other.
Pore Volume (PV) is defined as the ratio of a porous material's air volume to a porous
materials total volume. But what is the total volume of a porous material? For our
purposes, the total volume of a part is described by the amount of space contained within
an imaginary film that has been tightly shrunken around the outside of the porous part's
exterior geometry. Let’s designate the total volume within this film VT. Inside the tightly
wrapped film and within the cavities of the porous part exists a certain volume of air. Let's
designate this volume of air as VA. As previously stated, Pore Volume is equal to the ratio
of a porous material's air volume to total volume:
(PV % = VA / VT).
The Figure 17 below shows as the pore volume is being described in 3D simulation model
with aid of Petrel Software. The purple color corresponds to void spaces (0 cubic meters).
That is the reason why the entire model is shaded with purple color, as it represents pore
volumes in the given reservoir.
35
Figure 17: Pore Volume
Net Volume
The petroleum industry uses 60º Fahrenheit as a standard to correct liquid hydrocarbon
volumes. We refer to this corrected volume as Net Volume. The uncorrected volume is
referred to as a Gross Volume.
In API; Manual of Petroleum Measurement Standards Chapter 1-Vocuabulary, second
edition, the following definitions exist:
Volume, net standard; abbreviated NSV:
The total volume of all petroleum liquids excluding sediment and water and free water,
corrected by the appropriate volume correction factor (Ci1) for the observed temperature
and API gravity, relative density, or density to a standard temperature such as 60oF or
15oC and also corrected by the applicable pressure correction factor (Cp1) and meter factor.
The Figure 18 below demonstrates the graphical representation on Net Volume that has
been obtained in Petrel Software.
36
Figure 18: Net Volume
STOIIP – Oil in place is the total hydrocarbon content of an oil reservoir and is often
abbreviated STOOIP, which stands for Stock Tank Original Oil In Place, or STOIIP for
Stock Tank Oil Initially In Place, referring to the oil in place before the commencement
of production. In this case, stock tank barrels refers to the volume of oil after production,
at surface pressure and temperature
Accurate calculation of the value of STOOIP requires knowledge of:

Volume of reservoir rock containing the oil.

Percentage porosity of the reservoir rock

Percentage water content of that porosity

Amount of shrinkage that the oil undergoes when brought to the Earth's surface
Volume of reservoir rock containing the oil can be expressed as

Gross Rock Volume (GRV) multiplied by the net-to-gross ratio of the reservoir

Net Rock Volume (NRV) expressing the volume of reservoir rock only

Area of the reservoir multiplied by net pay thickness
37
This can be achieved using the formula
𝑵=
Where N
𝟕𝟕𝟓𝟖 𝑨 𝒉 ∅ (𝑺𝒐 )
𝑩𝒐𝒊
[STB]
= STOIIP, barrels
A
= Area, acres
h
= Net pay thickness, feet
7758
= Conversion factor
∅
= Porosity of the net reservoir rock
𝑆𝑜
= Oil saturation
Boi
= Formation volume factor
The Figure 19 below shows as the STOIIP is being described in 3D simulation model
with aid of Petrel Software. The purple color corresponds to void spaces (0 cubic meters).
Figure 19: STOIIP in 3D simulation model
38
GIIP - Gas Initially in Place. It represents the total hydrocarbon content of a reservoir, as
distinct from 'Reserves' which can be 'recovered' or produced. Oil or gas in place (OIP,
GIP) before the start of production is known as Oil or Gas Originally in Place or Initially
in Place. Gas Initially In Place corresponds to the amount of gas first estimated to be in a
reservoir.
GIIP differs from gas reserves, as GIIP refers to the total amount of gas that is potentially
in a reservoir and not the amount of gas that can be recovered. Calculating GIIP requires
engineers to determine how porous the rock surrounding the oil is, how high water
saturation might be and the net rock volume of the reservoir.
Conventional resources generally exist in discrete, well-defined subsurface accumulations
(reservoirs), with permeability values greater than a specified lower limit. Such
conventional gas resources can usually be developed using vertical wells, and often yield
economic recovery rates of more than 80% of the Gas Initially in Place (GIIP). By
contrast, unconventional resources are found in accumulations where permeability is low.
Such accumulations include “tight” sandstone formations, coal-beds, and shale
formations. Unconventional resource accumulations tend to be distributed over a much
larger area than conventional accumulations and usually require well stimulation in order
to be economically productive; recovery factors are much lower — typically of the order
of 15% to 30% of GIIP
Figure 20 below represents the graphical representation of Gas Initially In Place that has
been obtained through the simulation in Petrel Software. The color scheme on the left of
the geological model corresponds to the amount of the gas contained in the reservoir,
starting from purple (no gas content) to orange and red (high gas content). The plain view
helps to observe gas reserves from the top.
39
Figure 20: GIIP
While Figure 21 represents 3-dimensional model of the reservoir, where Gas Initially In
Place can be observed from different angles.
Figure 21: GIIP 3D
40
Contact Set
According to Schlumberger Oilfield Glossary, contact or interface, are also called fluid
contact, which separates fluids of different densities in a reservoir. Horizontal contacts are
usually assumed, although tilted contacts occur in some reservoirs. The contact between
fluids is usually gradual rather than sharp, forming a transition zone of mixed fluid. A
mixed-fluid reservoir will stratify according to fluid density, with gas at the top, oil in the
middle, and water below. Production of fluids often perturbs the fluid contacts in a
reservoir.
Figure 22: GOC, GWC, OWC
Gas Oil Contact (GOC) is defined as a bounding surface in a reservoir above which
predominantly gas occurs and below which predominantly oil occurs. Gas and oil are
miscible, so the contact between gas and oil is transitional, forming a zone containing a
mix of gas and oil.
41
The interface between the gas and oil phases present in a reservoir formation. During the
production of a well, the GOC may move, resulting in undesirable production conditions
such as a high proportion of gas that may be too much for surface processing facilities.
Monitoring the gas-oil and oil-water contacts is a key element of good reservoir
management practices.
Oil Water Contact (OWC) is defined as a bounding surface in a reservoir above which
predominantly oil occurs and below which predominantly water occurs. Although oil and
water are immiscible, the contact between oil and water is commonly a transition zone
and there is usually irreducible water adsorbed by the grains in the rock and immovable
oil that cannot be produced. The oil-water contact is not always a flat horizontal surface,
but instead might be tilted or irregular.
From the Petrel Software, the contacts can be easily spotted. They are separated by three
main colors. The Figure 23 below shows the top view of the model.
Figure 23: Top view of the model
42
The Figure 24 below shows the side view of the reservoir model. The blue layer indicates
water zone, green layer indicates oil zone whereas the red layer indicates the gas zone. All
the three zones were separated by GOC and OWC.
Figure 24: Side view of the reservoir model
43
Porosity Model – likewise represents the model that can be constructed and visualized in
Petrel, which is able to clearly demonstrate the distribution of porosity along the selected
reservoir or part of it in terms of percentage (Figure 25).
As can be seen in the figure below, lower values of porosity are colored with purple, while
higher values are designated with orange and red colors. In this case the entire reservoir
has average-to-high porosity values varying from 12.5% to 25%.
However there is a presence of low-porosity regions 2.5 – 5% (shaded with purple color)
as well as low-to-medium porosity regions – 7.5 – 10% (shaded with blue color).
Figure 25: Porosity Model
44
Permeability Model – represents the model that is being constructed and demonstrated
through Petrel. It demonstrates the distribution of permeability throughout the reservoir
and has the same graphical principle as Porosity Model. Geological regions with low
permeability are colored with purple color, while high-permeability regions are colored
with orange and red.
This can clearly be observed at the Figure 26 below. The permeability value is maintained
at the average value of 100 mD throughout the entire reservoir (shaded with blue color)
with some low-permeability regions, where the value reaches 1 mD approximately.
However there are some high-permeability regions as well (shaded with yellow color),
where permeability reaches approximately 1000 mD.
Figure 26: Permeability Model
45
3.4. Modeling Results
3.4.1. Volumetric Result
Property Modelling is the final section towards the static model in PETREL. As in
previous discussion, the PETREL generate the necessary parameters to calculate the Stock
Tank Oil Initially in Place STOIIP (STOIIP) and Gas Initially in Place (GIIP) by using
the upscale water, oil and gas saturation at intervals, effective porosity and the net gross
value of 0.8 above the water oil contact.
HC detected with GOC at upper contact found at 1698.61m depth and OWC at
1905.2 at lower contact below the reference point set in PETREL. The water saturation
(𝑆𝑤 ) in gas interval is zero (0) was probably the absence of water in gas interval pore
spaces. The recorded oil saturation (𝑆𝑜 ) in gas interval is 0.75392214 and gas saturation
(𝑆𝑔 ) is 0.24607786 simply calculated by 1-(𝑆𝑊 )-(𝑆𝑜 ). In oil interval, the saturation of water
(𝑆𝑤 ) is 0.2592503 and oil saturation (𝑆𝑜 ) is 0.7407497. Gas saturation recorded is zero (0)
as assumption of no gas phase in this interval pore spaces. The interval depth and
properties presented in the table # as measures to calculate the value of 𝑆𝑤 𝑎𝑛𝑑 𝑆𝑜 as well
the gas formation volume factor, 𝐵𝑔 .
Table 6: Interval depths and properties
Depth (meter)
Interval
Water
Total
depth
Sand Type
Porosity
Saturation
From
To
1
1750
1795
45
Great sand
0.219
0.32
2
1704
1795
91
Shaly sand
0.219
0.32
3
1904
1950
46
Fir sand
0.26
0.22
(𝑺𝒘 )
(meter)
46
The saturation of particular interval and gas formation volume factor, 𝐵𝑔 can be calculated
by the formula below with the parameters stated in Table 6.
(𝑆𝑎𝑡𝑢𝑟𝑎𝑡𝑖𝑜𝑛𝑜,𝑔,𝑤 ) =
∑(𝑆𝑜,𝑔,𝑤 )(Φ)(h)
∑(𝑆𝑜,𝑔,𝑤 )(h)
Where, Φ = porosity
h = total depth of interval
𝐵𝑔 = 0.02827
𝑧𝑇
𝑃
Where, 𝑧 = Compressibility factor
T = Reservoir temperature
P = Reservoir Pressure
Six (6) zones were found out to give a total STOIIP of 420 x 106 𝑠𝑚3 and total
GIIP value of 495 x 106 𝑠𝑚3 . The data extracted from PETREL Software for both oil and
gas interval properties are shown in Table 7 below.
Table 7: Oil and gas interval result
Parameter
Result (106)
Bulk Volume
4277 𝑚3
Net Volume
3422 𝑚3
Pore Volume
624 𝑠𝑚3
HCPV Oil
462 𝑟𝑚3
HCPV Gas
3 𝑟𝑚3
STOIIP
420 𝑠𝑚3
GIIP
495 𝑠𝑚3
47
The interval pore volume divided with bulk volume (as data in Table 6) will generate a
porosity value of 0.1459. The detail result of each zones displayed in Table 8. The type
of facies involves are undefined as assumption of the facies are mixed and irregular type
of formation. The zero value of certain type of facies is assumed the particular facies is
absence in the zone. The porosity of each zone is calculated based on the pore and bulk
volume data of each zone. The difference in value of total volume in table 3 and table 2 is
due to rounding off error with the percentage of difference is not more than 0.
Table 8: Details result of each zone
Zone
Bulk
Pore
Net
HCPV
HCPV
Vol.
Vol.
Vol.
Oil
Gas
(x 𝟏𝟎𝟔
(x 𝟏𝟎𝟔
(x 𝟏𝟎𝟔
(x 𝟏𝟎𝟔
(x 𝟏𝟎𝟔
𝟑
1
TT –
TT2
TT2 –
TT1
TT1 –
TN
TN –
TN1
TN1 –
TE
TOTAL
Porosity
𝟑
𝒎 )
𝒓𝒎 )
1854
274
491
𝟑
𝟑
𝟑
STOIIP
GIIP
(x 𝟏𝟎𝟔
(x 𝟏𝟎𝟔
𝒔𝒎𝟑 )
𝒔𝒎𝟑 )
𝒎 )
𝒓𝒎 )
𝒓𝒎 )
0.1478
1484
203
0
185
58
70
0.1426
393
52
1
47
153
331
42
0.1269
265
32
0
29
6
230
31
0.1348
184
23
0
21
21
971
156
0.1606
777
116
1
105
229
399
49
0.1228
319
36
0
33
28
4276
622
3422
441
2
420
495
48
3.5. Petrophysics
3.5.1. Lithology Study
The lithology interpretation for each well in interest are as follows;
3.5.1.1. B8 Well
Intervals (m)
1885 - 1990
1990 – 1933
Pattern
100% silt
Inter bedding of sandstone within a siltdominant formation
1933.0 - 1958
Inter bedding of silt within a claydominant formation.
1958 - 2008
Inter bedding of silt within a claydominant formation.
2008 - 2055
100% clay
49
3.5.1.2. B9 Well
Intervals (m)
Pattern
1820 – 1830
100% sandstone
1830 – 1824
About 31.7% shale
1840 – 1860
Dominant clay formation and minor
trace of silt.
1860 - 1885
Inter bedding of clay within a siltdominant formation.
1885 - 2010
100% clay
50
3.5.1.3. C5 Well
Intervals (m)
1918 - 1965
1965 – 1980
Pattern
100% clay
Inter bedding of clay within siltdominant formation
1980 – 2019
Dominant clay formation made up of
36% clay and minor trace of silt.
2019 – 2049
Dominant silt formation and minor
trace of clay.
2049 - 2104
Inter bedding of sand, silt and clay
2014 - 2167
Almost 100% clay
51
3.5.14. C6 Well
Intervals (m)
Pattern
2000 – 2090
100% clay
2090 – 2110
Almost 100% silt
2010 – 2041
Almost 100% silt, with minor trace of
sandstone.
2041 – 2070
100% clay
2070 – 2210
Inter bedding of sandstone and silt
2210 - 2255
Almost 100% clay
52
3.5.2. Log Interpretation
The interpretation was made to each well on the correlation (east-west), which are for B8
Well, B9 Well, C5 Well and C6 Well.
3.5.2.1. B8 Well
Layer
Top Tarbert –
Tarbert2
Tarbert2 –
Tarbert1
Tarbert1 – Top
Ness
Top Ness – Ness1
Ness1 – Top
Etive
Intervals (m)
Pattern
1885 - 1990
Reservoir
1990 – 1933
Reservoir
1933.0 - 1958
Non-reservoir
1958 - 2008
Non-reservoir
2008 - 2055
Non-reservoir
53
3.5.2.2. B9 Well
Layer
Top Tarbert –
Tarbert2
Tarbert2 –
Tarbert1
Tarbert1 – Top
Ness
Top Ness – Ness1
Ness1 – Top
Etive
Intervals (m)
Pattern
1820 – 1830
Reservoir
1830 – 1824
Non-reservoir
1840 – 1860
Non-reservoir
1860 - 1885
Reservoir
1885 - 2010
Non-reservoir
54
3.5.2.3. C5 Well
Layer
Base Cretaceous –
Top Tarbert
Top Tarbert –
Tarbert2
Tarbert2 –
Tarbert1
Tarbert1 – Top
Ness
Top Ness – Ness1
Ness1 – Top
Etive
Intervals (m)
Pattern
1918 - 1965
Non-reservoir
1965 – 1980
Reservoir
1980 – 2019
Reservoir
2019 – 2049
Non-reservoir
2049 - 2104
Reservoir
2014 - 2167
Non-reservoir
55
3.5.2.4. C6 Well
Layer
Base Cretaceous –
Top Tarbert
Top Tarbert –
Tarbert2
Tarbert2 –
Tarbert1
Tarbert1 – Top
Ness
Top Ness – Ness1
Ness1 – Top
Etive
Intervals (m)
Pattern
2000 – 2090
Non-reservoir
2090 – 2110
Reservoir
2010 – 2041
Reservoir
2041 – 2070
Non-reservoir
2070 – 2210
Reservoir
2210 - 2255
Non-reservoir
56
3.5.3. Well Log Correlation
The Gullfaks field was correlated in the several directions using the available Gamma Ray
(GR) logs from the wells. These wells penetrated the Tarbert, Ness and Etive formations.
The correlation was done using Petrel software and is shown in the following figures. The
key feature that was used to assist in the correlation was the lithology difference such as
the clay layer that exists between different zones.
As shown in the Figure 27 below, the field was correlated in the Northeast-Southwest
direction using the wells B8, B9, C5 and C6.
Figure 27: Wells correlated in Northeast-Southwest direction.
The correlation in Figure 28 shows that thinning occurred across the formations as it goes
from well B8 to well B9. All the zones including Tarbert, Ness and Etive experienced
57
thinning which might be caused by erosion. Moving on from well B9 to well C5, the
formations thickened gradually. However, it can be observed that the formation shifted
downwards. Therefore it can be inferred that faulting occurred and there was fault block
movements between well B9 and C5. Correlation between well C5 and C6 shows that
layer dipping occurred as the formation shifted downwards, but both the formations were
still in the same fault block.
Figure 28: Well tops correlations using Gamma Ray logs from well B8, B9, C5 and C6.
58
Another well correlation was analyzed in the North-South direction involving
well A10, A15, A16, B8 and B9 as shown in the Figure 29 below.
Figure 29: Wells correlated in North-South direction
From the well tops correlation, it is observed that the Tabert formation is not found
in well A10 due to some possible unconformities. Moving northwards, the well tops
descend gradually from well A16 to B9 and B8. This shows the dipping of the reservoir
formations.
59
Figure 30: Well tops correlations using Gamma Ray logs from well A10, A15, A16, B8 and B9.
60
Another correlation was done in the Northeast-Southwest direction using well C2,
C3, C4, C5 and C6.
Figure 31: Wells correlated in Northeast-Southwest direction.
The well tops correlation is shown in the following figure. We can observe that
the formations shifted upwards from well C6 to C5. Starting from well C5 northwards,
the depth of formation tops remained relatively equal showing that there was no
significant geological events occurring between these wells.
61
Figure 32: Well tops correlations using Gamma Ray logs from well C2, C3, C4, C5 and C6.
62
3.5.4. Zone of Interest
According to early interpretation, the Oil Zone for C6 Well is out of the investigated
layers, which is above the Base Cretaceous layer (and have no oil or water zone within
investigated layers). Refer Figure 33. Thus, this will well not be analyzed further.
Figure 33: The Oil Zone located above Base Cretaceous layer for C6 Well.
63
The analysis also done on C5 Well and the Oil Zone is out of the investigated layers,
which is above Base Cretaceous layer. Refer to Figure 34
Figure 34: The Oil Zone located above Base Cretaceous
layer for C5 Well.
Therefore, the zone of interest analysis will be done to B8 and B9 Well because the Oil
Zone is located within the investigated layers. Refer Figure 35 and Figure 36.
64
Figure 35: The Oil Zone located within investigated layers for
B8 Well.
Figure 36: The Oil Zone located within investigated layers for
B9 Well.
65
3.5.4.1. Zone of interest for B8 Well
Zone A
Zone B
Zone A
Zone A
Zone A
Type of zone
Oil zone
Depth
1895m – 1907m
Thickness
12m
Layer
Base Cretaceous – Tarbert 2
Within Zone A, the probable reservoir is located between depths of 1895m – 1990m (5m
thickness) because the low gamma ray reading shows that it is probably sand zone, and
66
have high porosity reading which may indicates the reservoir has a good storage capacity
for hydrocarbon.
Zone B
Zone B
Zone B
Type of zone
Water zone
Depth
1907m – 1958m
Thickness
51m
Layer
Tarbert 2 – Top Ness
67
3.5.4.2. Zone of interest for B8 Well
Zone C
Zone C
Zone C
Zone C
Type of zone
Oil zone
Depth
1820m – 1834m
Thickness
14m
Layer
Base Cretaceous – Tarbert1
Within Zone C, the probable reservoir is located between depths of 1820m – 1830m (10m
thickness) because the low gamma ray reading shows that it is probably sand zone, and
have high porosity reading.
68
3.5.5 Pressure Plot
MDT Formation Pressure: A10
2420
5400
5500
2440
2460
Pressure (psia)
2480
2500
2520
2540
2560
y = 104.93x - 249993
R² = 0.9226
Depth (ft)
5600
5700
5800
y = 3.9992x - 4158.2
R² = 0.9927
5900
6000
6100
Figure 37: Pressure plot for well A10
For well A10, a graph of depth against pressure is being plotted. From the data file
provided, two linear lines can be generated. The intersection of two lines indicates the
contact between two fluids i.e. gas and oil. From the intersection point, it is shown that
the Gas Oil Contact (GOC) is at the depth of 5569.23 ft.
69
Figure 38: Pressure plot for well B9.
A graph of depth against pressure for well B9 is being plotted. From the data file provided,
two linear lines can be generated. The intersection of two lines indicates the contact
between two fluids i.e. oil and water. From the intersection point, it is shown that the Oil
Water Content (OWC) is at the depth of 6250.09 ft.
70
3.5.6 Volume of Shale Calculation
Gamma ray log is able to record trace of radioactive mineral such as uranium, thorium
and potassium in the formation. Shale usually has high radioactive minerals and thus
gamma ray log can be used as an indicator of possible shale formation and also useful to
calculate volume of shale. As shown in the Figure 39 below.
Figure 39: Identification of shale formation using GR log
Since radioactive isotopes are often associated with the clay minerals in shales, it is a
commonly accepted practice to use the relative gamma ray deflection as a shale volume
indicator. The simplest procedure is to scale the gamma ray between its minimum and
maximum values from 0 to 100% shale.
71
Shale volume can be calculated from the equation below:
For Gamma-Ray:
𝑉𝑠ℎ =
𝐺𝑅𝑙𝑜𝑔−𝐺𝑅𝑚𝑖𝑛
𝐺𝑅𝑚𝑎𝑥−𝐺𝑅𝑚𝑖𝑛
Where, Vsh = Volume of shale
GRlog = Gamma ray from log
GRmax= Gamma ray max (100% shale)
GRmin = Gamma ray min (Clean sand)
Table below shows the result of the shale volume calculation for wells:-
72
Well: C6
GR max = 150, GR min = 34.17
Table 9: Volume of Shale for Well C6
Zone
GR log (Average)
Base Cretaceous – Top Tarbert
Volume of Shale (%)
-
100
Top Tarbert– Tarbert 2
50.18
13.8
Tarbert 2 – Tarbert 1
73.65
34.1
Tarbert 1 – Top Ness
-
100
Top Ness – Ness 1
51.85
15.3
Ness 1 – Top Etive
-
100
73
Well: C5 GR max = 150, GR min = 42
Table 10: Volume of Shale for Well C5
Zone
GR log (Average)
Base Cretaceous – Top Tarbert
Volume of Shale (%)
-
100
Top Tarbert– Tarbert 2
46.5
4.2
Tarbert 2 – Tarbert 1
80.88
36
Tarbert 1 – Top Ness
97
50.9
Top Ness – Ness 1
62.41
18.9
Ness 1 – Top Etive
-
100
74
Well: B9 GR max = 136. 9, GR min = 52.36
Table 11: Volume of Shale for Well B9
Zone
GR log (Average)
Volume of Shale (%)
Base Cretaceous & Top Tarbert–
Tarbert 2
54.135
2.1
Tarbert 2 – Tarbert 1
79.13
31.7
Tarbert 1 – Top Ness
-
100
Top Ness – Ness 1
75
26.8
Ness 1 – Top Etive
-
100
75
Well: B8 GR max = 124.42, GR min = 52.15
Table 12: Volume of Shale for Well B8
Zone
GR log (Average)
Volume of Shale (%)
Base Cretaceous & Top Tarbert–
Tarbert 2
53.3
1.6
Tarbert 2 – Tarbert 1
81.96
41.2
Tarbert 1 – Top Ness
96.52
61.4
Top Ness – Ness 1
75.2
31.9
Ness 1 – Top Etive
-
100
76
Well: A16
Table 13: Net Pay for Well A16
Top Tarbert Zone
Tarbert 2
GR LOG
65.94
GR Mx
132.78
GR Min
29.70
Vsh
0.35
Gross Thickness
6.59
Gross Sand
4.28
Porosity
0.23
Net Sand
4.28
Oil Saturation
0.76
Net Pay
3.26
Based on the
Table 13 above, it has shown an example for the values for gross
thickness, gross and, porosity, net sand and net pay. The results are based on the equations
below :
Gross thickness = Depth of each zone
Gross Sand
= Gross Thickness –(Gross thickness × Vsh)
Porosity
= Average Value of Zone
Net Sand
= Gross Sand × Porosity
So
= 0.7539
Net Pay
= Net Sans × So
The calculations are repeated based on the above equations for each zone and each well.
77
CHAPTER 4
RESERVOIR ENGINEERING
4.1 Reservoir Data
4.1.1. Summary of Results
Reported Reservoir Conditions
Reservoir Pressure
: 2516psia
Reservoir Temperature
: 220degF
Constant Composition Expansion
Bubble point Pressure
: 2516.7 psia
Differential Liberation Test
Oil Formation volume factor
: 1.1 bbl/stb
Solution Gas Oil Ratio
: 1.1342scf/stb
Oil Density
: 45.11lb/ft3
Reservoir Fluid Viscosity
Oil Viscosity
: 1.33 CP
78
4.1.2. Separator Sample
Type of sample
Separator Oil
Cylinder no.
Opening
pressure
separator
Separator Gas
1339-GFK
2339-GFK
at 100@95.0
125@95.0
temperature,
degF, Psig
Approximate
sample 575
20000@125psig
volume @1000 Psig (cc)
Bubble point pressure at 125@95.0
separator
NA
temperature,
degF Psig
Remarks
Pair with 2339-GFK
Pair with 1339-GFK
4.1.3. Compositional Analysis of Separator Oil, Separator Gas Samples and
Calculated Wellstream Composition
A spike flash technique was used to carry out the compositional analysis whereby the
sample was flashed to atmospheric conditions to obtain stock tank gas and liquid at
equilibrium conditions. The evolved gas phase was circulated for sufficient period of time
for the oil and gas to achieve equilibrium. The gas oil ratio (GOR) was then measured.
Table 14 below summarizes the results for compositional analysis of the separator oil and
gas samples.
79
Table 14: Compositional analysis of the separator oil and gas samples
Mole %
Components
Separator
Separator
Wellstream
Oil
Gas
CO2
0.08
1.49
0.91
N2
0.00
0.27
0.16
C1
1.91
60.66
36.47
C2
1.60
15.32
9.67
C3
2.40
10.14
6.95
IC4
0.81
1.88
1.44
NC4
2.66
4.82
3.93
IC5
1.45
1.43
1.44
NC5
1.57
1.30
1.41
C6
6.81
2.59
4.33
C7+
80.71
0.09
33.29
TOTAL
100.00
100.00
100.00
Molecular
Density @
Weight
60degF
218
0.8515
The wellstream composition was calculated based on GOR of 130scf/stb
In case of compositional analysis of separator oil the main purpose of the experiment is to
find the amount of each component in the fluid. All the values presented in the table in
the Wellstream column represent the amount of each component (e.g. CO2, N2, C1, C2,
C3 etc) in the fluid. The Molecular Weight of each component is left blank as they are
taken as default. The only value that has been altered is for C7+ as it is a heavier
component and its values (molecular weight and density @60degF) are to be entered in
the table. Likewise as can be seen from the table above the most amounts comprise C7+
components (33.29 mole% in the wellstream), while N2 corresponds only to 0.16 mole%
in the wellstream.
The separator oil and gas were physically recombined to the gas oil ratio at separator
conditions to represent the reservoir fluid. From the separator oil and gas composition, the
80
composition of the recombination fluid was calculated by using the separator GOR. The
resulting fluid was then used for the remaining test program to describe the fluid behavior
in the reservoir.
4.1.4. Constant Composition Expansion, CCE Experiments
This test was performed to simulate the pressure-volume relation of the fluid. CCE Test
objectives are to determine the bubble point pressure, oil compressibility and percentage
of liquid volumes below bubble point. Table 15 below summarizes the CCE Test results.
Table 15: Summary of CCE Test results
Pressure
Relative
Pressure
Relative
(psig)
Volume
(psig)
Volume
5000
0.9453
2516
1.0001
4500
0.9541
2401
1.0243
4000
0.9638
2253
1.0599
3500
0.9746
2090
1.1066
3000
0.9867
1897
1.175
2900
0.9893
1698
1.2655
2800
0.992
1477
1.4006
2700
0.9948
1292
1.5557
2620
0.997
1040
1.8696
2605
0.9974
830
2.2956
2591
0.9978
640
2.9457
472
3.9877
In case of Constant Composition Expansion (CCE) Experiments the main goal is to find
Bubble Point Pressure. Likewise from the table above the pressure is being initially
decreased from the value of 5000 psig, which corresponds to 0.9453 Relative Volume
value. The Bubble Point Pressure will be achieved once the relative volume approximately
81
gets equal to 1. Hereby from the table above the pressure that corresponds to Bubble Point
Pressure is 2516 psig as this pressure results in Relative Volume 1.0001, which fulfills the
initial condition. It is very crucial to find the Bubble Point Pressure as it will be used
further on for Differential Liberation (DL) Experiments.
Likewise this stage of experiment has been successfully been completed and the Bubble
Point Pressure value has been identified.
4.1.5. Differential Liberation, DL Experiments
Pressure
Vapor Z-
Liquid
Gas-Oil
Oil Relative
Gas
Gas FVF
(psig)
Factor
Density
Ratio
Volume
Gravity
(rb/Mscf)
(lb/ft3)
(Mscf/stb)
(rb/stb)
45.11
1.1342
1.7493
2516.7
0
2350
0.8686
45.669
1.0526
1.7095
0.7553
1.2574
2100
0.8692
46.502
0.9378
1.6535
0.7547
1.407
1850
0.8719
47.331
0.8309
1.6013
0.7565
1.6006
1600
0.8767
48.16
0.7307
1.5523
0.7614
1.8586
1350
0.8836
48.992
0.6361
1.5057
0.7704
2.2164
1100
0.8926
49.835
0.546
1.4609
0.7859
2.7411
850
0.9036
50.699
0.4591
1.4171
0.8121
3.5773
600
0.9167
51.608
0.3732
1.3726
0.8597
5.105
350
0.9324
52.632
0.2824
1.3234
0.9618
8.7518
159
0.9481
53.673
0.196
1.272
1.1726
18.685
56.323
0
1.1228
1.8901
0
0
In case of Differential Liberation (DL) Experiments the main flow starts from the Bubble
Point Pressure (2516 psig), which has been identified in the previous Constant
Composition Expansion (CCE) Experiments. The pressure keeps decreasing until the
surface pressure value (0 psig) in order to track down the change in fluid density change.
82
This is being done in order to investigate the behavior of the fluid as it is being extracted
to the surface.
4.1.6 Separators Experiments
The separator test objective is to determine the effect of separator pressure and
temperature on separator volume factor, GOR, oil and gas density and stock tank oil
gravity. Table below summarizes the results of all the three cases of separator test
accordingly.
Separator Stage
Separator
Separator Pressure
GOR
Liquid
Number
Temperature
(Psia)
(Mscf/bbl)
Density (lb/ft3)
(DegF)
1
60
14.7
62.821
1.0313
1
120
35.3
60.01
1.032
2
60
14.7
62.8
0.0151
4.1.7 Swelling Test (CO2)
Mole
Saturation
Swell Factor
Fraction
Pressure
(Relative
Gas
(psig)
Volume)
0
2519
1
5
2607
1.024
10
2705
1.0504
20
2913
1.1136
30
3159
1.1949
40
3285
1.3031
Added
83
4.1.8 Swelling Test (N2)
Mole
Saturation
Swell Factor
Fraction
Pressure
(Relative
Gas Added
(psig)
Volume)
0
2521
1
5
3216.6
1.0117
10
4019
1.0242
20
5784
1.0528
30
8057
1.0879
4.1.9 Well / Sampling Information
Figure 40: Oil Density
84
Figure 41: Oil Formation Volume Factor
85
4.2 Well Test Data
Before actually conducting the reservoir simulation studies, all data that is available for
dynamic modeling purposes are quality checked (QC), analyzed, and processed as part of
the simulator input. A10, A15 and A16 are a wildcat well in Gullfaks reservoir, located in
the North Sea. The objective of the well is to test the hydrocarbon potential in the
reservoir. The sand is tested in these wells in order to evaluate the well productivity and
flow performance, obtain reservoir data, obtain representative samples and investigate the
sand producibility. The following are the reservoir conditions:
Table 16: Reservoir conditions
Reservoir pressure
2516psia
Reservoir temperature
220⁰C
The following are the perforation depth data for three of the wells:
Table 17: Perforation depth data for three of the wells
Top MD
Bottom MD
Well A10
1923.89m
1943.89m
Well A15
1870.33m
1899.09m
Well A16
1913.03m
1933.03m
Bottom hole pressure, gas rate, water rate and oil rate were recorded for well A10, A15
and A16. Build-up and drawdown test from a single well has been recorded. For reservoir
engineering, the given recordings namely date, time, oil rate, gas rate, bottom hole
pressure and water rate were used. The data were from 1st July 2013 until 9th July 2013.
The following are the formation and well characteristic:
86
Formation Characteristic
Table 18: Formation Characteristic
Formation Name
Unit 3
Sampling Date
01-July-2011
Reservoir Pressure, psia
2434.91 @ 1701 m-TVDRKB
Reservoir Temperature, degF
220
Well Characteristics
Table 19: Well Characteristics
Total Depth (m-RKB)
*
Producing interval
1600 – 1615 m MDRKB
Tubing size, in.
3 ½ OD, 2.75(ID)
Well type
Vertical Well
For sampling condition for the type of surface PVT, following are the data:
Separator Pressure (psia)
: 125
Separator Temperature (degF)
: 95
Test Separator Oil Rate (stb/day)
: 1533.5
Test Separator Gas Rate (MMscf/day)
: 0.181
Gas Oil Ratio (scf/day)
: 130
Sample cylinder no.
:1339-GFK
(separator
(separator gas)
Below is the drawdown and pressure build up test for multi rate well:
87
oil),
2339-GFK
Figure 42: Multi rate well
Below is the drawdown and pressure build up test for single rate well;
Figure 43: Single rate well
88
4.3 Reservoir Simulation
4.4.1
Objectives of Simulation Study
Simulation study is planned to forecast the reservoir production performance and to
analyze the best development strategy which in turn will give the maximum recovery of
oil production of Gullfaks Field. In order to complete the goals, following objectives are
expected to be achieved;
i.
To determine the optimum number of wells and propose a suitable depletion
strategy
ii.
To generate production profile and calculate reserves based on well
potential.
iii.
To develop a justifiable numerical simulation model to predict reservoir
performance.
The result of simulation study is highly important as it will be the main reference or the
main basis of other judgment for the next phase of this FDP. The main simulators used for
this field development project are Petrel and Eclipse 100. The static model was develop
by using Petrel and exported to Eclipse 100 for dynamic. All the data input required for
simulation were defined in Petrel. Most of the file that were exported to Eclipse 100 are
in include file (.INC), which is some value cannot be edited by Eclipse 100. In this model,
all the reservoir properties such as rock properties and fluid properties are first defined in
the Main Gullfaks model.
4.4.2
Reservoir Model Set Up
The simulator used for reservoir modeling is Petrel RE. The dynamic model is developed
using the static model done earlier. All the data input required for simulation were defined
as in the static model. The following chart shows the workflow involved in the dynamic
modeling process.
89
• Make a simulation fault
• Transmissibility multiplier
Simulation Fault
• Adding an aquifer
• Run a case wih aquifer
Aquifer
• Create observed data file
• Import observed data
• Visualize the observed data
Observed Data
History Matching
• Make history development strategy
• Run history matching
• View history matching simulation results
Figure 44: Workflow of dynamic modelling
4.4.2.1 Simulation Fault

Make a simulation fault
A new simulation fault is created by using the Utilities folder. A new points are
added in the grid cell closed to the project boundary to make sure the fault is
extended all the way to the boundary. However, the project boundary (edges
around surface) need to be displayed first in a 2D window so as the top horizon of
the 3D grid model. This process is later save as ‘Fault Polygon’. However, to store
the new fault in the ‘Fault folder’ under the simple grid on the Models pane, the
previous created ‘fault polygon’ need to be ‘right-clicked’ and ‘Create simulation
(grid) fault’ is selected after the ‘3D Grid’ is activated on the Models pane.

Transmissibility multiplier
The new fault is viewed in a 3D window. A constant ‘transmissibility multiplier’
is entered after the ‘Fault analysis’ process that is located in the ‘Property
modelling’ folder is opened. The changes in the project is then saved.
90
4.4.2.2 Aquifer

Adding an aquifer
a. A polygon which encloses the eastern part of the model is draw
(deactivated old) and saved as ‘Aquifer boundary’.
b. The ‘Upscaled grid’ on the ‘Model’ pane is activated.
c. The ‘Make aquifer’ process which located under ‘Simulation’ on the
‘Process’ pane is opened.
d. By selecting ‘create new’, a new aquifer model is created and named as
Fet1.
e. The connection and properties of the Fet1 is defined and inserted.
f. In order to check the effect of the size of the water reservoir on the water
production from well P07, previous step (e) is repeated by changing the
external radius.
g. The project is saved.

Run a case with aquifer
a. A new case is created and named under the ‘Define simulation case’ pane.
The ‘grid’ tab is inspected and aquifer ‘Fet1’ is dropped from the ‘Models’
pane.
b. The process is applied and the case is take part.
4.4.2.3 Observed Data

Create observed data file
a. Data from well build-up and drawdown history is used and copied on a
new notepad with the following format;
91
Figure 45: Format for creating observed data file
b. Data conversion is conducted before it is copied into the notepad as the
history data is in field unit and the unit used by the Petrel software is in
metric unit.
c. The file is then save as VOL File.

Import observed data
a. After selecting to import data (observed data) under ‘Global observed
data’, well names in the file is make sure matches the correct well in the
project.
b. The column number for the data that is imported is rechecked so that it is
correct and also an appropriate ‘Property identifier’ is selected under the
‘Data’ tab.
c. ‘Create new’ is then selected in the ‘Global observed data column’ in order
to add subject to the Global observed data folder.
d. ‘OK’ is clicked to import the observed data.

Visualize the observed data
a. A function window is opened and ‘Dynamic data folder’ is expand
followed by the ‘Source type’ folder under the ‘Results’ pane.
b. The ‘check box’ in the well A10 is selected under the expanded ‘Identifier’
folder.
c. Boxes in front of Observed data, Oil production rate in the Rates folder and
Bottom hole pressure in the Pressures folder are selected.
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4.4.2.4 History Matching

Make history development strategy
a. The ‘Stimulation folder’ is expanded in the ‘process’ pane and the ‘Make
development strategy’ process is opened
b. A new development strategy is selected. ‘Use presets button’ is clicked and
‘History strategy’ is selected from the drop-down menu.
c. The new strategy is named.
d. The ‘Strategy tree’ is observed and all the wells excepts for A10, A15 and
A16 are removed in the wells folder.
e. The ‘Rules’ folder in the ‘Strategy tree’ (the left pane of the Make
development strategy process dialog) is selected and the History rate
control (Wells folder) rule is clicked.
f. All the parameters for the history rate control is checked and ‘OK’ is
clicked to save the history development strategy.
g. The new Development strategies folder is at the bottom of the input pane.

Run history matching
a. ‘Define simulation case’ is opened and ‘Initialization case’ is selected
under ‘Edit existing’. Then a new case is created and named as History.
b.
The ‘Strategy tab’ is opened and the new item is appended into the
‘Development strategy’.
c. ‘History strategy’ from the input pane is dropped into the ‘Development
Strategy’ by clicking the blue arrow.
d. ‘Apply’ and ‘Export’ buttons are clicked. After the export process is
finished, the case is ‘Run’.

View history matching
a. A function window is opened and ‘History cases’ is selected in the cases
pane.
93
b.
The ‘Dynamic data folder’ is expand followed by the ‘Source type’ folder
under the ‘Results’ pane.
c. The ‘check box’ in the well A10 is selected under the expanded ‘Identifier’
folder.
d. Boxes in front of Observed data, Oil production rate in the Rates folder and
Bottom hole pressure in the Pressures folder are select to be viewed.
e. The history strategy data and observed data are viewed and analyzed.
4.4.3 Base Case Model
The base case model for dynamic modeling was shown in the Figure 46 below. The total
STOIIP for the model is 420 x106 sm3.
Figure 46: Base case model of dynamic modelling
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4.4.4
Reservoir Development Planning
4.4.4.1 Creaming Curve
Suitable well target locations are selected from dynamic model by placing them in the
strategic locations which fulfilled reservoir criteria as follows:
i. High oil saturation
ii. Good reservoir quality in terms of permeability and porosity
iii. Clearance from OWC
iv. Away from fault
vi. Reservoir thickness
The wells identified are A10, A15, A16, B8, B9, C2, C3, C4, C5 and C6. To determine
the optimum reservoir development strategy, each of the wells is run individually in order
to analyze individual performance of the well in response with well location. Productive
drainage area is indicated by ability of the well to produce the highest oil recovery. The
Figure 47 below shows the individual well performance in term of cumulative oil
production. From Figure 48, it is observed that well A15 has the highest recovery amongst
all while B8 is the poorest. Drainage area at well B9 almost reach A15 as the second
highest followed by A10 and A16.
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Figure 47: Graph of Field Oil Production Cumulative
Figure 48: Chart of Cumulative Oil Production for Individual wells
To determine the optimum number of wells per reservoir, creaming curve method is
applied. Creaming curve plots the total amount of oil discovery against the total number
of wells. Drilling a well is expensive so an increasing number of wildcats generally
indicate that it is getting harder to find oil. The total amount of oil that is discovered
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against the total number of exploratory wells drilled is plotted. In plotting the creaming, 5
simulation cases were run to get the total cumulative oil of each case of which the number
of wells is the variable of those cases. The respective wells with their oil cumulative
production resulted from the simulation are presented below.
Table 20: Optimization of Number of Wells per Reservoir
a
No. of
wells
1
b
Case
Producer Wells
Cumulative Oil (𝑠𝑚3 )
A15
1,686,307
2
A15, B9
3,835,326
c
3
A15, B9, A10
5,246,142
d
4
A15, B9, A10, A16
6,261,746
e
5
A15, B9, A10, A16, B8
6,784,733
The creaming curve is plotted as follow:
Creaming curve
8000000
Cum.Oil Production (sm3)
7000000
6000000
5000000
4000000
3000000
2000000
1000000
0
0
1
2
3
4
5
6
No. of wells
Figure 49: Creaming curve
The creaming curve above clearly shows that the total oil production is increasing with
the number of wells. The recovery is optimum when the reservoir has 5 wells. Lesser
number of wells is preferred if the same amount of oil is contributed by two cases, but in
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Creaming curve show no wells that not contributing to the total reserve. Thus it can be
concluded that the optimum number of wells required in this particular reservoir is five
(5).
4.4.3.2 Water Injection
The main drive mechanism of Gullfaks field is water aquifer with some scattered gas cap
drive mechanism. The producer wells are produced by natural water drive from the active
underlying water aquifer. As the reservoir is produced, the aquifer support is depleting by
time. Since there is vast amount of aquifer in the field, water injection is identified as the
most viable strategy for pressure maintenance of the aquifer so that the aquifer can
continue to support natural depletion of the hydrocarbons. Water injection is also cheaper
in capital expenditure (CAPEX) and operating expense (OPEX) and easier in operation
handling. The Figure 50 below illustrates the aquifer in Gullfaks field.
Figure 50: Water Aquifer in Gullfaks field
Water injector wells are located in the aquifer areas in order to provide pressure
maintenance. The wells identified are C2, C3, C4, C5 and C6. Sensitivity analysis is
conducted for the pressure maintenance scheme to determine the optimum number of
98
injectors. The results are shown in term of cumulative oil production forecast for 5 years
in Table 21.
Table 21: Sensitivity analysis for water injection
Case
Cumulative Oil Production (𝑺𝑴𝟑 )
Injector Wells
a
C2, C3, C4, C5, C6
599,399,236
b
C2, C3, C4, C5
59,881,140
c
C2, C3, C4, C6
59,791,672
d
C2, C3, C4
60,559,692
e
C2, C3
60,495,996
f
C2, C4
60,844,700
g
C3, C4
60,159,220
h
C2
47,475,984
i
C3
55,365,820
j
C4
48,537,184
From Table 21, the optimum water injection scheme is Case G with 2 injectors (C2 and
C4). Figure 51 below displays the production forecast for selected water injection well at
C2 and C4 as the optimum availability of aquifer at the particular location. The water
injection will maintain the pressure from fast depleting aquifer.
99
Figure 51: Water Aquifer in Gullfaks field
4.4.5
Sensitivity Analysis
The main objective of sensitivity analysis is to show what extent the viability of a project
is affected by variations in major quantifiable. This is a technique used to study the impact
of changes in project variables on the base case. To put it in other words, the whole idea
of doing sensitivity analysis is to identify the key variables which influence the project
effectiveness.
In fact, doing sensitivity analyses based on the simulation base case result is able to
optimize the reservoir performance. Besides, sensitivity analyses also play the role in
prioritizing the importance reservoir parameters which affecting production performance.
There are four parameters which have been sensitized in the simulation study i.e. pressure
maintenance scheme, injection time, production life and water cut. By using the base
model, the parameters mentioned is varied one by one at one time to study the optimum
condition in oil recovery.
Upon decided to use water injection as production maintenance scheme, the injection is
done by manipulating the injection starting time. Base case waterflood injection time is
being compared with other cases of different injection time. The results turns out that there
is an obvious difference in field oil production cumulative between base case waterflood
and the case of waterflood starting at different time.
From the result, base case water flood with C2 and C4 injection wells manage to produce
60,844,700 sm3 while water injection on year two is only able to produce 23,263,914 sm3.
This can be seen from the Figure 52 below
100
Figure 52 Comparison of Field Oil Production Cumulative between Base Case and Year Two
On the other hand, comparison is being made between water injection time of January
2014 and July 2014. From the Figure 53 below, it can be seen that oil production
cumulative of water flood at January 2014 is having higher production as compared to the
one at July 2014. Let the water flood to be at January 2014, the production is 23,263,914
sm3, while water flood at July 2014 produces 10,439,950 sm3.
101
Figure 53: Comparison of Field Oil Production Cumulative between Waterflood at January 2014 and July
2014
Judging from the trending of the field oil production cumulative curves, the early the
injection time, the higher the production. This might be due to the reason that early
injection time can maintain the pressure longer, and hence the oil recovery is higher.
102
4.4.6
Optimum Model
In summary, through the reservoir simulation studies done, it is proposed that the optimum
development of Gullfaks Field involves 5 producers well and 2 injectors well with water
cut of 0.5. It is also proposed that the water injection to be started right from the start of
production for maximum recovery. Based on the production forecast for 5 years, the
proposed development plan will produce 60844700 sm3 amount of oil. The production
profile (oil and water production) for each of the producer wells are shown in Figure 54,
Figure 55, Figure 56, Figure 57 and Figure 58.
Figure 54: Production forecast for well A10
103
Figure 55: Production forecast for well A15
Figure 56: Production forecast for well A16
104
Figure 57: Production forecast for well B8
Figure 58: Production forecast for well B9
105
4.4.7 Production Forecast
Based on the optimum dynamic model (5 producers and 2 injectors with water cut of 0.5
and water injection from start), production forecast is run for 5 years and 10 years to
determine the recovery. The field cumulative oil production for 5 years and 10 years are
60844700 sm3 and 92995192 sm3 respectively. The results for 5-year forecast are
illustrated in Figure 59 below:
Figure 59: Field production forecast for 5 years
4.4.7.1 Expected Ultimate Recovery (EUR) and Recovery Factor (RF)
Based on the static model, the STOIIP is 420 x106 sm3. The EUR is obtained from the
field production forecast for 5 years and 10 years respectively. The recovery factor is then
obtained from the ratio of EUR to STOIIP. The Table 22 below shows the EUR and
recovery factor.
Table 22: Expected Ultimate Recovery and recovery factor
Forecast Period
EUR (sm3)
Recovery Factor
(%)
5 years
60844700
14.5
10 years
92995192
22.1
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4.4.8 Enhanced Oil Recovery (EOR) Considerations
4.4.8.1 Enhanced Oil Recovery (EOR) screening
Enhanced oil recovery (EOR) can be defined as any method that increases oil production
by using techniques or materials that are not part of normal pressure maintenance or water
flooding operations. At a first stage, production hydrocarbons flow to the production wells
naturally and ascent to the surface along the well due to usually high reservoir pressures.
However, pressure in the reservoir decreases as time passes. Therefore, a prolongation of
production may be accomplished by EOR method. EOR can begin after a secondary
recovery process or at any time during the productive life of an oil reservoir. EOR method
is considered as tertiary recovery in Gullfaks reservoir management plan. In order to
ensure the success of EOR method, the available methods were screened according to the
fluid and reservoir properties. Below are the reservoir and fluid properties of Gullfaks
field.

Reservoir Pressure : 2516 psia

Reservoir Temperature: 220 ⁰F

Oil Viscosity : 1.33 cp

Formation Type : Shaly sandstone

Depth : 1701 mTVDSS
The main objective of EOR process is to mobilize the residual oil throughout the entire
reservoir. The process of enhancing microscopic oil displacement and volumetric sweep
efficiencies may be achieved. EOR by using CO2 injection is a technology where CO2 is
injected into oil fields under high pressure and behaves as a solvent to drive additional oil
from the geologic formation to production wells. At the end of the process, a portion of
the injected CO2 remains in the oil field where it remains isolated from the atmosphere by
the same geological materials that originally contained the oil.
107
Figure 60: CO2 injection (left) and EOR production well (right).
Based on the Gullfaks Field, the reservoir has a good quality, however, it is found that the
field is very faulted. The recovery factor without CO2-EOR is 58+% (Kaarstad, 2008).
EOR has used 5 mill ton/yr. for a 10 year period evaluated whereby about 30 mill m3
additional oil (as seen at the time of evaluation). For the EOR, it is found to be very costly
because CO2-handling equipment on 3 platforms (1 million offshore work hours). For
EOR, assumptions of future oil prices are very important (Figure 61). North Sea oil fields
will face a financial gap that must be covered if CO2.
Figure 61: Assumption of future oil prices
108
4.4.8.2 CO2 Injection in Gullfaks
CO2 flooding should be used in moderately light-oil reservoirs (API gravity more than 25)
and the reservoir should be deep enough to have high pressure to achieve miscibility. CO2
can dissolved in water, thus it can lower the interfacial tension between oil and water.
A fairly wide range of crude oils and reservoir depths can meet the requirements for
miscible CO2 flooding. The density (and therefore the solubility of CO2 in oil) decreases
with temperature, so the MMP required for given oil must increase with higher
temperature. Since the reservoir temperature normally increases with depth, the MMP
must also increase with depth. The pressure required to fracture the reservoirs increases
much faster than temperature with depth. Therefore, there is an MMP “window of
opportunity.” CO2 flooding is carried out by injecting large quantities of CO2 (30% or
more of HCPV) into the reservoir. CO2 will extract the light to intermediate components
from the oil and displace the oil to the producer. Comparing immiscible and miscible,
miscible process is more effective as it would reduce the irreducible oil saturation. In CO2
gas injection, it could be immiscible or miscible. This depends on the reservoir pressure
and temperature to reach minimum miscible pressure for miscible CO2 as shown in Table
24 below:
Table 23: Oil Gravity and Amount of Depth Needed
Oil Gravity, API Depth must be greater than (ft)
>40
2500
32 to 39.9
2800
28 to 31.9
3300
22 to 27.9
4000
<22
Fails miscible, screen for immiscible
109
Table 24: CO2- miscible flooding and Immiscible CO2 flooding
CO2-miscible flooding
Oil Gravity, ⁰API
Depth must be greater than (ft)
>40
2500
32 to 39.9
2800
28 to 31.9
3300
22 to 27.9
4000
<22
Fails miscible, screen for immiscible*
Immiscible CO2 flooding
13 to 21.9
1800
<13
All oil reservoirs fail at any depth
At < 1,800 ft. all reservoirs fail screening criteria for either miscible or immiscible
flooding with supercritical CO2. Carbon dioxide (CO2) is injected into a reservoir to
increase production by reducing oil viscosity and providing miscible or partially miscible
displacement of the oil. This method belongs to an enhanced oil recovery method,
meaning that it can recover the immobile oil to improve the efficiency. The downside is
that the method is costly and the cost fluctuates with the price of gas. In addition is there
no reliable source in Norway that is big enough, and CO2 that is not used has to be stored
in a safe manner. The lack of a reliable source puts CO2–injection below WAG and huffand-puff injection (J. & Bachu S, 2002) .
110
For future EOR consideration, there are two factors that is suggested to be recommended
which as following:

Current Oil-in-Place
A reliable estimate of the current Sor is should be the most important criterion in
deciding whether to go for an EOR process. Obviously, a high Sor is often
desirable, although such is usually not the case. As a rule-of-thumb, Sor > 0.35 is
desirable for most EOR processes.

Economic, geo-political and management policy criteria
Current oil prices and future geo-political scenarios should be considered in
making the decision to go ahead with EOR investments. For example, if the oil
price remains at its current low level, there is less chance of any chemical flooding
getting widespread field applications. However, government incentives such as tax
and royalty holidays may change the decision.
111
4.5 Reservoir Management
An integrated and comprehensive surveillance and monitoring program need to be
commenced since the early stage of production. The main reservoir management
objectives on Gullfaks have been to maximize profit for the owners, exploit resources to
a highest level possible, secure safe and long term workplace, and execution of activities
without causing any harm or damage to the people, environment and the facilities itself.
Dedicated and coordinated efforts of various functional groups are very essential to
achieve these objectives.
The reservoir of Gullfaks Main Field is complex due to large number of faults and extreme
permeability contrast ranging from several Darcies in the Tarbert formation to milli-Darcy
in the Cook formation. The highly productive sands are poorly consolidated which causing
sand production problem. Some of the areas contain reservoir fluid with high Hydrogen
Sulphide (H₂S). Other than that, there are uncertainties related to structures, degree of
communication, extreme contrast in reservoir properties and effective control of sand as
well as H₂S pose a great challenge for reservoir management.
Despites all the challenges, the recovery factor on Gullfaks Main Field is high. A total of
335 Msm³ of oil has been produced so far, this high recovery factor is attributed to
effective reservoir management which involved conservation of reservoir energy,
implementation of simple and advanced strategies, systematic and sustained collection of
data together with continuous application of improved recovery techniques.
Energy conservation is achieved through water and gas injection. Simple and advanced
techniques like selective perforation of wells, sand control, zonal isolation, multi-target
wells, controlled drainage through DIACS technology, through-tubing drilling etc. for the
data collection part, it involves 3D and 4D seismic, core and well log, RFT/MDT pressure,
PLT, RST saturation, well completion, production and injection.
What is more, studies in improved recovery techniques have been conducted and some of
them being implemented like infill-drilling, water and WAG injections, polymer assisted
surfactant flooding, microbial injection and CO₂ injection. As far as concern, the current
112
IOR initiatives are expected to extend the production life of the field until 2030 and meet
the target recovery of 400 Msm³ of oil.
4.5.1 Reservoir Management Challenges and Strategies
The functional groups must constantly monitor the reservoir performance and always
ready to modify, thus implement the strategy based on new data, requirements and modern
technology applications. Always bear in mind, a flexible management strategy must be
implemented from the very beginning and able to make any critical adjustment or
justification when necessary.
Some of the challenges found in Gullfaks are as follows:

Complex geological structure
The reservoir contains many faults, therefore placing the wells in intended
reservoir intervals are challenging. The communication pattern among fault
segments is very uncertain. This makes difficulty in creating optimum drainage
and pressure maintenance strategy.

High permeability contrasts
The permeability in high permeable sands is as high as 10 Darcies (Tarbert
formation) while only few milli-Darcy in the low permeability zones (lower
Cook). This high contrast causes uneven fluid movement, pressure differential and
crossflow in difeerent zones. Later, this effects operational problems and will
result in poor recovery from poor permeablie zones. The biggest challenge is to
monitor while control production and injection of different reservoirs. Many wells
and well intervention operations are needed to attain satisfactory recovery factor.

Unconsolidated reservoir sand
Reservoir sands in the high productive reservoir are poorly consolidated.
Maximum sand production rate must be reduced after water breakthrough.
Effective sand control method is necessary to encounter this problem and maintain
oil production rate.
113

Hydrogen Sulphide (H₂S) content
Corrosive and harmful to the health and pollutes the quality of export gas,
unwanted in the processing systems. Massive water circulation creates favorable
conditions for H₂S generating bacteria especially the one close to the injection
wells at the oil producing zones. Therefore, effective handling of this harmful gas
is compulsory.
Among the strategies taken to overcome the challenges as summarized as below:

The main reservoir management efforts must be directed towards improving the
understanding of the reservoir complexity. Substantial flexibility was introduced
in the development stage in order to accommodate necessary changes to reflect the
current understanding based on structural and stratigraphic information, pressure,
well log, well productivity, fluid movement, well testing, and other data. The
location of new wells and their respective perforation intervals as well as
completion methods were optimized based on previous drilled wells data. Due to
extensive faulting, a large number of wells were drilled on the Gullfaks Field.
The platforms were developed with a total of 136 slots with more than 250 well
targets have been drilled. Dedicated producers and injectors are normally placed
in each reservoir unit. The producers are placed upflank on the structure while the
injectors are placed downflank closer to OWC within the same major fault block.
Long-reach highly deviated and horizontal wells have also been drilled to
penetrate more than one fault blocks. This method successfully reduced the
number of development wells, dependency on reservoir continuity and the need
for subsea development.

Several measures have been considered to counteract the large permeability
contrasts among different reservoir zones. In addition of drilling production wells
in each reservoir unit, selective perforation was used to balance production and
pressure support in different sands. Hydraulic fracturing was done at different
114
places to establish communication between high and low permeability zones. Long
horizontal wells were drilled in area with low production sands. Production
Logging Tool (PLT) were run routinely to obatain production profiles along
perforation intervals. Large number of well intervention operations was carried out
to shut-off the high water production intervals. This helps to improve sweep
efficiency and oil recovery from low permeability zones.

Sand control methods are applied in most of the production wells. Gravel packing,
chemical sand control, sand screens and propped hydraulic fracturing were among
the important sand control methods used in Gullfaks. Besides, monobore well
construction was used to facilitate gravel packing operations.

In order to remove H₂S from the well stream, a large amount of chemicals were
being used. Due to emission to water and treatment of bulk amount of chemicals,
the production from H₂S wells were reduced or periodically shut down to contain
from the contamination. The distance between injectors and producers also being
selected carefully. Biocide injection had been tried but there was no significant
effect. The mixing of nitrate in the injection water in 1999 had slowed down H₂S
development in the Lower Bent reservoir. A suction separator has been installed
in one of the platform, but it is still early to conclude the effect on H₂S regulation.
As a conclusion, the main focuses of the Gullfaks reservoir management have been
continuous collection of relevant data to minimize uncertainty, revision of management
strategies based on new data and knowledge, and application of simple, cost effective and
new technologies to maximize economic recoveries. This measures will continuously
being flexible and adjusted when necessary (Talukdar, 2008).
115
CHAPTER 5
CONCLUSION
The successful and solid measures in geology and geophysics, petrophysics and
reservoir engineering are essential in preparing the foundation before continue the project
plan into drilling engineering, facilities engineering, production technology, economic
analysis as and HSE considerations. The assumptions and considerations made after
reservoir engineering must to be confirmed before any decision making in later stage.
Discussion in periodic stage is important in plan execution later due to constantly
changing trends of the reservoir and may need to draw new strategies for the production
operation. The objectives to develop a technical study in maximizing hydrocarbon
production and recoverable hydrocarbon is achieved with total recoverable reserve of
60,844,700 for 5 years and 92,995,192 for 10 years of production respectively. The future
plan confident must be made as well as the collective efforts of the operators, drilling
contractors, service companies and special service to make the future planning possible.
116
REFERENCES
Hesjedal, A. (2013, July 16). Norwegian University of Science. Retrieved from
Department
of
Petroleum
Engineering
and
Applied
Science:
http://www.ipt.ntnu.no/~tpg5200/intro/gullfaks_introduksjon.html
J., S., & Bachu S. (2002). Screening, Evaluation and Ranking of Oil Reservoir Suitable
for CO2 Flood EOR.
Kaarstad, O. (2008). Creating a North Sea CO2 Value Chain. Statoil ASA.
Talukdar, S. (2008). Reservoir Management of the Gullfaks Main Field. SPE 113260.
Tollefsen, S., Graue, E., & Svinddal, S. (1992). The Gullfaks Field Development:
Challenges and Perspectives. Society of Petroleum Engineers (SPE).
117