Fall 2013
Saudi Aramco
A quarterly publication of the Saudi Arabian Oil Company
Integrated Technologies Yield Five Years of Excellent Performance:
A Unique Field Case Study
see page 2
First Successful Application of Limited Entry Multistage Matrix Acidizing in
Saudi Aramco’s Deep Gas Development Program: A Case Study for Improved
Acid Stimulation and Placement Techniques
see page 21
Journal of Technology
THE SAUDI ARAMCO JOURNAL OF TECHNOLOGY
Saudi Aramco
Fall 2013
A quarterly publication of the Saudi Arabian Oil Company
Contents
Integrated Technologies Yield Five Years of Excellent
Performance: A Unique Field Case Study
2
Orji O. Ukaegbu and Essam M. Al-Alyan
Development of an Automated Environmental
Monitoring System for Groundwater
7
Philip E. Reed and Daniel W. Beard
Innovative Process to Ensure Efficient Multistage
Fracturing Treatments
13
Ibrahim M. Hakami, Francisco A. Gomez, Khalid S. Asiri, Wassim
Kharrat, Fernando Baez, Eduardo Vejarano R. and Danish Ahmed
First Successful Application of Limited Entry Multistage
Matrix Acidizing in Saudi Aramco’s Deep Gas Development
Program: A Case Study for Improved Acid Stimulation and
21
Placement Techniques
Mahbub S. Ahmed, Dr. Zillur Rahim, Ali H. Habbtar, Dr. Hamoud A.
Al-Anazi, Adnan A. Al-Kanaan and Wael El-Mofty
Upgrading Multistage Fracturing Strategies Drives Double
Success after Success in the Unusual Saudi Gas Reserves 29
Mohammed A. Al-Ghazal, Saad M. Al-Driweesh and
Fadel A. Al-Ghurairi
Illuminating the Reservoir: Magnetic NanoMappers
40
Abdullah A. Al-Shehri, Dr. Erika S. Ellis, Jesus M. Felix Servin,
Dr. Dmitry V. Kosynkin, Dr. Mazen Y. Kanj and Dr. Howard K.
Schmidt
Field Evaluation of LWD Resistivity Logs in Highly
Deviated and Horizontal Wells in Saudi Arabia
48
Dr. Pedro Anguiano-Rojas, Douglas J. Seifert, Dr. Michael Bittar,
Dr. Sami Eyuboglu, Dr. Yumei Tang and Dr. Burkay Donderici
Integrated Geology, Sedimentology and Petrophysics
Application Technology for Multimodal Carbonate
Reservoirs
55
Roger R. Sung, Dr. Edward A. Clerke and Dr. Johannes J. Buiting
Integration of Static and Dynamic Data for Enhanced
Reservoir Characterization, Geological Modeling and Well
62
Performance Studies
Dr. Shouxiang M. Ma, Dr. Murat M. Zeybek and Dr. Fikri J. Kuchuk
Solid Particle Erosion in a Partially Closed Ball Control
Valve
Dr. Ehab Elsaadawy, Dr. Marcello Papini and Dr. Abdelmounam M.
Al-Sherik
70
Journal of Technology
THE SAUDI ARAMCO JOURNAL OF TECHNOLOGY
Integrated Technologies Yield Five Years
of Excellent Performance: A Unique Field
Case Study
Authors: Orji O. Ukaegbu and Essam M. Al-Alyan
ABSTRACT
This article covers the story of a field that was brought on
production using a combination of industry leading edge technologies: maximum reservoir contact (MRC) multilateral
wells, advanced well completions and intelligent field infrastructure. Though individual components of the technologies
had been tested and proven, the combination of these technologies
in one development made this field stand out as a first in the
industry. This feat came with particular challenges and rewarding opportunities.
This article undertakes an assessment of the field, the wells
and the technologies, following five years of production, in a
unique case study detailing real-time field and well performance
monitoring, management and production optimization. The
experience from this field has provided unique knowledge and
insight to better understand how the advantages of these technologies were leveraged to take performance to the next level.
During the five years of production, this field has met or exceeded the fundamental field key performance indices (KPIs),
such as production targets, sweep efficiency and well potential.
Moreover, the intelligent field infrastructure environment has
made possible proactive real-time reservoir management, leading to more efficient operations and results oriented business
workflows.
INTRODUCTION
Haradh is the southernmost production area in the super giant
field Ghawar. The Arab-D reservoir focused on in this article
produces Arabian Light crude oil. Haradh was developed in
three increments, Fig. 1, over a span of 10 years, and Haradh-III
is the last of the three increments to be developed. While most
parts of Ghawar were developed predominantly with vertical
wells decades ago, before recent advances in drilling and completion technology, the challenge in the Haradh-III development
was to leverage recent technology advancements1 to achieve
significant savings in development and operating costs per
barrel, with long-term sustenance of well productivity and
maximization of oil recovery.
The advances in technology presented development alternatives and ample opportunity to add value by building on
2
FALL 2013
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
Fig. 1. Map of Ghawar showing Haradh increments.
lessons learned from previous developments. The Haradh
increments were brought on production at 300 thousand barrels
of oil per day (MBOPD) each, but were developed with different
technologies. Haradh-I was developed in 1996 primarily with
vertical wells, and Haradh-II was developed in 2003 using single
lateral horizontal wells2. Haradh-III was developed in 2006
using a combination of industry leading edge technologies to
create the world’s largest field development with maximum
reservoir contact (MRC) multilateral wells, advanced well
completions and intelligent field infrastructure. Though individual components of the technologies had been tested and
proven, the combination of these technologies in one development made Haradh-III stand out as a first in the industry. This
feat came with particular challenges3, 4 and rewarding opportunities.
One of the main technology decisions for the Haradh-III
development was replacing many single lateral horizontal wells
with only 32 MRC multilateral wells to deliver 300 MBOPD
with substantial capital costs (CAPEX) avoidance. The initial
concerns were whether drilling technology1 had matured sufficiently to deliver the MRCs to plan; whether 32 MRCs were
sufficient to deliver the target production of 300 MBOPD
sustainably; and whether a huge price would be paid for the
advanced completions that might prevent future access to the
reservoir should frequent well intervention and workovers
become necessary to achieve project objectives.
After five years of continuous, uninterrupted production, the
pre-development concerns have been put to rest. The historical
data to date are being utilized to benchmark and evaluate the
performance of the various technologies deployed in the
Haradh-III development against project objectives and expectations set prior to field development and to assess their impact
on fluid behavior and sweep.
This article undertakes an assessment of the impact of the
various technologies deployed in Haradh-III in three broad categories — field and well performance; production optimization;
and real-time reservoir management — in relation to initial
concerns and expectations, and in comparison with Haradh-I
and Haradh-II, which were developed without these technologies.
TECHNOLOGIES DEPLOYED IN HARADH-III
DEVELOPMENT
It is not the intention of this article to delve into the operational
details of the deployment of the technologies and strategies
adopted in the development of Haradh-III, as numerous published SPE papers and journals have covered the subject. Suffice
it to say that the main focus of this article is on an evaluation
of the impact of MRC multilateral wells, advanced well completions (AWCs) and intelligent field infrastructure on overall
field performance. The AWC implemented in Haradh-III consists
of remotely operated chokes and inflow control valves (ICVs),
emergency shutdown systems and permanent downhole monitoring systems (PDHMSs), along with surface multiphase flow
meters (MPFMs).
The Haradh-III wells were completed with up-to-date
downhole and surface production technologies to control and
monitor well performance and optimize production and reservoir performance. Each oil well is connected to a MPFM,
allowing selective control and measurement of production rate
and phase fraction at various choke settings, including high
accuracy pressure and temperature measurements. The MPFM
is connected to the remote terminal unit (RTU), which collects
all well data and transmits them to the supervisory control and
data acquisition system (SCADA)5. All these technologies are
linked by the fiber optic based open transport network (OTN)
data communication system. The OTN together with the
SCADA, RTU, MPFM and AWC make up the intelligent field
infrastructure, which provides real-time data acquisition and
monitoring for quick decision making. Measurements of pressure and temperature, and oil, gas and water rates are carried
out in real time and transmitted to the data center and desktops
for prudent reservoir management and active reservoir surveillance to optimize reservoir performance.
required, thereby meeting one of the key performance indicators
(KPIs) and goals of the project. MRC multilateral wells have
been a major game changer, enabling Haradh-III to meet or
exceed project expectations. Trilateral and quad-lateral MRCs
deployed in Haradh-III have produced significant productivity
gains over single lateral horizontal wells, with savings in initial
development costs6. The large footprint of the MRCs has delivered higher productivity and an enlarged drainage area per
well, and target oil production rates have been sustained at
lower drawdown7.
Figure 2 compares the average sustainable rate per well of
Haradh-III with those of Haradh-I and Haradh-II. The average
sustainable rate per well in Haradh-III is five times the rate in
Haradh-I and more than twice the average sustainable rate in
Haradh-II. In addition to the productivity gains, the decline
rates observed in Haradh-III wells have been less than expected,
resulting in savings from drilling of maintain-potential wells.
Previous studies in Haradh-I and Haradh-II have shown that
reservoir heterogeneities, such as fractures, vugs and superpermeability stratiform, play a significant role in the fluid displacement process8, 9, and these perhaps were responsible for
water arrival in a few wells. This experience has been mitigated in Haradh-III due to the positive impact of the MRCs,
attributable to not only their large footprint but also the architectural design of the MRCs. The MRC wells operate at lower
drawdown to allow sweep and recovery by matrix dominated
by gravity displacement10, 11. In addition, the design of the
MRC1 allowed placement and cementing of the 7” liner section
inside the Arab-D reservoir, which perhaps isolated possible
fracture swarms and super-permeability streaks, thereby contributing to a more uniform sweep.
On all counts of well and reservoir performance indicators,
such as well productivity index (PI), well potential, field water
cut, the number of inactive producers and the number of wells
that experienced water breakthrough, Haradh-III has outperformed Haradh-I and Haradh-II at comparable periods in their
production life. To put this in perspective, Fig. 3 shows a comparison of Haradh-I, II and III in terms of the number of dead
wells (nonactive oil producers) after the first five years of production. So far there have been no dead wells in Haradh-III.
Haradh-I showed the greatest number of dead wells during its
first five years of production, primarily due to its development
IMPROVED FIELD AND WELL PERFORMANCE
Haradh-III was put on production during the first quarter of
2006 at an oil production rate of 300 MBOPD. Since coming
onstream, production has been sustained at target rates as
Fig. 2. Sustainable well rate after the first five years of production (MBD).
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
FALL 2013
3
Fig. 3. Number of dead wells after the first five years of production.
Fig. 5. Well optimization result (MBD), HRDH-A01.
Fig. 4. Field water cut after the first five years of production.
Fig. 6. Well optimization result (MBD), HRDH-A05.
with vertical wells with full bore penetration of all stratigraphic
zones, which consequently suffered early arrival of water12 in a
bottoms-up sweep pattern.
Figure 4 shows the average field water cut per increment after
the first five years of production. After five years of production,
Haradh-III is showing traces of water. During a comparable
period in the production life of Haradh-I and Haradh-II, they
showed three to four times the level of water compared to
Haradh-III. Given the similarities in rock quality and fluid
displacement mechanism among the three increments, the outperforming by Haradh-III in terms of the number of dead wells
and water cut behavior is attributed to the novel technologies
deployed in developing Haradh-III and the new business environment made possible by new technologies.
PRODUCTION OPTIMIZATION
To fully realize the benefits of a higher PI at a lower drawdown
made possible by the larger footprint of the MRCs, an AWC
was necessary to ensure that all laterals were contributing to
fluid flow into the wellbore and that cross flow was minimized. Downhole ICVs were installed in individual laterals of
the MRCs to control production and balance withdrawal from
individual laterals. This enabled the MRCs to achieve desired
withdrawals at lower drawdown in an environment of controlled
flood front advancement and consequently to minimize water
cut10, 13, 14.
AWCs have continued to be instrumental in the exercising of
prudent reservoir management controls on individual laterals
to optimize production and maximize well value. Production
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
optimization is now a routine reservoir management task, utilizing capabilities presented by the remote control of individual
laterals and real-time capture and measurement of production
rates and phase fractions from desktops. Recent examples of
well optimization efforts are shown in Figs. 5 and 6 on MRC
producers HRDH-A01 and HRDH-A05.
In both examples, the individual laterals were tested
through different downhole choke settings at a constant surface choke setting while recording measurements of oil and
water rates and bottom-hole pressures in real time. Thereafter,
an optimized choke setting was selected, resulting in substantial
oil gains and the reduction or elimination of water production.
In MRC HRDH-A01, after the optimization, the oil rate increased by 40% and water production was reduced to zero. In
MRC HRDH-A05, the post-optimization oil rate was 50%
higher and water production dropped by 50%.
REAL-TIME RESERVOIR MANAGEMENT
As part of the novel technologies implemented in Haradh-III,
every producer is connected to a MPFM, allowing selective
control and measurement of production rate and phase fraction
at various choke settings, including high accuracy pressure and
temperature measurements. The MPFM is connected through
the RTU to the SCADA. Integration of MPFMs into the intelligent field infrastructure has enabled accurate measurement of
production rates and proper production allocation for every
well, which is essential for proper reserves accounting and
prudent reservoir management.
The intelligent field infrastructure has enabled Haradh-III to
have a full-fledged capability of remote well control and monitoring. The ability to remotely open, close and control wells
through surface and subsurface sensors and to capture reservoir
performance information in real time has opened limitless opportunities for proactive and real-time reservoir management15.
The benefits have been multifaceted, from less human intensive
well interventions, to capturing and using real-time data from
wells and surface facilities for making timely production and
reservoir management decisions. The remotely operated chokes
and valves have made it possible to adjust well rates or shut-in
wells without the need for field support.
The Haradh increments are produced under pressure maintenance by peripheral water injection. The real-time measurement
and monitoring of rates and reservoir pressure has enabled
quick and timely adjustment of production and injection rates
as necessary to achieve the desired injection production ratio
in line with reservoir management strategy, all without the
delay attendant on the need to wait for back-allocated production injection data. In addition, pressure measurements from
the PDHMSs of numerous standing observation wells and also
from the PDHMSs of MRCs when they are shut-in on scheduled
maintenance provide continuous and reliable reservoir pressure
for routine monitoring.
The real-time data transmitted to data centers and desktops
have been customized to be displayed as a health check for
reservoir performance16. Real-time display of production and
injection rates by well and by reservoir — and also the display
of critical operational indices of the reservoir, such as total
number of active wells, shut-in wells, overproducing or overinjecting wells (compared to target), and underproducing or
under-injecting wells — has helped to track changes in reservoir
performance with time and ensure compliance of field operations
to set production priorities and injection production strategy.
Real-time capture of information combined with proactive
reservoir management has led to savings in operating costs and
the potential to lengthen the production plateau.
CONCLUSIONS
The Haradh-III development encompassed a combination of
industry leading edge technologies: MRC multilateral wells,
AWCs and intelligent field infrastructure. The novel technologies
deployed in the Haradh-III development have been costeffective, as evidenced by well and reservoir performance indicators, and have resulted in savings in development and operating
costs. During the five years of production, this field has met or
exceeded the fundamental field KPIs, such as production targets,
sweep efficiency and well productivity. The technologies provided a platform to utilize real-time capture of information for
prudent reservoir management controls on individual laterals
and wells to optimize production and maximize well value,
with the potential to lengthen the production plateau and
increase oil recovery. The experience from this field has provided
unique knowledge and insight to better understand how the
advantage of these technologies could be leveraged to take
performance to the next level.
ACKNOWLEDGMENTS
The authors would like to thank the management of Saudi
Aramco for their permission to publish this article. The authors
would also like to thank the ‘Udhailiyah Reservoir Management
Division and the Southern Area Reservoir Management
Department for their encouragement and guidance. We also
would like to acknowledge the contributions of many individuals
and peers from Saudi Aramco’s E&P community.
This article was presented at the SPE Saudi Arabia Section
Technical Symposium and Exhibition, al-Khobar, Saudi
Arabia, May 15-18, 2011.
REFERENCES
1. Al-Bani, F., Baim, A.S. and Jacob, S.: “Drilling and
Completing Intelligent Multilateral MRC Wells in Haradh
Inc-3,” SPE/IADC paper 105715, presented at the
SPE/IADC Drilling Conference, Amsterdam, The
Netherlands, February 20-22, 2007.
2. Mubarak, S.M., Pham, T.R., Shamrani, S.S. and Shafiq,
M.: “Using Downhole Control Valves to Sustain Oil
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3. Nughaimish, F.N., Faraj, O.A., Al-Afaleg, N.I. and AlOtaibi, U.F.: “First Lateral Flow Controlled Maximum
Reservoir Contact (MRC) Well in Saudi Arabia: Drilling
and Completion: Challenges and Achievements: Case
Study,” IADC/SPE paper 87959, presented at the
IADC/SPE Asia Pacific Drilling Technology Conference and
Exhibition, Kuala Lumpur, Malaysia, September 13-15,
2004.
4. Afaleg, N.I., Pham, T.R., Al-Otaibi, U.F., Amos, S.W. and
Sarda, S.: “Design and Deployment of Maximum Reservoir
Contact Wells with Smart Completions in the Development
of a Carbonate Reservoir,” SPE paper 93138, presented at
the SPE Asia Pacific Oil and Gas Conference and
Exhibition, Jakarta, Indonesia, April 5-7, 2005.
5. Al-Arnaout, I.H., Al-Zahrani, R.M. and Jacob, S.: “Smart
Wells Experiences and Best Practices at Haradh IncrementIII, Ghawar Field,” SPE paper 105618, presented at the
SPE Middle East Oil and Gas Show and Conference,
Bahrain, March 11-14, 2007.
6. Saleri, N.G., Al-Kaabi, A.O. and Al-Muallem, A.S.:
“Haradh III: A Milestone for Smart Fields,” Journal of
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Petroleum Technology, Vol. 58, No. 11, November 2006,
pp. 28-33.
7. Salamy, S., Al-Mubarak, S.M., Al-Mubarak, H., AlDawood, N. and Al-Alawi, A.: “Maximum Reservoir
Contact Wells: Six Years of Performance — Lessons
Learned and Best Practices,” SPE paper 118030, presented
at the Abu Dhabi International Petroleum Exhibition and
Conference, Abu Dhabi, U.A.E., November 3-6, 2008.
8. Al-Kaabi, A.O., Al-Afaleg, N.I., Pham, T.R., Al-Muallem,
A.S., Al-Bani, F.A., Hart, R.G., et al.: “Haradh-III:
Industry’s Largest Field Development with Maximum
Reservoir Contact Wells, Smart-Well Completions, and the
iField Concept,” SPE Production & Operations, Vol. 23,
No. 4, November 2008, pp. 444-447.
9. Pham, T.R., Stenger, B.A., Al-Otaibi, U.F., Al-Afaleg, N.I.,
Al-Ali, Z.A. and Sarda, S.: “A Probability Approach to
Development of a Large Carbonate Reservoir with Natural
Fractures and Stratiform Super-Permeabilities,” SPE paper
81433, presented at the Middle East Oil Show, Bahrain,
June 9-12, 2003.
10. Al-Mubarak, S.M., Pham, T.R., Shamrani, S.S. and
Shafiq, M.: “Case Study: The Use of Downhole Control
Valves to Sustain Oil Production from the First Maximum
Reservoir Contact, Multilateral, and Smart Completion
Well in Ghawar Field,” SPE Production & Operations,
Vol. 23, No. 4, November 2008, pp. 427-430.
11. Al-Arnaout, I.H., Al-Buali, M.H., Al-Mubarak, S.M., AlDriweesh, S.M., Zareef, M.A. and Johansen, E.S.:
“Optimizing Production in Maximum Reservoir Contact
Wells with Intelligent Completions and Optical Downhole
Monitoring System,” SPE paper 118033, presented at the
Abu Dhabi International Petroleum Exhibition and
Conference, Abu Dhabi, U.A.E., November 3-6, 2008.
12. Pham, T.R., Al-Otaibi, U.F., Al-Ali, Z.A., Lawrence, P.
and Van Lingen, P.: “Logistic Approach in Using an
Array of Reservoir Simulation and Probabilistic Models
in Developing a Giant Reservoir with Super-Permeability
and Natural Fractures,” SPE paper 77566, presented at
the SPE Annual Technical Conference and Exhibition, San
Antonio, Texas, September 29 - October 2, 2002.
13. Mubarak, S.M., Dawood, N. and Salamy, S.: “Lessons
Learned from 100 Intelligent Wells Equipped with
Multiple Downhole Valves,” SPE paper 126089,
presented at the SPE Saudi Arabia Section Technical
Symposium, al-Khobar, Saudi Arabia, May 9-11, 2009.
14. Al-Mubarak, S.M., Sunbul, A.H., Hembling, D.,
Sukkestad, T. and Jacob, S.: “Improved Performance of
Downhole Active Inflow Control Valves through
Enhanced Design: Case Study,” SPE paper 117634,
presented at the Abu Dhabi International Petroleum
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Exhibition and Conference, Abu Dhabi, U.A.E.,
November 3-6, 2008.
15. Al-Mubarak, S.M.: “Real-time Reservoir Management
from Data Acquisition through Implementation: ClosedLoop Approach,” SPE paper 111717, presented at the
Intelligent Energy Conference and Exhibition,
Amsterdam, The Netherlands, February 25-27, 2008.
16. Al-Dhubaib, T.A., Issaka, M.B., Barghouty, M.F., AlMubarak, S.M., Dowais, A.H., Shenqiti, M.S., et al.:
“Saudi Aramco Intelligent Field Development Approach:
Building the Surveillance Layer,” SPE paper 112106,
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Exhibition, Amsterdam, The Netherlands, February 25-27,
2008.
BIOGRAPHIES
Orji O. Ukaegbu has more than 20
years of diverse petroleum engineering
experience. He is currently a
Petroleum Engineering Specialist in the
Southern Area Reservoir Management
Department. Orji joined Saudi Aramco
in 2003 and has been involved in
management activities in South
numerous reservoir m
Ghawar, including the Haradh-III increment development.
Prior to joining Saudi Aramco, he worked for Shell in
Nigeria and the Netherlands.
Orji received his B.S. degree in Mechanical Engineering
from the University of Nigeria, Nsukka, in 1988.
Essam M. Al-Alyan joined Saudi
Aramco in 2005 as Reservoir Engineer
working in the Reservoir Management
Department. He has worked in
different assignments as a Production
Engineer and Reservoir Engineer,
handling fields of different maturity
complexity. Essa
Essam worked as a Reservoir Engineer for
and complexity
the Haradh-III increment, the world’s largest field
development with advanced well completions and
intelligent field infrastructure. Currently, he is working
with the Haradh-I increment, one of the most challenging
areas in the super giant field Ghawar.
Essam received his B.S. degree in Petroleum Engineering
from King Saud University, Riyadh, Saudi Arabia.
Development of an Automated
Environmental Monitoring System for
Groundwater
Authors: Philip E. Reed and Daniel W. Beard
ABSTRACT
INTRODUCTION AND BACKGROUND
Protection of groundwater resources in Saudi Arabia is of vital
importance as the Kingdom’s aquifers supply over 90% of the
water used in the country, and are essentially nonrenewable due
to the arid climate, and if impacted, can pose risks to human
health and the environment. As part of its corporate-wide
groundwater protection program, Saudi Aramco actively monitors shallow groundwater at many of its operating facilities,
primarily through a network of hundreds of groundwater
monitoring wells. Groundwater sampling and laboratory
analysis occurs on a periodic basis each year to monitor
changes in groundwater quality. Limited staff and laboratory
resources posed challenges in meeting this objective, and a
practical solution was required.
This article presents a solution to these challenges: the development of an automated, stand-alone measurement system
deployed in groundwater monitoring wells using a multi-parameter sensor array package. A key feature of the package is an
ultraviolet (UV) fluorescence sensor that can measure dissolved-phase aromatic hydrocarbons at microgram per liter
concentrations. In combination with data logging and wireless
capabilities, the deployed system enables real-time and remote
monitoring of groundwater quality from standard 4” diameter
monitoring wells.
Prior to field deployment, a series of laboratory bench-scale
calibration profiles was developed for the UV fluorescence
sensor to determine its sensitivity to typical Saudi Aramco
hydrocarbon streams. A complete prototype system was then
constructed and placed in an active groundwater monitoring
well.
This article discusses the results of the laboratory calibration and field evaluation, including performance monitoring of
individual array components, development of power budgets
to match data logging requirements with solar power generation, data transmission and remote system management via
Ethernet-to-wireless communications, and long-term system
performance in a harsh (high temperature, humid and dusty)
environment. The benefit of this system is that it allows for
automated (and more frequent) monitoring of sensitive and
remote areas, enabling prioritization of staff and laboratory
resources where they are needed the most.
Saudi Aramco’s Groundwater Protection Program incorporates
over 1,000 groundwater monitoring wells, covering nearly 60
operating facilities located throughout the Kingdom of Saudi
Arabia. Groundwater sampling and laboratory analysis must
occur on a periodic basis each year to monitor changes in
groundwater quality and identify any impacts that may pose
risks to human health and the environment. Limited staff and
laboratory resources posed challenges in meeting this objective, and a practical solution was required.
Our solution was to develop an automated monitoring
system incorporating an in situ ultraviolet (UV) fluorescence
sensor that can measure dissolved-phase hydrocarbons at
microgram per liter concentrations. This technology has recently become available and is sensitive enough to measure
volatile organic compounds at the concentration levels necessary to evaluate groundwater impacts. This technology can be
combined with wireless or General Packet Radio Service
(GPRS) capabilities and off-the-shelf data loggers to enable
real-time and remote monitoring of groundwater quality from
monitoring wells.
In the literature, applications of UV fluorescence for measuring hydrocarbons have been published in areas such as online wastewater treatment monitoring and closed-loop cooling
water systems1-4, but not for groundwater monitoring wells.
The intent of developing a groundwater monitoring system using this technology is not to completely replace conventional
groundwater sampling, but to enable early and real-time detection of dissolved-phase hydrocarbons as well as monitoring of
real-time, continuous changes in physical parameters, such as
temperature and water level. The system could also be used as
a tool to measure groundwater remediation progress. Less frequent groundwater sampling can then be instituted to verify
sensor data and to allow for periodic recalibration based on
well specific conditions.
CONCEPT AND SENSOR ARRAY SYSTEM
COMPONENTS
The objectives for developing an automated groundwater
monitoring system were to provide a monitoring platform that
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
FALL 2013
7
can operate in a remote or “stand-alone” environment for a
long period of time with minimal servicing, withstand harsh
weather conditions (high operating temperatures, high humidity and dust), be power independent, be sensitive enough to
reliably measure groundwater parameters of interest, including
dissolved-phase hydrocarbons at microgram per liter concentrations, and have the capability to transmit data in real time
from the remote location to the office.
With these objectives in mind, the conceptual design of the
system included the following:
• UV fluorometer capable of detecting dissolved-phase
hydrocarbons in the microgram per liter range.
• Water level sensor with atmospheric pressure
compensation (gauge).
beam is focused approximately 5 nm to 10 nm in front of the
window using a small lens. Emitted light is collected by the
same lens, reflected by the dichroitic beam splitter (due to the
longer wavelengths of the fluoresced light) and detected by a
large area photodiode. An interference filter (center wavelength 360 nm) is used in front of the photodiode to discriminate stray light and to select the fluorescence light.
In addition to using the UV fluorometer to detect hydrocarbons in the monitored groundwater well, other water quality
parameters are measured by the sensor array system, including
atmospheric pressure compensated water level (gauge pressure), groundwater temperature, conductivity and turbidity.
System battery voltage and data logger enclosure temperature
are also recorded.
• Temperature, conductivity and turbidity measurement
instruments.
UV FLUORESCENCE SENSOR CALIBRATION
• Programmable data logger.
The UV fluorescence sensor was factory calibrated by the manufacturer using a proprietary calibration standard. Note that
the amount of aromatic hydrocarbons in a liquid sample can
be determined and related to the total amount of hydrocarbon
present only if the ratio of aromatics to total hydrocarbons remains relatively constant. Should the ratio of aromatics to total hydrocarbons change due to different hydrocarbon product
streams, a new calibration should be established before field
deployment. In this study, the UV fluorescence sensor was recalibrated in the laboratory using typical Saudi Aramco hydrocarbon streams dissolved in water, e.g., using locally produced
laboratory standards of gasoline, diesel and Arab Light (AL)
crude oil.
One unique aqueous calibration standard was prepared for
Saudi Aramco gasoline, diesel and crude oil (three total calibration standards). The calibration standard apparatus was
assembled, and reagent grade water was added to the apparatus
before any hydrocarbon was introduced. The hydrocarbon/water interface layer was never penetrated, agitated, aerated or
disturbed after hydrocarbon was introduced to the apparatus;
however, the aqueous standard was gently mixed to encourage
hydrocarbon partitioning and mixing. Each calibration standard
preparation was allowed to equilibrate for several days prior
to testing. Calibration standards were prepared within sealed
containers to reduce evaporation of the hydrocarbon. Dissolved
phase saturated aqueous fractions were removed from below
the hydrocarbon/water interface to provide approximately
four liters each of the calibration standard for use in the recalibrated hydrocarbon solutions.
For the calibration solutions, the UV fluorescence sensor
was suspended inside a four liter glass beaker together with silicone sample tubing, Fig. 1. The tubing was placed alongside
the sensor window to enable sampling of water as close as
practicable to the sensor. All additions or subtractions of calibration standards and reagent grade water diluents were made
by reversible peristaltic pumps under the solution surfaces. The
calibration solution was stirred gently to mix, but was never
• Solar-charged 12 volt DC battery.
• GPRS or wireless telemetry capability.
The sensor array design included the selection of a miniature
UV fluorometer with dimensions that allowed its deployment
in a 4” diameter groundwater monitoring well. Aromatic hydrocarbons dissolved in water can be stimulated with UV light
to fluoresce. Aromatic compounds in petroleum hydrocarbons
are known to be excited by monochromatic UV light and emit
fluorescent radiation at different wavelengths, according to the
number of aromatic rings present in the compound. Generally,
larger aromatic molecules fluoresce at longer wavelengths. A
relationship results between the aromatic composition of a
petroleum product and the maximum peak fluorescence wavelength. For example, fluorescence from gasoline emits with a
strong single peak at 290 nm, which represents single-ring
mono-aromatics. Fluorescence from diesel emits with its
strongest peak at 320 nm, representing the two-ring di-aromatics.
Peaks at 350 nm, 410 nm and 480 nm represent even larger
aromatic ring compounds. As a result of this relationship, ratios
of fluorescence wavelength peak intensity can distinguish different products. Beer’s Law governs the direct relationship between
the concentrations of the aromatic hydrocarbons in a given
sample (e.g., water) and the amount of UV radiation absorbed
at a specific wavelength. The intensity of the fluorescence
emission is proportional to the concentration of fluorescing
hydrocarbons dissolved in the groundwater.
The sensor used in the array excites the hydrocarbons by activating a miniature 2.5 Hz xenon flash-lamp behind an optical
window. The required wavelength for excitation is selected via
an interference filter centered at 254 nm with a full-width halfmaximum (FWHM) of 25 nm (or 254 nm ± 12.5 nm), detecting
an emission light at 360 nm with a FWHM of 50 nm (360 nm
± 25 nm). A small percentage of the excitation light is reflected
by a dichroitic beam splitter and is used as a reference signal to
evaluate variations of the excitation energy. The excitation
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
Fig. 1. Laboratory calibration apparatus configuration.
agitated, aerated or disturbed. The sensor and sample tubing
point were placed about 10 cm above the bottom of the
beaker, which was placed over a magnetic stirring plate. Black
nonreflective paper was placed beneath the bottom of the
beaker to reduce reflection errors. Room lighting was switched
off prior to powering up the laboratory instruments to reduce
signal noise effects (controller/data logger and sensor).
The UV fluorescence sensor was connected to a controller/
data logger equipped with a liquid crystal display showing raw
analog output. Calibration solutions were slowly introduced
into the system using the peristaltic pump. Once the sensor
analog output reading stabilized and was recorded, a calibration
solution sample was obtained by reversible peristaltic pump,
filling 125 ml and 40 ml volatile organic analyte (VOA) amber
glass sample bottles. A minimum of one tubing volume was
purged prior to sample collection (providing a sample that
originated as near the sensor detector window as possible).
Additional reagent grade water was added by reversing the
peristaltic pumps, adding and remixing the calibration solution,
and resampling to establish data to prepare calibration graphs
of hydrocarbon concentrations vs. data logger output. Each
time the calibration solution was diluted, and after the data
logger output stabilized and was recorded, the next laboratory
sample was obtained. This process was repeated a total of four
or five times to obtain data points over a sufficient concentration
(output) range to enable reproducible calibration trend line
generation.
Sample bottles were preserved by refrigeration to less than
4 °C and transported to an analytical laboratory for chemical
analyses of total petroleum hydrocarbons (TPH) ranges (C6C9, C10-C14, C15-C28, C29-C36) by USEPA method 80155 and
analyses of volatile organic compounds (VOCs) by USEPA
method 8260. Specifically, the VOA analyses were performed
to evaluate for the presence of benzene, toluene, ethylbenzene
and xylenes (BTEX) in the calibration solutions.
Calibration plots were developed relating UV sensor millivolt (mV) output vs. laboratory determined TPH and BTEX
for each of the calibration solutions evaluated. For the gasoline
calibration solution, the UV fluorescence was very sensitive for
TPH (C6-C9), reaching the upper limit of sensor raw analog
Fig. 2. Gasoline and diesel calibration, TPH.
Fig. 3. AL crude calibration, TPH.
Fig. 4. AL crude calibration, BTEX.
output at TPH concentrations under 200 micrograms per liter
for this carbon range, Fig. 2. Laboratory results for BTEX
compounds were non-detectable at this low TPH range. For
the diesel calibration solution, TPH (C6-C9) response plotted
against sensor mV output produced a fairly linear fit, Fig. 2;
however, the TPH plot (C10-C14) was linear only above a concentration range of about 1,000 to 1,500 micrograms per liter.
The TPH (C10-C14) range may indicate sampling and/or laboratory error or nonlinearity at lower concentrations. Higher
carbon ranges (C15-C28, C29-C36) were below the lower limits
of determination (below 0.1 milligram per liter), and as with
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gasoline, the BTEX constituents were non-detectable at this
low TPH range.
The AL crude solution calibration results, Fig. 3, exhibited
linear responses for TPH (C6-C9), TPH (C10-C14), and TPH
(C15-C28), but TPH (C29-C36) responses were nonlinear.
Separate BTEX constituents were detected and graphed vs.
analog output, Fig. 4.
ARRAY ASSEMBLY AND FIELD DEPLOYMENT
Once the UV fluorometer was calibrated, system components
were assembled into a configuration that allowed for deployment into a 4” diameter groundwater monitoring well. The
monitoring well selected was screened across the water table,
which was present at 1.5 m below ground surface.
Groundwater parameters at the well were recorded with a
calibrated YSI-556 multimeter prior to sensor array deployment and consisted of a temperature of 27 °C, total dissolved
solids content of 19.4 g/l, pH of 7.0, conductivity of 29.8
mS/cm and dissolved oxygen of 0.03 mg/l. The well was located approximately 300 m from the seashore adjacent to a
wastewater evaporation pond. Water levels fluctuated approximately 8 cm per day due to a semi-diurnal tidal influence.
Figure 5 illustrates the system installed at the monitoring
wellhead, including an environmentally sealed fiberglass enclo-
Fig. 5. Sensor wellhead configuration.
Fig. 7. Control box with data logger, RF modem, 12 volt DC battery and keypad.
sure, a 20 watt solar panel and a Yagi-type directional antenna
mounted on a post above ground level. The sensor array, including the UV fluorometer and sensors measuring water level
temperature, conductivity and turbidity, is shown in Fig. 6.
The sensor array was suspended by a length of rope attached
to the wellhead; cables from the sensor package were routed to
the enclosure. Figure 7 shows the inside of the enclosure that
houses the data logger, power supply (12 volt DC battery) and
a 2.4 GHz wireless modem.
Communications with the data logger were by wireless RF
modems. The base station antenna is located on a tall building
2 km away from the field station. A serial device server is used
to interface the RF base station modem to the facility Ethernet.
Com port redirector software is used to create a virtual serial
port connection on a dedicated workstation to collect data
hourly (during daylight hours only) from the field station.
Prior to installation of the sensor package into the monitoring well, a 0.375” internal diameter section of Teflon-lined
polyethylene tubing was affixed to the UV fluorometer with
the end of the tubing located near the optical window. The
tubing was extended up to the top of the well. This provided
the ability for groundwater sampling via a peristaltic pump
connected to the tubing at the surface. The sample tubing end
essentially coincided with the location of the UV fluorometer
instrument window. The UV fluorometer was placed at the
bottom of the array in tandem with the pressure transducer, at
a depth of approximately 2.2 m below the top of the groundwater in the screened section of the monitoring well.
POWER MANAGEMENT AND DATA TRANSMISSION
Fig. 6. Sensor array well package.
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
Overall system power requirements are very low primarily due
to the selection of components, but also because of the measurement strategy employed with the use of switched sensor
power. The UV fluorescence hydrocarbon sensor has a maximum
Fig. 8. UV fluorometer sensor output, in calibrated TPH.
current drain of ~300 mA while measuring. Other sensors consume approximately 50 mA during measurement. The wireless
modem consumes between 35 mA and 75 mA while communicating with the base station, depending on whether it is transmitting or receiving. It has an average quiescent current drain
of about 4 mA with a half-second cycle, during which it can
respond to a communication attempt from the base station.
To minimize system power requirements, the wireless modem was only powered on during daylight hours. Additionally,
since changes in groundwater well conditions occur slowly,
measurements were made only once hourly for the UV fluorometer and once every 10 minutes for the other water quality
parameters.
Data collected from the field station are written to an ASCII
text file on the workstation. The data from the text files are
automatically read and inserted into a relational database
management system using stored procedures and scheduling.
Excel™ spreadsheets and other applications have been developed to access the data for visualization and reporting purposes. For the UV fluorometer, data was plotted in mVs,
factory calibrated micrograms per liter and calibrated micrograms per liter Saudi Aramco gasoline, diesel and AL crude oil
products. For the remaining sensors in the array, time series
plots were also developed for conductivity, water depth, water
temperature and turbidity. Battery voltage and control panel
temperature readings with time were also plotted to monitor
power draw and environmental conditions.
FIELD PERFORMANCE
The system was allowed to operate with essentially no maintenance to observe its robustness and performance in high temperature, high humidity and dusty conditions. Based on the
data transmitted back to the office desktops, each sensor performed within specifications with the exception of the sidelooking turbidity sensor, which was giving erroneous output
due to the restricted space inside the 4” diameter well.
During the first 21 months of array operation, no detectable
hydrocarbons were noted by the UV fluorometer. At that time,
an increase in sensor output from 400 mV to over 850 mV
Fig. 9. Field sample comparison with TPH calibration.
was noted, Fig. 8. To validate the elevated readings, triplicate
groundwater samples were collected via the tubing using a
peristaltic pump and submitted to an analytical laboratory for
chemical analyses of TPH ranges (C6-C9, C10-C14, C15-C28,
C29-C36) by USEPA 8015 method and analyses of VOCs under
the USEPA 8260 protocols. At the time the samples were collected, the UV fluorometer sensor output was averaging 675
mVs and the TPH results for the C6-C9, C10-C14, C15-C28 and
C29-C36 ranges for the triplicate samples averaged 526 micrograms per liter, 277 micrograms per liter, 2,233 micrograms
per liter and 260 micrograms per liter, respectively. Figure 9
illustrates the comparison of the field samples with the calibration plots for TPH.
After approximately 23 months of sensor array operation, a
degradation of conductivity readings was noted, indicating
that sensor cleaning was required. At this time, the sensor
package was removed from the well to enable observation of
visible signs of corrosion or fouling. The UV fluorometer window was clear with no signs of fouling. The conductivity sensor
was brushed clean and the desiccant for the vented pressure
transducer was also changed. No other serious signs of fouling
or corrosion were noted.
When the measurement scheme was developed, it was expected that accumulated terrestrial dust on the solar panel
might not adequately charge the 12 volt DC battery. This situation has not been the case in over two years of monitoring
with only one intentional rinsing of the solar panel. The system
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11
battery voltage has not fallen below 12.5 volts during the
entire deployment period.
CONCLUSIONS AND FUTURE APPLICATIONS
As demonstrated in the laboratory calibration and field trials,
aromatic hydrocarbon fluorescence is extremely sensitive to
hydrocarbons in water, and results indicated a linear response
across the concentration ranges tested. The deployed system
continues to perform superbly in the high temperature, high
humidity and dusty conditions prevalent in Eastern Saudi
Arabia. Planned future modifications to the array include
changing the side-looking turbidity sensor with a look-down
type sensor, which has recently become available on the market.
Periodic groundwater sampling from the tubing installed near
the sensors will continue to occur to compare sensor output to
laboratory analytical results.
Future deployment of similarly designed sensors in different
groundwater conditions is planned to observe UV fluorometer
response in differing groundwater chemistries. Other potential
applications include leak detection monitoring where the system can be installed in shallow groundwater conditions near
storage tanks, sumps, piping, etc., in remote areas, and in deep
groundwater conditions.
ACKNOWLEDGMENTS
The authors would like to thank Saudi Aramco management
for their permission to present and publish this article. Special
thanks to Mr. Harry Day, retired Engineering Specialist with
the Environmental Protection Department, for his contribution
during instrument calibration.
A version of this article was presented at the SPE/APPEA
International Conference on Health, Safety, and Environment
in Oil and Gas Exploration and Production, Perth, Australia,
September 11-13, 2012.
REFERENCES
1. Borsdorf, H. and Roland, U.: “In Situ Determination of
Organic Compounds in Liquid Samples Using a Combined
UV-Vis/Fluorescence Submersible Sensor,” International
Journal of Environmental and Analytical Chemistry, Vol.
88, No. 4, April 10, 2008, pp. 279-288.
2. Meidinger, R.F., St. Germain, R.W., Dohotariu, V. and
Gillispie, G.D.: “Fluorescence of Aromatic Hydrocarbons
in Aqueous Solution,” Proceedings of the U.S. EPA/Air and
Waste Management Association International Symposium
on Field Screening Methods for Hazardous Wastes and
Toxic Chemicals, Las Vegas, NV, 1993, pp. 395-403.
3. Tedetti, M., Guigue, C. and Goutx, M.: “Utilization of a
Submersible UV Fluorometer for Monitoring
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
Anthropogenic Inputs in the Mediterranean Coastal
Waters,” Marine Pollution Bulletin, Vol. 60, No. 3, March
2010, pp. 350-362.
4. Westaby, C.: “Hydrocarbons in Water Monitoring Using
Fluorescence,” paper presented at the 30th Annual Electric
Utility Chemistry Workshop, University of Illinois at
Urbana-Champaign, June 8-10, 2010.
5. Test Methods for Evaluating Solid Waste, Physical/
Chemical Methods, SW-846, 3rd edition, U.S.
Environmental Protection Agency, Washington, D.C., 2008.
BIOGRAPHIES
Philip E. Reed is an Engineering
Consultant in Saudi Aramco’s
Environmental Engineering Division,
Land & Groundwater Protection Unit.
JJoining Saudi Aramco in 2002, he has
over 30 years of diverse experience in
environmental hydrogeology, including
characterizations, field instrumentation applications,
site characterizations
risk assessments, groundwater remediation design and
construction.
Phil received his B.S. degree in Geology from Rensselaer
Polytechnic Institute, Troy, New York, and his M.S. degree
in Geological and Civil Engineering from the University of
Arizona, Tucson, Arizona.
Phil is also a Registered Professional Engineer in
Arizona and California. He is an active member of the
Society of Petroleum Engineers (SPE) and has previously
been published in the Saudi Aramco Journal of Technology
and other publications.
Daniel W. Beard joined Saudi Aramco
in 2000 as an Environmental Specialist
in the Environmental Protection
Department’s Marine Environmental
Protection Unit. He previously worked
for industry, government, academic
and consulting organizations,
specializing in field sstudies, instrumentation, data automation and processing and database development.
Dan received his B.S. degree in Physical Science with an
emphasis in Atmospheric Science in 1980 from Northern
Arizona University, Flagstaff, AZ, and an M.S. degree in
Physical Oceanography from Texas A&M University,
College Station, TX, in 1984.
Innovative Process to Ensure Efficient
Multistage Fracturing Treatments
Authors: Ibrahim M. Hakami, Francisco A. Gomez, Khalid S. Asiri, Wassim Kharrat, Fernando Baez,
Eduardo Vejarano R. and Danish Ahmed
ABSTRACT
Multistage fracturing (MSF) is a common practice today as it
allows control of the stimulation of long intervals and improves
the ultimate recovery of hydrocarbons. MSF completions,
designed with open hole packers and frac ports, are currently
implemented by Saudi Aramco to control stimulation and improve recovery in gas wells. The integrity of the open hole
packer and the functionality of the frac ports are vital for an
effective fracturing treatment.
During a MSF treatment, the bottom frac port is opened
first by pressurizing the MSF completion to a predetermined
pressure. After the first fracturing stage has been pumped, a
ball is dropped to isolate the lower zone, open the second frac
port with pressure and enable the second fracturing stage. This
step is repeated until all frac ports have been opened and the
corresponding zones have been fraced, one after the other. At
every step of pressurizing the MSF completions, a drop in pressure is automatically interpreted as showing that the correct
frac ports are open and that the MSF completion is ready for
another fracturing stage. The open hole packers are also assumed
to be holding. Opening the wrong frac port or multiple frac
ports at the same time, or having a leaking open hole packer
will certainly lead to undesired results and possible expensive
remedial rig interventions. Therefore, downhole monitoring is
needed to confirm that the MSF completion is ready (i.e., the
correct frac ports are open and the packers are holding) before
every fracturing stage.
The fiber optic enabled coiled tubing (FOECT) system can
be used as a monitoring system by measuring the distributed
temperature survey (DTS), which can be interpreted in real-time
to confirm which frac port is open and if open hole packers are
sealing.
This article demonstrates through two case studies how DTS
was used to assess the readiness of the MSF completion for
proppant fracturing treatment. An innovative profiling process
in the MSF completion is proposed to replace assumptions
with measured facts, to give client confidence on when to start
the fracturing treatment, and to eliminate unnecessary operations by detecting any MSF completion hardware malfunction.
INTRODUCTION
Multistage fracturing (MSF) completions with mechanical
packers were developed in 2001. Since then, it is estimated that
more than 8,000 MSF treatments have been performed worldwide. Saudi Aramco has installed 17 MSF completion systems
since 2007 with the objective of producing gas from its unconventional and tight carbonate and sandstone formations1.
MSF completions are designed to segment the open hole
section into several compartments isolated with mechanical or
swellable open hole packers, Fig. 1, which also make the entire
MSF completion robust and permanent. Frac ports are placed
in between the open hole packers to enable hydraulic fracturing treatments of all compartments, one by one, starting from
the toe. The first frac port at the toe is opened by pressurizing
the MSF completion system to a predetermined value. Drop
ball mechanisms at each of the other frac ports are then activated,
one after the other, to isolate the previously fractured interval
and open the next frac port toward the heel to enable fracturing treatment of the stage. Each dropped ball is slightly bigger
than the previous one. The open hole packers and frac ports
are set according to the open hole log interpretation. The stage
lengths can vary from 200 ft to 1,000 ft. Open hole packers
are also placed without frac ports in between to isolate the
nonproductive zones. After completing all fracturing stages, a
total flow back and cleanup is usually performed.
The fracture geometry generated during a MSF job is affected
by the well azimuth. In fact, longitudinal fractures, Fig. 2a, are
created when the horizontal lateral is drilled toward the maximum stress direction (σH,max), while transverse fractures, Fig.
2b, are created when the horizontal lateral is drilled toward
the minimum stress direction (σH,min). For the latter case, several fractures can be placed one next to the other, as they are
Fig. 1. MSF completion assembly showing open hole packers and frac ports.
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Fig. 2a. Longitudinal fractures, σH,max.
DTS was used in the first MSF completion to confirm that it
was ready for the next fracturing stage and in the second one
to indicate that the well was showing a malfunction of its frac
ports. An innovative FOECT profiling process, based on the
real-time downhole DTS measurements, is proposed to help
the client decide to either proceed with or stop the fracturing
treatment.
TECHNICAL DETAILS
FOECT
Fig. 2b. Transverse fractures, σH,min.
independent of each other. In the former case, however, the
fracture from one interval can grow into the next or previous
zones.
The reservoir contact area increases with the number of
fractures in a MSF completion, which would enable long-term
sustained productivity. But this advantage can be completely
lost should the MSF completion components malfunction. In
fact, below are some scenarios that would call for a workover
rig to recomplete the well:
• The open hole packers fail to seal properly during the
installation of the MSF completion system.
• Multiple or wrong frac ports are open when
pressurizing the MSF completion system.
Below are additional scenarios that would eliminate some
fracturing stages:
• The open hole packers are leaking after an acid
fracturing job.
• One longitudinal fracture is overlapping neighboring
compartments.
The MSF completion is designed without any downhole
check of its components’ performance. It is just assumed that
only the correct frac port is open after pressurizing the completion and that the open hole packers are always sealing properly. Therefore, a downhole monitoring system is needed to
confirm that the MSF completion is holding before every fracturing stage.
A coiled tubing (CT) intervention is needed, first to displace
the wellbore before/after opening the first frac ports, then to
serve as a contingency for the activation or perforation of the
frac ports in the case of malfunction of the drop ball mechanism, acid wash, post-proppant fracturing cleanout, nitrogen
kickoff, and/or the milling of all the dropped balls at the end
of the operation2. The fiber optic enabled coiled tubing
(FOECT) system can improve the efficiency of all the above
interventions, besides the fact that the distributed temperature
survey (DTS) measured with the fiber optic cable will allow
real-time monitoring of the conditions of the frac ports and
open hole packers.
This article demonstrates through two case studies how
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The FOECT is a real-time surface readout system of downhole
measurements. It comprises fiber optic cables installed inside
an Inconel fiber carrier, which is injected inside the CT string,
fiber optic bottom-hole assembly (FOBHA), surface electronics
and software. The FOBHA is capable of measuring in real time
the bottom-hole pressure inside (BHPCT) and outside (BHPAnn)
the downhole tool, the bottom-hole temperature (BHT), casing
collar locator (CCL) and gamma ray (GR) signals, and the
tension-compression (TC) forces at the downhole tool. The
FOECT system allows operators to act with a greater degree of
precision based on real-time interpretation of measured downhole data, eliminating guessing and rule of thumb.
The real-time monitoring and interpretation of the downhole
data acquired from the FOBHA will enable operators to:
• Control the activation of the frac ports based on the
real-time measurement of the TC sub.
• Correlate the depths of the perforations/hydrajetting
slots based on the CCL/GR readings.
• Optimize the post-proppant fracturing cleanout based
on the BHPAnn.
• Optimize the nitrogen kickoff based on the BHPAnn.
DTS
The fiber optic cable acts as a continuous temperature sensor
throughout the length of the CT, which allows the taking of
real-time downhole distributed temperature profiles. The fiber
optic cable is installed in the CT inside an Inconel fiber carrier,
which is non-intrusive, allowing standard operations normally
done with conventional strings to be carried out, including
pumping corrosive fluids and dropping balls. DTS profiles are
recorded from the top of the well to the targeted depth by
sending 10 nanosecond bursts of light down the fiber optic
cable. During the passage of each packet of light, a small
amount is backscattered from molecules in the fiber. This
backscattered light can be analyzed to measure the temperature along the fiber. Because the speed of light is constant, a
spectrum of backscattered light can be generated for each meter of the fiber by the use of time sampling, allowing a continuous log of spectra along the fiber to be generated3.
During the bullheading of neutral fluid through the annulus
Well
Deviation
Tubing
MSF Completions
Frac Port
Open Hole Packer
A
Horizontal
4½” - 12,972 ft
4½” - 15,375 ft
Pressure activated
3½” OD ball
15,318 to 14,720 ft
14,720 to 14,328 ft
B
Slanted 30°
4½” - 12,855 ft
4½” - 14,440 ft
Pressure activated
3” OD ball
3¼” OD ball
3½” OD ball
14,337 to 14,127 ft
14,127 to 13,937 ft
13,937 to 13,817 ft
13,817 to 13,708 ft
Table 1. Data for gas Well-A and Well-B
CT, the temperature profile of the well can be monitored via
DTS. This profile will show some disturbance across the depth
of any open frac ports. In fact, wellbore temperature will decrease up to the injection point. After stopping the injection
and monitoring the warm-back of the wellbore, it can be observed that the profile across any open frac port interval will
take longer to recover heat, which is an indication of fluid intake in that zone. In the case of any failure in the open hole
packers, the temperature profile across will also clearly identify
disturbance in the profile due to flow in the backside. These
real-time downhole measurements will help to confirm if the
correct frac port is open and if the corresponding open hole
packers are sealing, making it safe to proceed with the fracturing stage. The DTS measurement will also provide the reservoir injection profile.
CASE STUDIES
The following case studies provide operational details of the
first implemented FOECT profiling jobs in Saudi Arabia. The
CT intervention objective was to displace the wellbore to brine
and assess the readiness of the MSF completion for fracturing
treatments.
Well Description
The two gas wells, Table 1, were completed with a MSF completion so as to perform segmented proppant fracturing of a
tight sandstone formation.
Job Design
The FOECT run was designed to complete the following steps:
• Run in hole (RIH) to tag the end of the MSF
completion.
• Displace the wellbore to the required brine.
• Pressure up the MSF completion system through CT to
the required pressure to open the first frac ports at the
toe.
• Take DTS-1 profiles while injecting brine through the
annulus CT.
• Take DTS-2 profiles after stopping the injection.
Fig. 3. DTS-1 injection profiles, Well-A.
• Confirm if the first frac port is the only one open and if
its corresponding open hole packers are sealing before
proceeding with the first fracturing stage.
The assessments of the MSF completion before the subsequent
fracturing stages were not approved at this time because the
CT run was not required before the fracturing treatment and
also because the confidence of the service companies in the
performance of their MSF completion was extremely high;
however, CT was available in case of any contingency purpose.
Job Execution — Well-A
After the wellbore was displaced to brine, the MSF completion4 was pressurized for many trials until a drop in pressure
was noticed at a much higher value than the one predetermined to open the pressure activated frac ports (frac port-1).
With the fiber optic cable in position across the first frac port
at the toe, an injection through the annulus CT was initiated
while taking the DTS-1 profiles every 5 minutes, Fig. 3. Then
the DTS-2 profiles were acquired every 20 minutes after stopping the injection to observe the warm-back response of the
wellbore, Fig. 4.
A sharp change in the slope of the DTS-1 profiles can be
observed by examining the sequence of these profiles over
time, Figs. 5 to 8. This change occurred at the depth of the first
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Fig. 4. DTS-2 warm-back profiles, Well-A.
Fig. 7. DTS-1 injection profile 3, Well-A.
Fig. 5. DTS-1 injection profile 1, Well-A.
Fig. 8. DTS-1 injection profile 4, Well-A.
Fig. 6. DTS-1 injection profile 2, Well-A.
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frac ports, with no disturbance of the slope across the second
frac ports. It can therefore be confirmed that the expected frac
port was open after the repetitive trials and that the abnormal
higher pressure was for activation of the port. Open hole packers 1 and 2 were determined to be sealing, as the DTS profiles
did not show any sharp disturbance across their depths.
The DTS-2 warm-back profiles confirmed the above
interpretations (the sealing of open hole packers 1 and 2) and
additionally allowed us to inquire about the zone injectivity
across the depths of frac port-1. The injectivity is low into the
zone between frac port-1 and open hole packer-2, while it is
better in the middle of the interval between frac port-1 and
open hole packer-1. Zones that take longer to warm-back are
associated with higher injectivity than a zone that recovers
temperature faster.
Based on the above real-time DTS measurements, it was
decided to pull the CT out of hole and proceed with the first
fracturing stage, which was performed successfully.
Job Execution — Well-B
After displacing the wellbore to brine and while pressurizing
the MSF completion5 to open the pressure activated frac port,
frac port-1, at the toe, it was noticed that there was already a
low injectivity to the formation. At this stage, the client decided to switch the CT services provider to mobilize a FOECT
unit and perform the required assessments to decide the way
forward. With the fiber optic cable positioned across all the
frac ports, a DTS-0 baseline profile was taken, Fig. 9. Next, an
injection through the annulus CT was initiated while taking
the DTS-1 profiles, Fig. 10. Then DTS-2 profiles were taken
after stopping the injection to monitor the warm-back response of the wellbore, Fig. 11.
A very sharp change in the last profile curve of DTS-1 was
Fig. 11. DTS-2 warm-back profile, Well-B.
Fig. 9. DTS-0 baseline profile, Well-B.
Fig. 12. DTS profile (track 2) vs. production logging tools logs (track 3), Well-B.
Fig. 10. DTS-1 injection profile, Well-B.
observed, Fig. 10. This clearly indicates that the injected fluid
was squeezed at the depth of the upper frac port, frac port-4.
Indeed, the interval above frac port-4 was cooling down while
the one below it was still warming up, compared to the DTS-0
baseline, as previously shown in Fig. 9. Another smaller
change in the slope was noticed at the depth of frac port-2,
with absolutely no disturbance of the slope across the pressure
activated frac port-1 at the toe. It can therefore be confirmed
that both frac port-4 and frac port-2 were open, while frac
port-1 was closed. The blind assumption of the MSF completion
provider that the injectivity noticed at the surface was into frac
port-1 was wrong. The DTS-2 profile, Fig. 11, shows the
warm-back results of the DTS after pumps were stopped, and
the cool spot remaining across frac port-4 confirmed the results
observed during DTS-1.
The MSF completion provider did not accept the DTS
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interpretations and asked the client to run a wireline production logging tool to try to confirm that the correct frac port
was open and all the upper three frac ports were closed.
After pulling out of hole, the same FOECT string was used
to run the wireline real-time production logging tools, without
the need to switch to an e-line logging reel or to call for a wireline unit. In fact, the FOECT system enables the connecting of
any real-time production logging tools below an electric-tooptical converter at the BHA level. The logging data gathered
with the FOECT acquisition system are displayed similarly to
a standard wireline format6.
The total downhole flow rate, measured in real time with
the production logging spinner tool (Fig. 12, track 3, green
curve), was clearly and definitely confirming the DTS interpretations as most of the injected fluid was squeezed into frac
port-4 while the remaining fluid was squeezed into frac port-2.
Based on the above facts, the MSF completion provider
acknowledged the malfunction of the frac ports.
FOECT PROFILING
After it was proved that the MSF completion components
could have mechanical malfunctions and that the DTS measured in real time with the FOECT system can detect these defects, the following innovative profiling procedure has been
proposed to confirm if the MSF completion is ready for the
next fracturing stage, and to optimize the design, execution
and evaluation of the fracturing treatment.
1. RIH with the FOECT string to tag the end of the MSF
completion.
2. Take a DTS baseline.
3. Displace the wellbore to the required brine.
4. Pressure up the MSF completion system through CT to the
predetermined pressure to open the first frac port at the toe.
5. Take DTS-1 profiles while injecting brine through the
annulus CT.
6. Take DTS-2 profiles after stopping the injection.
7. Confirm if the correct frac port is the only one open and if
its corresponding open hole packer is sealing.
8. In case of positive results, perform DataFRAC while taking
real-time measurement of the BHPann with FOBHA and
acquiring DTS profiles.
9. After the DataFRAC, take real-time measurements of the
BHT log and DTS profiles.
10. Adjust the fracturing design to optimize its execution
phase.
11. Pull the CT out of hole then perform the first fracturing
stage.
NOTE: It may be possible to keep a small outer diameter
FOECT in hole to monitor and adjust in real time the
execution of an acid fracturing treatment.
12. After the fracturing stage, RIH with the FOECT string to
perform DTS profiles to evaluate the job and assess the
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
isolation of the open hole packers after the treatment.
13. Open the next frac port toward the heel. This can be done
in one of three ways:
a. By dropping the required ball then pressurizing the
MSF completion.
b. With a contingency CT run using a special ball-shaped
BHA and a TC sub in the FOBHA to control the weight
on bit.
c. With a CT run using a special frac sleeve activation
BHA and a TC sub in the FOBHA.
14. Repeat steps 5 to 13 as needed.
CONCLUSIONS
1. The MSF completion components can experience some
mechanical malfunctions (case study of Well-B) that cannot
be detected without a real-time downhole monitoring
system.
2. The real-time DTS measured with the FOECT system is
needed to assess the downhole condition of the MSF
completion components, eliminate blind assumptions, and
confirm if the correct frac port is open and its open hole
packers are sealing so as to proceed with the fracturing
stage based on measured facts.
3. The DTS interpretations are consistent with the ones
obtained from production logging tools.
4. The FOECT profiling should be used not only to assess the
functionality of the first frac port at the toe of the MSF
completion, but also to confirm the readiness before every
fracturing stage.
5. The FOECT system can also be used to perform
DataFRAC and get real-time downhole measurements to
adjust the fracturing treatment design, optimize its
execution and improve its evaluation.
ACKNOWLEDGMENTS
The authors would like to thank Saudi Aramco and Schlumberger management for the permission to present and publish
this article. Special thanks go to all Saudi Aramco and Schlumberger operation team members who participated in these jobs
and made them successful.
This article was presented at the SPE Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi,
U.A.E., November 11-14, 2012.
REFERENCES
1. Rahim, Z., Al-Kanaan, A.A., Johnston, B., Wilson, S., AlAnazi, H.A. and Kalinin, D.: “Success Criteria for
Multistage Fracturing of Tight Gas in Saudi Arabia,” SPE
paper 149064, presented at the SPE/DGS Saudi Arabia
Section Technical Symposium and Exhibition, al-Khobar,
Saudi Arabia, May 15-18, 2011.
2. Al-Ghazal, M., Abel, J.T., Wilson, S., Wortman, H. and
Johnston, B.: “Coiled Tubing Operational Guidelines in
Conjunction with Multistage Fracturing Completions in the
Tight Gas Fields of Saudi Arabia,” SPE paper 153235,
presented at the SPE Middle East Unconventional Gas
Conference and Exhibition, Abu Dhabi, U.A.E., January
23-25, 2012.
3. Schlumberger: “The Essentials of Fiber Optic Distributed
Temperature Analysis,” 2005.
4. Finkbeiner, T., Freitag, H-C., Siddiqui, M., Woudwijk, R.,
Joseph, K. and Amberg, F.: “Reservoir Optimized
Fracturing — Higher Productivity from Low Permeability
Reservoirs Through Customized Multistage Fracturing,”
SPE paper 141371, presented at the SPE Middle East Oil
and Gas Show and Conference, Manama, Bahrain,
September 25-28, 2011.
5. Vargus, G., Howell, M., Hinkie, R., Williford, J. and
Bozeman, T.: “Completion System Allows for
Interventionless Stimulation Treatments in Horizontal
Wells with Multiple Shale Pay Zones,” SPE paper 115476,
presented at the SPE Annual Technical Conference and
Exhibition, Denver, Colorado, September 21-24, 2008.
6. Al-Buali, M.H., Shawly, A.S., Dashash, A.A., Stuker, J. and
Burov, A.: “Integration of Fiber Optic Enabled Coiled
Tubing System with Multiphase Production Logging Tool
for Remedial Work Candidate Evaluation,” SPE paper
148135, presented at the SPE Reservoir Characterization
and Simulation Conference and Exhibition, Abu Dhabi,
U.A.E., October 9-11, 2011.
BIOGRAPHIES
Ibrahim M. Al-Hakami is a Society of
Petroleum Engineers (SPE) certified
Petroleum Engineer who has 8 years
of experience with the Gas Production
Engineering Division of Saudi Aramco.
He is currently pursuing stimulation
technologies to maximize gas
production and meet the growing demand. Ibrahim
received the 2013 Southern Area Oil Operations
Innovation Award for the application of fiber optics as a
diagnostic tool for completion problems.
In 2005, he received his B.S. degree in Petroleum
Engineering from the University of Kansas, Lawrence, KS.
Francisco A. Gomez is a Petroleum
Engineering Specialist. Since joining
Saudi Aramco in 2005, he has been
working in the Southern Area
Production Engineering Department,
first in the Satellite Fields for the
Haradh Unit. He recently moved into
the R
Remote
Field
Gas Production Engineering Division
th
t Fi
ld G
with the South Haradh Production Engineering Unit. He
has over 30 years of experience in the oil and gas industry,
and his areas of expertise include production engineering,
reservoir engineering, simulation modeling, completions,
stimulation, field development and coiled tubing
operations. Francisco’s experience includes working for
Occidental de Colombia, Lagoven S.A., Corpoven S.A., BP
de Venezuela and AGIP de Venezuela (later named ENI de
Venezuela).
In 1983, he received his B.S. degree in Petroleum
Engineering from the University of Tulsa, Tulsa, OK.
Khalid S. Asiri is a Gas Production
Engineering Supervisor in the Southern
Area Production Engineering
Department. He worked with the
Ministry of Petroleum and Minerals
before joining Saudi Aramco in 2002.
Khalid has worked in several areas
within
the company, including Gas Production Engineering,
ithi th
Gas Well Completion and Services, and Reservoir and Gas
Drilling Engineering. He is currently serving in a supervisor
position for the Unconventional Stimulation Unit, which
covers all unconventional stimulation activities in tight gas
reservoirs.
Khalid received his B.S. degree in Petroleum Engineering
from King Saud University (KSU), Riyadh, Saudi Arabia, in
1999.
He is a member of the Society of Petroleum Engineers
(SPE) and the Saudi Council of Engineers (SCE).
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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19
Wassim Kharrat has been working
with Schlumberger since September
1998 in several countries around the
world, including Tunisia, Germany,
Libya, the United States and Saudi
Arabia. He built his technical and
operational expertise in coiled tubing
and
Currently, Wassim is working as a
d matrix
i stimulation.
i l i
Coiled Tubing District Technical Engineer in ‘Udhailiyah
with a focus on introducing and implementing ACTive new
technology (real-time monitoring with fiber optics) for all
types of coiled tubing jobs.
In 1998, he received his M.S. degree in Mechanical and
Industrial Engineering from École Nationale Supérieure
d'Arts et Métiers (ENSAM), Paris, France.
Fernando Baez joined Schlumberger in
2000. He is currently the ACTive
Domain Champion for the company’s
fiber optic enabled coiled tubing (CT)
service in Saudi Arabia, Kuwait and
Bahrain. Before this, Fernando was
part of the CT software team in Sugar
Land,
TX, serving
L
d TX
i as the Domain Expert. He has worked
with Schlumberger in various capacities that include field
operations in Colombia; Technical Instructor in Kellyville,
OK; coordination of fast track training of specialists in
Mexico; and Field Service Manager in the north of Mexico.
Prior to joining Schlumberger, Fernando worked for
Ecopetrol, a NOC in Colombia.
In 1999, he received his M.S. degree in Mechanical
Engineering from the Universidad de los Andes, Bogota,
Colombia.
Fernando has coauthored several patents and papers
related to his specialized field.
Eduardo Vejarano R. joined
Schlumberger in 2000 in the Coiled
Tubing segment. His experience
includes working as a Field Engineer
and then as an Engineer in Charge in
Colombia, followed by positions as a
Coiled Tubing Drilling Engineer and
Manager in western Venezuela. Eduardo
Field Services Manag
more recently was the Technical Engineer for Coiled
Tubing Drilling in Russia and then in Saudi Arabia. He
became the Account Manager for the Gas Production
Engineering Division (GPED) at Saudi Aramco, providing
technical support for coiled tubing operations.
In 1998, Eduardo received his B.S. degree in Mechanical
Engineering from Universidad de Los Andes, Bogota,
Colombia.
He has been a member of the Society of Petroleum
Engineers (SPE) since 2010.
20
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
Danish Ahmed is a Production
Technologist who began working at
Data and Consulting Services (DCS) in
Schlumberger-Saudi Arabia in 2007.
His experience involves working with
Well Production Services (WPS), based
in ‘Udhailiyah, supporting
proppant/acid
/ id ffracturing and matrix acidizing jobs.
Currently, Danish is working in the Consulting Services
group in DCS and is also supporting Coiled Tubing
Services (CTS) and its ACTive services.
In 2007, he received his M.S. degree in Petroleum
Engineering from Heriot-Watt Institute of Petroleum
Engineering, Edinburgh, Scotland.
First Successful Application of Limited Entry
Multistage Matrix Acidizing in Saudi Aramco’s Deep
Gas Development Program: A Case Study for
Improved Acid Stimulation and Placement Techniques
Authors: Mahbub S. Ahmed, Dr. Zillur Rahim, Ali H. Habbtar, Dr. Hamoud A. Al-Anazi,
Adnan A. Al-Kanaan and Wael El-Mofty
ABSTRACT
Among its various design and operating parameters, efficient
acid stimulation in deep carbonate reservoirs depends on the
placement technique, injection profile and treatment composition. Unlike acid fracturing, matrix acidizing creates several
conductive flow channels with substantially higher conductivity
compared to the reservoir rock. These conductive channels
transport reservoir fluids from the formation matrix directly
into the wellbore, overcoming both low permeability and near
wellbore damage. The treatment composition, and more importantly, the injection technique to maximize the number and
depth of penetration of these conductive channels are among
the most predominant design criteria of successful carbonate
matrix acidizing, especially in a high-pressure, high temperature
environment.
The Permian Khuff carbonate reservoir in the Ghawar
structure of Saudi Arabia produces nonassociated gas and condensate. The reservoir is characterized by heterogeneous
porosity and permeability distribution extending in both areal
and vertical directions, with varying in situ stress contrast
along the structure extension. Due to the reservoir complexity,
each well requires individual assessment to determine the optimum completion design to achieve efficient matrix and/or fracture acidizing treatment. Some wells may need only a simple
matrix acid treatment, while other wells may need open hole
multistage (OHMS) fracture stimulation. Results demonstrate
that OHMS completion was required in the example application well to successfully stimulate all net pay intervals.
This article presents an overview of Saudi Aramco’s efforts
to evaluate various stimulation methods used in the Khuff
reservoir and highlights an optimal carbonate stimulation technique for certain reservoir conditions via the successful application of a limited entry OHMS completion for effective
stimulation. The technique uses a system that is designed to
run as part of the production liner but also provides mechanical diversion at specified intervals, thereby allowing multiple
matrix acidizing treatments to be effectively placed in the target zones. The technique was successfully applied recently for
the first time in Saudi Aramco’s gas program, and the details
are discussed in this article.
INTRODUCTION
Saudi Aramco has been successfully exploiting its deep Khuff
gas reservoirs for the past decade with hydraulically fractured
vertical and horizontal wells in single and multiple stages1-5.
All Khuff gas producers need acid stimulation, either in terms
of matrix acid or acid fracturing, prior to connecting to the gas
plant. Matrix acid allows the removal of near wellbore damage induced during the drilling phase, while acid fracturing
opens up channels beyond the near wellbore region. Both improve the well productivity, but in relatively tighter porosity,
development acid fracturing provides the best opportunity for
well productivity enhancement. The Khuff reservoir is characterized by both vertical and areal heterogeneity with sub-layers
within the main Khuff formations. Over the past decade, a
good number of wells have penetrated this reservoir both vertically and horizontally, providing valuable information on its
characteristics. Stimulation of these wells often tips the balance
between challenges and opportunities for successful development of the nonassociated Khuff gas in the Kingdom.
KHUFF RESERVOIR
The Khuff formation represents the earliest major transgressive
Fig. 1. Khuff reservoir heterogeneity seen from open hole logs.
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carbonate deposited on a shallow continental shelf in Eastern
Saudi Arabia. The reservoir properties can vary significantly
due to the huge surface area that the reservoir covers. Rock diagenesis, dolomitization, leaching and other chemical changes
impact reservoir properties and fluid flow characteristics6.
The Khuff reservoir is a high pressure, high temperature
carbonate reservoir with two main gas-bearing layers: a tight
dolomite, Khuff-B, and a more prolific calcite, Khuff-C. The
reservoir exhibits extensive heterogeneity in stress, reservoir
quality and reservoir fluids throughout the field, Figs. 1 and 2.
This heterogeneity, combined with the deep and hot nature of
the reservoir, has made it a challenging task to achieve uniform
and effective stimulation of all layers2, 3, 7. Consequently, well
production potential can significantly fluctuate if treatments
are not optimized.
STIMULATION OF VERTICAL KHUFF PRODUCERS
In the early development program, Khuff producers were
drilled vertically and stimulated. The vertical wells were cased
with either a 7” or 4½” liner and cemented. The wells were
matrix acid stimulated with an injection pressure below the
fracture initiation pressure. This type of stimulation is used
mainly for wells possessing good reservoir quality. For wells
drilled in tighter reservoir sections, acid fracturing is required
to increase productivity. Typically, a single acid fracturing
across the perforated zones is sufficient. The perforation intervals are chosen based on the rock porosity and stresses, which
are calculated from the open hole logs calibrated by core and
diagnostic fracture injectivity test (DFIT) data4. The job’s final
Fig. 2. Khuff seismic shows variations in reservoir properties.
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
design is calibrated using pre-fracture injection parameters and
subsequent analysis. Generally, a successful stimulation treatment will generate a fracture half-length of 100 ft to 150 ft
and a fracture conductivity of 2,000 md-ft to 3,000 md-ft.
STIMULATION OF HORIZONTAL KHUFF PRODUCERS
As time progressed, wells began to be drilled horizontally.
Stimulation of horizontal Khuff producers takes different
courses depending on how the well is completed. If the horizontal well is completed open hole, and the reservoir development can be categorized as between moderate to good quality,
the well is simply stimulated by bullheading acid into the wellbore. In this process there is little control over the intervals
where the acid will penetrate. It is very likely that the high permeability intervals will be stimulated, leaving behind the low
permeability intervals. This type of acid stimulation, therefore,
may not be the preferred option. In barefoot completions,
however, where wellbore accessibility and stability can be challenging, bullheading acid to stimulate the well may be the only
option.
Horizontal wells completed open hole can also be stimulated with acid deployed by coiled tubing (CT). In this process,
acid is injected into the wellbore using CT, which means different intervals can be stimulated independently and selectively.
This type of stimulation falls under matrix stimulation rather
than acid fracturing.
In 2001, open hole multistage (OHMS) completions were
commercialized in North America to enable the segmenting of
long laterals for selective multistage fracturing (MSF) treatment of individual segments and subsequent isolation for zone
shutoff if required. The application of the OHMS completion
technology in Saudi Aramco started in 2007. The MSF equipment is deployed by the rig during the completion phase of the
well. Subsequently, acid fracturing is conducted in multiple
stages through the fracturing ports, which are activated by the
ball dropping mechanism, Fig. 3.
If the well is drilled in the maximum stress direction (σmax),
the first stage fracture will grow longitudinally parallel to the
wellbore toward σmax, causing the potential risk of overlapping with subsequent fractures. Initiation of the second and
third fractures can become a challenge due to possible pressure
communication across the first induced fracture8. Therefore,
the MSF may be changed to a single stage fracture followed by
additional stages of matrix stimulation.
To avoid fracture overlapping, wells need to be drilled in the
minimum stress direction (σmin), allowing the fractures to initiate
Fig. 3. Typical configuration of OHMS fracturing horizontal completion with
isolation packers and injection ports.
perpendicular to the wellbore. Drilling these wells toward
σmin, however, often poses drilling challenges, such as wellbore
instability and differential sticking. Adequate hole preparation
and drag modeling are needed to mitigate potential mechanical
sticking, while the 1D Mechanical Earth Model and its continuous calibration via real time geomechanics are needed to finetune drilling parameters to avoid breakouts or stuck pipe9.
Although drilling toward σmin is challenging, the improved
long-term sustained productivity and effective MSF treatment
it enables justify this strategy.
More recently, a trial test was successfully conducted in the
field implementing a novel stimulation technique that provides
limited entry, selective, multistage matrix acid stimulation.
DESCRIPTION AND FUNCTION OF THE LIMITED ENTRY
OHMS SYSTEM
Limited entry OHMS stimulation and matrix acidizing systems
function in a manner somewhat similar to standard OHMS
completion systems. Multiple stages are created using hydraulicset mechanical packers for isolation, Fig. 4, allowing for fracture
stimulation or straddling off of individual sections of a wellbore depending on reservoir characteristics and production targets. The difference with limited entry systems is that instead
of one fracture port per stage, multiple limited entry, shear
activated stimulation jets, Fig. 5, are installed to provide controlled leak off. This effectively places the desired treatment at
a constant rate and pressure along the stage length, thereby
maximizing the development of complex wormholes and
conductive channels along the stimulated reservoir length.
To stimulate each successive stage individually in the horizontal leg, both the liner and the annulus must be isolated. The
liner isolation is achieved by the actuation balls as they land on
their respective seats to isolate the stages below. Isolation of
the annulus is achieved using hydraulic-set mechanical, dual
element packers designed to withstand high differential pressures
during treatment cycles at reservoir temperatures. The design
of these packers feature a dynamic setting mechanism that continuously delivers additional packoff forces to the elements as
the treatment pressures increase over the initial setting pressure
inside the liner — a criterion that allows the packer to cope
Fig. 4. Hydraulic-set mechanical, dual element open hole packer.
Fig. 5. Stimulation jet.
Fig. 6. Single stage of a limited entry, multi-jet system.
with the sudden downhole temperature drop as colder treatment fluids are pumped from the surface.
Each stage consists of a drillable cutter assembly pinned
into a shear housing assembly. Below the shear housing are the
shear activated stimulation jet assemblies, spaced out with the
casing/liner at predetermined depths, Fig. 6. Above the lowermost packer in each stage is the locking/landing sub. Multiple
stages can be run, with the biggest ball size being at the top.
Pre-job Preparation
Stage engineering and segmentation is done after thorough
review and evaluation of the open hole logs recorded while
drilling or recorded post-drilling on wireline. Best practices
show that density neutron, porosity and resistivity data are
required as a minimum to determine formation fluids, permeability and other reservoir properties, while borehole caliper
logs are essential to determine wellbore geometry and to pick
the best locations for setting the open hole packers. At the end
of the logging program and prior to the limited entry, multi-jet
system deployment, a special reaming trip is performed using a
proprietary dual solid blade spiral reamer, which is designed to
mimic the dimensions and stiffness of the completion string.
This mitigates the risk of mechanical sticking and ensures
successful installation10, 11.
System Installation and Stimulation Operation
Once the approved deployment schematic is generated showing target setting depths for each system component and the allowable tolerance, a completion tally is designed with proper
space out, and the system is deployed to target depth. During
deployment, the system is open ended to allow circulation
through the liner to the bottom as per normal procedures.
After the completion assembly is run to the target setting
depth, a small ball is dropped from the surface and circulated
to the lowermost end of the completion assembly, where it
lands in the seat of a toe circulation sub and closes off the system. Surface pressure is then increased to set the liner hanger,
then further increased to set all of the open hole packers at
once, thereby segmenting the open hole lateral into predetermined stages for selective stimulation. The running tool is then
released and pulled out of the hole, leaving the multistage
lower completion set with a polished bore receptacle to connect with the upper completion, which is run on a lower seal
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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assembly to string into the liner hanger. The well is secured as
per the program, and the drilling rig is released.
Fracture stimulation starts by applying surface pressure to
open the lowermost hydraulically activated fracture port
(Stage-1) and establish direct injectivity into the reservoir rock,
Fig. 7. The DFIT and the main treatment are then performed
as per the Stage-1 program.
At the top of each successive stage above Stage-1 is a shear
housing/drillable cutter assembly that is opened by landing an
actuation ball in its ball seat. Once the actuation ball lands on
the appropriately sized seat, pressure increases in the liner.
When the activation differential pressure is reached within the
liner, the drillable cutter assembly shears off and moves down
the length of the stage to open each jet by cutting off its metal
pin. The drillable cutter assembly then lands in a locking/landing sub at the bottom of the stage, providing isolation from the
lower stages. Increasing ball and seat sizes allows for multiple
stages to be run in sequence; smaller incremental sizing of the
balls and seats allows for more stages without sacrificing the
minimum acceptable restriction inside the completion.
The balls are typically flowed back to the surface or rattle in
place for a short period until they mechanically or chemically
disintegrate, depending on the composition of the balls. If
necessary, the drillable cutter assembly can be milled out to
achieve a full liner inside diameter; the landing/locking sub
also features a locking profile to prevent the drillable cutter
from rotating during milling operations.
System Applications
The limited entry system described here is best suited for matrix acid treatments in prolific and naturally fractured carbonate formations. Matrix acid stimulation reduces the formation
damage (skin factor) caused during the drilling process and
enhances near wellbore conductivity for improved production.
Carbonates readily dissolve in acid. Therefore, by pumping
acid below fracture pressure into the wellbore, highly conductive flow paths known as wormholes are created that transport
reservoir fluids from within the formation matrix directly into
the wellbore, overcoming both low permeability and near
wellbore skin, Fig. 8. Additionally, these multistage, limited
entry multi-jet systems can be used in various configurations
depending on the desired completion strategy and lateral section management requirements. A full limited entry multi-jet
system or a combination of this with a standard OHMS system
configuration can be used to suit individual requirements, Figs.
9 and 10.
LIMITED ENTRY, MULTI-JET, OHMS COMPLETION IN
THE KHUFF
The Khuff wells’ completion and stimulation history shows that
based on the reservoir quality, almost every standard stimulation
technique has been used. This includes single bullhead acid
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
Fig. 7. Acid stimulation through a Stage-1 hydraulically activated fracture port.
Fig. 8. Acid stimulation through a limited entry, multi-jet system for effective
wormhole creation.
Fig. 9. The multistage, limited entry, multi-jet system uses a series of shear
activated jets to evenly distribute acid across the stimulation interval.
Fig. 10. A combination system allows for customized stimulation of the entire
wellbore in a continuous pumping operation.
treatment and CT acid wash in prolific reservoirs, cased hole plug
and perforation techniques through cemented liners, and OHMS
fracture treatments in low to moderate permeability intervals.
In relatively tighter formations, OHMS fracturing treatments are required to achieve an extended fracture half-length.
In relatively prolific reservoirs, where MSF treatments may not
be necessary, the choice is CT acid treatments vs. multistage
matrix acid. The multistage limited entry technique has shown
considerable success.
Accurate acid placement is a major concern in matrix
acidizing of prolific carbonates as the acid tends to flow preferentially where the permeability is highest, further increasing
local permeability at these intervals and leaving the lower permeability regions of the reservoir untreated. Industry experience
shows that a significant percentage of matrix treatments
around the globe do not meet expectations because of an
improper job design. In some cases, huge increases in water
production are observed after a stimulation job because the
acid may have preferentially stimulated the high permeability
sections associated with water.
Due to the rapid reaction of carbonates with acid, matrix
acidizing creates dominant wormholes through which the acid
flows with ease, leaving most of the pay zone unstimulated.
This cannot be avoided if the acid is simply bullheaded into the
well and allowed to find its own natural route. Some form of
combined mechanical and chemical diversion is necessary for
effective placement of the stimulation fluids to attain optimum
depth and complexity of wormholes, which will facilitate
hydrocarbon flow from the formation matrix to the wellbore.
EXAMPLE APPLICATION
A relatively prolific horizontal well, Well-A, was drilled geometrically parallel to the maximum principle stress plane,
σmax. The well was logged, and composite logs were carefully
analyzed for reservoir porosity development. The three-stage
OHMS limited entry, multiple injection port system, with six
limited entry injection ports per stage, was successfully deployed
to total depth in this 4,000 ft horizontal section, Fig. 11.
Matrix pumping was scheduled and performed as per the
approved treatment program. All system components functioned
as initially expected. The DFIT was performed for each stage,
and the main matrix acid treatments were pumped as per the
program.
Well-A was opened for cleanup and flow back, and the gas
rate was recorded, confirming stable production at a high productivity index (PI), Fig. 12. A comparison of well PI was done
with the two offset wells: one vertical well, which was acid
fractured in a single stage and one horizontal well, which was
matrix acid stimulated with CT. The well performance was
matched, and a wellbore skin was calculated. In this comparison, the limited entry, high rate, multistage matrix with a calculated skin of -3.4 outperformed the CT matrix acid well
with a calculated skin of -2.0. The vertical well with a single
stage acid fracture had the lowest PI with a calculated skin
of -5.7, Fig. 13.
CONCLUSIONS
The following conclusions have been drawn from the work
performed in the Khuff reservoirs.
1. Optimization of acid stimulation depends on the reservoir
quality and the well configuration. Saudi Aramco has
successfully implemented a holistic approach toward
planning and execution of OHMS in the Khuff wells.
Fig. 11. Wellbore configuration showing open hole logs, and packer and port
placements.
2. A novel approach to address the more prolific Khuff
intervals, where efficient matrix acidizing was sufficient to
meet expected well rates, was successfully implemented.
The limited entry OHMS completion has shown promising
results in its first application, although more testing is
required.
3. This stimulation technology is readily applicable to those
wells that have good reservoir development but require
near wellbore stimulation on large intervals.
4. This technique is not a replacement for traditional MSF in
moderate to tight gas reservoirs where deep penetration is
required. Acid fracturing through this current system may
be evaluated in the future.
ACKNOWLEDGMENTS
Fig. 12. PI stabilizes for Well-A.
The authors would like to thank the management of Saudi
Aramco for their permission to publish this article. Special
thanks and appreciation go to the Packers Plus and Schlumberger teams for providing close cooperation and assistance
during the initial modeling, implementation and presentation
phases of the limited entry, multi-jet OHMS completion
technology.
This article was presented at the SPE Saudi Arabia Section
Annual Technical Symposium and Exhibition, al-Khobar,
Saudi Arabia, May 19-22, 2013.
REFERENCES
Fig. 13. Comparing inflow performance of Well-A with various offset wells.
1. “2009-2012 Gas Program,” Saudi Aramco Gas Reservoir
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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25
Management Division Internal Documentation.
2. Rahim, Z., Al-Anazi, H.A., Al-Malki, B.H. and Al-Kanaan,
A.A.: “Optimized Stimulation Strategies Enhance Aramco
Gas Production,” Oil and Gas Journal, Vol. 108, No. 37,
October 4, 2010.
3. Rahim, Z., Al-Kanaan, A.A., Al-Anazi, H.A., Johnston, B.,
Wilson, S. and Kalinin, D.: “Open Hole Multistage
Fracturing Boosts Saudi Arabia Gas Well Rates,” Oil and
Gas Journal, Vol. 109, No. 23, June 6, 2011.
4. Al-Qahtani, M.Y. and Rahim, Z.: “A Mathematical
Algorithm for Modeling Geomechanical Rock Properties of
the Khuff and pre-Khuff Reservoirs in Ghawar Field,” SPE
paper 68194, presented at the SPE Middle East Oil Show,
Bahrain, March 17-20, 2001.
5. Rahim, Z., Al-Qahtani, M.Y. and Buhidma, I.: “Improved
Gas Recovery from Acid of Hydraulic Fracturing,” Saudi
Aramco Journal of Technology, Spring 2001, pp. 50-60.
6. Plumb, R.A.: “Influence of Composition and Texture on
Failure Properties of Clastic Rocks,” SPE paper 28022,
presented at the Rock Mechanics in Petroleum Engineering,
Delft, The Netherlands, August 29-31, 1994.
7. Rahim, Z., Al-Anazi, H.A., Al-Kanaan, A.A., Makmun, A.,
Fredd, C. and Gurmen, N.: “Evolving Khuff Formation
Gas Well Completions in Saudi Arabia: Technology as a
Function of Reservoir Characteristics Improves
Production,” SPE paper 163975, presented at the SPE
Middle East Unconventional Gas Conference and
Exhibition, Muscat, Oman, January 28-30, 2013.
8. Plumb, R.A., Edwards, S., Pidcock, G., Lee, D. and Stacey
B.: “The Mechanical Earth Model Concept and Its
Application to High Risk Well Construction Projects,” SPE
paper 59128, presented at the IADC/SPE Drilling
Conference, New Orleans, Louisiana, February 23-25, 2000.
9. Ahmed, M., Rahim, Z., Al-Anazi, H.A., Al-Kanaan, A.A.
and Mohiuddin, M.: “Development of Low Permeability
Reservoir Utilizing Multistage Fracture Completion in the
Minimum Stress Direction,” SPE paper 160848, presented
at the SPE Saudi Arabia Section Technical Symposium and
Exhibition, al-Khobar, Saudi Arabia, April 8-11, 2012.
10. Al-Ghazal, M.A., Al-Driweesh, S.M. and El-Mofty, W.:
“Practical Aspects of Multistage Fracturing from
Geosciences and Drilling to Production: Challenges,
Solutions and Performance,” SPE paper 164374,
presented at the Middle East Oil and Gas Show and
Conference, Manama, Bahrain, March 10-13, 2013.
11. Al-Jubran, H.H., Wilson, S. and Johnston, B.: “Successful
Deployment of Multistage Fracturing Systems in
Multilayered Tight Gas Carbonate Formations in Saudi
Arabia,” SPE paper 130894, presented at the SPE Deep
Gas Conference and Exhibition, Manama, Bahrain,
January 24-26, 2010.
26
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
BIOGRAPHIES
Mahbub S. Ahmed is a Petroleum
Engineering Consultant with Saudi
Aramco’s Gas Reservoir Management
Department. His expertise includes
reservoir management, gas field
development and reservoir simulation.
Prior to joining Saudi Aramco in
2001, Mahbub work
worked as a Senior Reservoir Engineer with
2001
the Occidental Oil and Gas Company in Bakersfield, CA;
as a Senior Consultant with Geoquest in Denver, CO; as a
Senior Engineer with Scientific-Software Intercomp in
Denver, CO; and as a Reservoir Engineer with the Algerian
National Oil Company (Sonatrach) in Algiers. He has
conducted numerous reservoir simulation and engineering
studies of oil and gas fields across the U.S., South America
and the Middle East.
Mahbub received his B.S. degree in 1982 from the
Institut Algérien du Pétrole, Boumerdes, Algeria, and his
M.S. degree in 1988 from the University of Oklahoma,
Norman, OK, both in Petroleum Engineering.
He is a member of the Society of Petroleum Engineers
(SPE).
Dr. Zillur Rahim is a Senior Petroleum
Engineering Consultant with Saudi
Aramco’s Gas Reservoir Management
Department (GRMD). He heads the
team responsible for stimulation
design, application, and assessment.
Rahim’s expertise includes well
stimulation, pressure transient test analysis, gas field
stimulation
development, planning, production enhancement, and
reservoir management. Prior to joining Saudi Aramco, he
worked as a Senior Reservoir Engineer with Holditch &
Associates, Inc., and later with Schlumberger Reservoir
Technologies in College Station, TX, where he consulted on
reservoir engineering, well stimulation, reservoir
simulation, production forecast, well testing, and tight gas
qualification for national and international companies.
Rahim is an instructor of petroleum engineering industry
courses and has trained engineers from the U.S. and
overseas. He developed analytical and numerical models to
history match and forecast production and pressure
behavior in gas reservoirs. Rahim also developed 3D
hydraulic fracture propagation and proppant transport
simulators, and numerical models to compute acid
reaction, penetration, proppant transport and placement,
and fracture conductivity for matrix acid, acid fracturing
and proppant fracturing treatments.
Rahim has authored more than 70 technical papers for
local/international Society of Petroleum Engineers (SPE)
conferences and numerous in-house technical documents.
He is a member of SPE and a technical editor for SPE’s
Journal of Petroleum Science and Technology (JPSE).
Rahim is a registered Professional Engineer in the State of
Texas, and a mentor for the Saudi Aramco’s Technologist
Development Program (TDP). He is an instructor for the
Advanced Reservoir Stimulation and Hydraulic Fracturing
course offered by the Upstream Professional Development
Center (UPDC) of Saudi Aramco. Rahim is a member of
GRMD’s technical committee responsible for the assessment, approval, and application of new technologies and
heads the in-house service company engineering team on
the application of best-in-class stimulation and completion
practices for improved gas production.
Rahim received his B.S. degree from the Institut Algérien
du Pétrole, Boumerdes, Algeria, and his M.S. and Ph.D.
degrees from Texas A&M University, College Station, TX,
all in Petroleum Engineering.
Ali H. Habbtar is a Supervisor in
Saudi Aramco’s Gas Reservoir
Management Department, where he is
responsible for the management of all
reservoirs feeding the Hawiyah Gas
Plant. He has over 10 years of
industry experience in reservoir
engineering
i
i and
d well
ll productivity enhancement through
stimulation.
As a member of the Society of Petroleum Engineers
(SPE), Ali has published numerous SPE papers.
Ali received his B.S. degree in Petroleum Engineering
from Pennsylvania State University, University Park, PA,
and an M.B.A. from the Instituto de Estudios Superiores de
la Empresa (IESE Business School), Barcelona, Spain.
Dr. Hamoud A. Al-Anazi is the
General Supervisor of the North
Ghawar Gas Reservoir Management
Division in the Gas Reservoir
Management Department (GRMD).
He oversees all work related to the
development and management of huge
Ain-Dar,
gas fields like Ain
Da Shedgum and ‘Uthmaniyah.
Hamoud also heads the technical committee that is
responsible for all new technology assessments and
approvals for GRMD. He joined Saudi Aramco in 1994 as
a Research Scientist in the Research & Development Center
and moved to the Exploration and Petroleum Engineering
Center — Advanced Research Center (EXPEC ARC) in
2006. After completing a one-year assignment with the
Southern Area Reservoir Management Department,
Hamoud joined the GRMD and was assigned to supervise
the SDGM/UTMN Unit and more recently the HWYH
Unit. With his team he successfully implemented the
deepening strategy of key wells that resulted in a new
discovery of the Unayzah reservoir in UTMN field and the
addition of Jauf gas reserves in HWYH field.
Hamoud’s areas of interests include studies of formation
damage, stimulation and fracturing, fluid flow in porous
media and gas condensate reservoirs. He has published
more than 50 technical papers at local/international
conferences and in refereed journals. Hamoud is an active
member of the Society of Petroleum Engineers (SPE) where
he serves on several committees for SPE technical
conferences. He is also teaching courses at King Fahd
University of Petroleum and Minerals (KFUPM), Dhahran,
Saudi Arabia, as part of the Part-time Teaching Program.
In 1994, Hamoud received his B.S. degree in Chemical
Engineering from KFUPM, and in 1999 and 2003, he
received his M.S. and Ph.D. degrees, respectively, in
Petroleum Engineering, both from the University of Texas
at Austin, Austin, TX.
Adnan A. Al-Kanaan is the Manager
of the Gas Reservoir Management
Department (GRMD), where he
oversees three gas reservoir management divisions. Reporting to the Chief
Petroleum Engineer, Adnan is directly
responsible for making strategic
decisions
and sustain gas delivery to the
d
ii
tto enhance
h
Kingdom to meet its ever increasing energy demand. He
oversees the operating and business plans of GRMD, new
technologies and initiatives, unconventional gas development
programs, and the overall work, planning and decisions
made by his more than 70 engineers and technologists.
Adnan has 15 years of diversified experience in oil and
gas reservoir management, full field development, reserves
assessment, production engineering, mentoring of young
professionals and effective management of large groups of
professionals. He is a key player in promoting and guiding
the Kingdom’s unconventional gas program. Adnan also
initiated and oversees the Tight Gas Technical Team to
assess and produce the Kingdom’s vast and challenging
tight gas reserves in the most economical way.
Prior to the inception of GRMD, he was the General
Supervisor for the Gas Reservoir Management Division
under the Southern Reservoir Management Department for
3 years, heading one of the most challenging programs in
optimizing and managing nonassociated gas fields in Saudi
Aramco.
Adnan started his career at the Saudi Shell Petrochemical
Company as a Senior Process Engineer. He then joined
Saudi Aramco in 1997 and was an integral part of the
technical team responsible for the on-time initiation of the
two major Hawiyah and Haradh Gas Plants that currently
process more than 6 billion cubic feet (bcf) of gas per day.
Adnan also directly managed Karan and Wasit fields —
two major offshore gas increment projects — with an
expected total production capacity of 4.3 bcf of gas per
day.
He actively participates in the Society of Petroleum
Engineers (SPE) forums and conferences, and has been a
keynote speaker and panelist for many such programs.
Adnan’s areas of interest include reservoir engineering, well
test analysis, simulation modeling, reservoir characterization, hydraulic fracturing, reservoir development
planning and reservoir management.
He chaired the 2013 International Petroleum Technical
Conference to be held in Beijing, China.
Adnan received his B.S. degree in Chemical Engineering
from King Fahd University of Petroleum and Minerals
(KFUPM), Dhahran, Saudi Arabia.
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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27
Wael EI-Mofty is the Middle East
Area Manager for Packers Plus Energy
Services. In that role, he focuses on
helping out major operators in the
area, assessing the technical and
economic viability of multistage
fracturing technology while enhancing
the
h applications
li i
iin their
h respective reservoirs to optimize
returns on investment.
Wael has over 27 years of oil and gas experience with a
solid background in drilling and completion engineering,
formation evaluation and geomechanics. Over the last 15
years, he has focused particularly on project development
work around North Africa and the Middle East.
Before joining Packers Plus, Wael held various
management positions with Eastman Whipstock, Baker
Hughes and Halliburton in different locations around the
world, including in the U.S., North Sea, Africa and the
Middle East.
He received his B.S. degree in Chemical Engineering
from Cairo University, Giza, Egypt. Wael also received an
Industrial Management diploma from Oklahoma State
University, Stillwater, OK.
He is an active member of the Society of Petroleum
Engineers (SPE) and a registered consulting engineer with
the Egyptian Syndicate of Engineers.
28
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
Upgrading Multistage Fracturing
Strategies Drives Double Success after
Success in the Unusual Saudi Gas Reserves
Authors: Mohammed A. Al-Ghazal, Saad M. Al-Driweesh and Fadel A. Al-Ghurairi
ABSTRACT
Open hole multistage fracturing (MSF) technologies have been
deployed in Saudi Arabia’s tight gas fields in both carbonate
and sandstone formations with the objective of maximizing
reservoir contact by inducing independent multiple fractures
and increasing matrix contribution.
Full achievement of this objective has not been straightforward or quick. While good well productivity was seen from the
early wells completed with MSF technologies, several technical
issues had to be investigated and resolved when the technology
was initially introduced. These issues included mechanical and
differential sticking during the deployment phase as well as
failure to attain a clear fracture signature for the subsequent
stages after fracturing the first stage in carbonate formations
due to potential hydraulic communication between the fracture
stages.
Compared to other fields the world over, the application of
MSF operations in Saudi Arabia has been typically more challenging and has required more sophisticated approaches due to
the deep, highly heterogeneous, high-pressure, high temperature
nature of the gas-bearing formations, as well as the high pumping
pressure required and the large treatment volumes being pumped.
Accordingly, improvement strategies were implemented to
mitigate these limitations and realize the full advantage of using MSF technologies in developing tight gas reserves. This article discusses these strategies and shows how they have been
successfully utilized to further improve the application of MSF
and surpass most of the original production expectations.
Furthermore, the article addresses a scheme for increasing
the success rate for the secondary (contingency) coiled tubing
(CT) ball seat milling out operations for MSF systems.
The article takes a holistic approach integrating the various
technical disciplines involved in ensuring optimum results are
obtained.
exhibiting unconventional heterogeneity, Fig. 1. Only a handful of MSF technologies were installed in the early years while
the benefits were evaluated. To date, about 50 MSF completion systems have been run to support the gas development
program in Saudi Arabia.
The purpose of using MSF technologies has been to maximize reservoir contact, completely cover the production interval
and ensure precise treatment fluid placement1, 2, Figs. 2 and 3.
Targets have spanned both carbonate and sandstone formations, with the number of fracture stages ranging from two to
Fig. 1. Carbonate rock outcrop demonstrating heterogeneity (Photo courtesy of
Mohammad Reza Saberi, University of Bergen).
Fig. 2. MSF technologies offer the greatest reservoir contact.
INTRODUCTION
As early as 2007, the first open hole multistage fracturing (MSF)
completion systems were being installed in Saudi Arabia’s
deep, highly deviated wells located in high-pressure, high temperature, highly slanted, tight layered, gas-bearing formations
Fig. 3. Achieving the maximum reservoir contact, complete zonal coverage and
precise fluid placement with MSF technology.
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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seven per lateral. The production results have varied, with the
majority of the MSF wells meeting or exceeding the pre-stimulation expectations1, 3-7. Also, three different MSF technologies
were deployed by three different technology suppliers with
differences mainly in the design of the isolation packers, the
external pressure sleeve and the seat and ball material3, 8.
Given the fact that Saudi Arabian gas reservoirs are more
challenging than most other reservoirs in that they are very deep,
extremely hot, highly heterogeneous and developed with complex well trajectories, many challenges had to be overcome
during the early phase of applying MSF technologies in Saudi
Arabia6. The main challenges encountered included mechanical
and differential sticking as well as hydraulic communication
between stages in carbonate formations, preventing the creation
of separate fractures in each stage of the completion assembly.
This article addresses the main challenges faced and describes the effective strategies that have been devised to mitigate these challenges and realize the full benefits of the MSF
technologies. Also, the article reviews the production results
for MSF wells and compares them to those of offset wells that
have been completed using other techniques, such as horizontal open hole or cased hole.
pressure, given that other features of the packer stay the same,
the packer should be short enough to minimize contact with
the wellbore and pass any dogleg during the deployment, facilitating easier reach to target depth. Figure 5 shows a mechanical packer that has a dogleg severity of about 30°/100 ft as a
result of its small radius.
STRATEGIES FOR PREVENTING DIFFERENTIAL
STICKING
A few of the early MSF technologies encountered differential
sticking because of the use of excessively heavy drilling mud as
well as a large difference in pressure between two adjacent
formation members, Fig. 6. For example, within the Khuff-B
formation are six zones with different formation pressures, an
environment that is prone to cause differential sticking. The
STRATEGIES FOR PREVENTING MECHANICAL
STICKING
A few of the early MSF technologies encountered mechanical
sticking issues due to restrictions in the wellbore, especially in
cases where the reamer used did not accurately and precisely
mirror the open hole packer. The following strategies were
developed and implemented to prevent mechanical sticking.
Specialized Reamer
Fig. 4. 3D drag profiling for an MSF well.
A specialty reamer was run to clean out the wellbore prior to
running the MSF system. The specialty reamer mirrors both the
size of the open hole packer to ensure good cleaning and the
stiffness of the packer to ensure passage through the dogleg.
Drag Modeling
A detailed drag modeling program was used to simulate the
drag forces imposed while running the MSF technologies
downhole, Fig. 4. As MSF well candidates are identified from
the beginning, the drag model is initially run using the planned
well directional survey to evaluate the potential of running the
MSF technologies to the target depth; any necessary changes in
the directional plan are made based on the modeling results.
Later, the modeling is performed again using the actual survey
data to verify the potential of running the MSF system to the
target depth as well as to optimize the deployment string design.
Fig. 5. Short, small raidus mechanical packer for easier deployment.
Packer Size
While it is true that longer packers offer higher differential
30
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
Fig. 6. Differential sticking can be encountered during installation of MSF systems
due to varying formation pore pressures within the same formation.
following strategies were developed and put into action to
prevent differential sticking.
Fluted Centralizer
A fluted centralizer was connected to the MSF technologies to
enable positive standoff from the wellbore and prevent hydraulic lock. The centralizer is a slip-on type with a large water
course and a swivel device to allow liner rotation inside the
centralizer. This results in minimizing the contact between the
wellbore and the MSF technologies while maintaining a good
passage for fluids in the wellbore.
Mechanical Earth Model
For wells that had been drilled in the minimum horizontal in
situ stress plane (σmin), a 1D Mechanical Earth Model (MEM)
was used to foresee the formation pore pressure and provide
the optimum mud weight to improve wellbore quality, leading
to successful deployment, Fig. 7. The MEM is initially built using the logging while drilling (LWD) composite log and core
data from offset wells. Then, the model is tested on the offset
wells for verification and calibration purposes. Also, the MEM
is calibrated while drilling in real time using the pressure data
obtained from LWD measurements. A 1D MEM is used as opposed to a 3D MEM for the following reasons. First, it fits the
purpose. Second, it does not require the amount of input normally required for a 3D MEM. Finally, it is cheaper. Along
with the optimum drilling mud weight, the model also provides the mud weights at which formation breakout, kick, mud
loss and breakdown are expected to occur. The use of the
MEM eliminates any differential sticking issues by lowering
mud weight in a safe manner.
STRATEGIES FOR MINIMIZING HYDRAULIC
COMMUNICATION BETWEEN STAGES IN CARBONATE
FORMATIONS
Clear fracture signatures were not observed for all the subsequent fracture stages after fracturing the first stage for some
wells drilled in the maximum horizontal in situ stress plane
(σmax) and completed across the Khuff carbonate9. This setback was caused by hydraulic communication between the
fracture stages due to natural fractures or the failure of the isolation packer to keep the pressure and fluid contained in the
stage, resulting in a much shorter fracture length.
Several initiatives were put into action to mitigate the effects
of this complex issue, such as a reduction in the acid volume
and the use of a balanced system and anchoring tools. The
acid volume reduction was recommended to minimize the
eroding away of the rock matrix around the slips of the isolation packer, whereas the balanced system and anchoring tools
were favored to prevent any excessive movement of the isolation packer during the high-pressure fracturing operation,
Fig. 7. 1D MEM for an MSF well drilled in the minimum stress direction.
Fig. 8. Balanced system vs. unbalanced system.
Fig. 8. In spite of all the aforementioned efforts, communication between stages was still observed. Several other attempts
were made to reduce the communication impact, such as the
use of double packers and the elimination of flow back operations between stages to avoid the suction effect, but the communication issue was still not completely resolved. Only one
strategy has effectively resolved the communication issue:
changing the wellbore azimuth from the σmax to the minimum
horizontal in situ stress plane (σmin).
Changing the Drilling Direction from σmax to σmin
Initially, MSF wells were drilled toward the σmax direction for
better wellbore stability and a higher rate of penetration (ROP)
for the drilling bit. Because MSF conducted in wells drilled in
the direction of σmax results in longitudinal fractures that often
have some form of hydraulic communication between zones of
the first fracture stage and zones of the subsequent fracture
stages, the decision was made to change the wellbore azimuth
of MSF wells to the σmin direction, resulting in transverse fractures and helping to reduce the communication issue between
the completion stages, Fig. 9. This change was very challenging
from a drilling viewpoint as it required much more planning
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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Fig. 11. Main treatment plot for stage 1 of Well H-9.
Fig. 9. Longitudinal fractures for wells drilled in the maximum stress direction vs.
transverse fractures for wells drilled in the minimum stress direction.
Fig. 12. Mini falloff and SRT/SDT treatment plot for stage 2 of Well H-9.
Fig. 10. The segmented interval of Well H-9.
and time. Before a well could be drilled, the geomechanics of
the area around the planned well had to be studied to mitigate
the wellbore stability issues caused by the high horizontal
stresses imposed on the wellbore when drilling perpendicular
to the natural fractures in the formation. Also, to improve the
ROP while drilling in the σmin direction, heavy-duty bits developed for very high revolution-per-minute applications had to
be used.
The following are examples of a carbonate well drilled in the
σmax direction where no communication between stages was
observed. Second, a carbonate well drilled in the σmax direction
where communication between stages was observed. Third, a carbonate well drilled in the σmin direction where no communication
was observed; and finally, a sandstone well drilled in the σmin
direction where no communication was observed.
EXAMPLE WELL H-9 (CARBONATE WELL DRILLED IN
σMAX WHERE NO COMMUNICATION WAS OBSERVED)
Well H-9 was drilled in the carbonate Khuff-C formation
towards the σmax direction. This led to the expectation of lon32
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
Fig. 13. Main treatment plot for stage 2 of Well H-9.
gitudinally oriented fractures, i.e., fractures primarily aligned
along the wellbore. Subsequently, the well was completed with
a three-stage MSF system, Fig. 10.
During the fracturing operation, the first frac port opened at
5,565 psi after pumping 6 barrels (bbl) of treated water. Then
the first stage was successfully acid fractured, Fig. 11. The step
rate test and step down test (SRT/SDT) for the second stage
confirmed that there was no communication with the first
stage, Fig. 12. Subsequently, the second stage was successfully
acid fractured, Fig. 13. Afterwards, a SRT/SDT was conducted
for the third stage, and it confirmed that there was no communication, Fig. 14. Subsequently, the third stage was successfully
EXAMPLE WELL U-1 (CARBONATE WELL DRILLED IN
σMAX WHERE COMMUNICATION WAS OBSERVED)
Fig. 14. Mini falloff and SRT/SDT treatment plot for stage 3 of Well H-9.
Well U-1 was sidetracked as highly slanted in the σmax direction with a net reservoir contact of 1,557 ft, Fig. 16. The well
was completed with MSF equipment in the carbonate Khuff-B
formation, Fig. 17.
With the MSF system deployed at the target depth, the first
port was opened. The first stage was then successfully acid fractured by pumping a mixture of pad, acid and diversion fluid. Subsequently, during the main treatment of the first stage, there was a
drop of about 5,254 psi surface pressure, from 16,054 psi to
10,800 psi, Fig. 18. When pumping commenced in stage 2, it was
very clear that there was communication between stages 1 and 2.
As shown in Fig. 19, an immediate pressure decline to 0 psi
Fig. 15. Main treatment plot for stage 3 of Well H-9.
Fig. 17. The segmented interval of Well U-1.
Fig. 18. The pressure drop seen in Well U-1 during the main treatment of the
first stage.
Fig. 16. The horizontal azimuth of Well U-1 varies from 103° to 107°.
acid fractured, Fig. 15. After treating the entire interval, the
well achieved a stabilized flow rate of 21.1 million standard
cubic ft per day (MMscfd) at a flowing wellhead pressure
(FWHP) of 2,150 psi. It is noteworthy to mention here that for
all of the stages no flow back operations were conducted before fracturing all stages to avoid any suction effects that could
lead to hydraulic communication between stages.
Fig. 19. Communication between stages 1 and 2 for Well U-1.
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STRATEGIES FOR SUCCESSFUL CT BALL SEAT MILLING
OUT OPERATIONS
MSF technologies are meant to be interventionless, but coiled
tubing (CT) interventions were made in four MSF wells in
Saudi Arabia to mill out ball seats for different objectives, such
as the cleanup of debris (e.g., excess proppant) and the opening of the frac port (if the port did not open after several attempts without milling)8, 10, 11. Based on these CT intervention
experiences, the following strategies were established to increase the success rate for the secondary (contingency) CT ball
seat milling out operations.
Integrated Approach
The best scheme for a successful CT ball seat milling out
operation takes into consideration both the ball seat material
and the CT bottom-hole assembly. The ball seat should be
readily millable in a relatively short time, and the milling tool
should be aggressive enough to drill through the ball seat without damaging the MSF completion.
Sufficient WOB
run to check that sufficient WOB is applied in planning for the
job. The optimum WOB was found to be in the range of 800
lb to 1,000 lb. If too little weight is applied, there will be no
progress, but at the same time, if too much weight is applied,
the mill may stall, Fig. 29.
PRODUCTION RESULTS AND DISCUSSION
MSF technologies have been successfully utilized in several gas
fields in the Southern Area of Saudi Arabia covering both the
carbonate Khuff and the sandstone pre-Khuff (mainly Unayzah) reservoirs, Fig. 30.
In general, the production results from wells completed using MSF technologies — as deployed in the Southern Area gas
fields — have been very positive with actual results exceeding
expectations. Figure 31 shows a comparison of the average
well productivity of MSF wells with that of wells completed
using other techniques (non-MSF wells) in the two main fields
of the technology application, namely Field-A and Field-B. The
comparison shows that significant production improvement
was gained using MSF technologies in both fields. In Field-A,
MSF wells produce at a rate that is approximately three times
the rate produced by non-MSF wells, whereas in Field-B, MSF
Weight-on-bit (WOB) proved a critical parameter in ball seat
milling out jobs. Therefore, a CT force simulation should be
Fig. 31. Average well production comparison between MSF and conventionally
completed wells.
Fig. 29. Repeated stalls as a result of too much WOB.
Fig. 30. MSF technologies classified by field in the Southern Area gas fields of
Saudi Arabia.
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
Fig. 32. Average well production comparison between MSF wells and offset wells
completed with other horizontal open hole or cased hole completion techniques.
wells produce at a rate approximately 2.3 times the rate produced by non-MSF wells. While it is true that the reservoir
properties are different from one well to the other in both fields
and that most of the non-MSF wells are older, this production
comparison indicates that MSF technologies enable very good
well productivity with very competitive advantages. Accordingly,
the forecast is that the application of MSF technologies will
grow sharply and rapidly, especially as our industry moves into
more development projects targeting unconventional resources.
In addition, Fig. 32 is a comparison between the average gas
production rate for wells completed with MSF technologies
and for offset wells completed with other horizontal open hole
or cased hole completion techniques (H non-MSF wells) in the
two main fields of application.
CONCLUSIONS AND RECOMMENDATIONS
1. Implementation of strategic mitigation practices has
practically eliminated any deployment issues associated
with MSF technologies and resulted in consistent successful
deployment of the technologies to their target depth.
2. Proper use of the MEM has improved wellbore stability by
providing the optimum mud weight when drilling in the
σmin direction.
3. Multiple transverse fractures are required to maximize the
contact area between the well and the formation, and to
reap the full benefits of MSF technologies.
4. In general, carbonate wells drilled in the σmax direction
with longitudinal fractures following MSF achieved good
production results. But wells drilled in the σmin direction
created multiple transverse fractures with MSF and resulted
in a relatively higher production rate.
5. Changing the horizontal wellbore drilling direction from
the σmax to σmin has helped significantly in minimizing
hydraulic communication between the fracture stages in
carbonate formations. Accordingly, it is recommended that
wells planned to be completed with MSF technologies
should be drilled in the σmin direction, except in cases
where it is not viable, such as due to well proximity issues.
In this situation, efficient matrix acidizing should be sought
as an alternative.
6. A balanced system and anchoring tools are recommended
to prevent any excessive movement of the isolation packers
during the high-pressure fracturing operation.
7. The millability of the MSF system should be considered
and evaluated if it seems likely that a CT ball seat milling
out operation will be required during the life of the well.
8. Overall, the performance of wells completed with MSF
technologies surpasses that of wells completed with other
completion techniques, such as horizontal open hole and
cased hole, in terms of stabilized gas production rate.
9. Based on the positive production results achieved from
wells completed with MSF technologies, it is recommended
to continue using MSF technologies in exploiting moderate
and low permeability rock formations in the Kingdom.
ACKNOWLEDGMENTS
The authors would like to thank the management of Saudi
Aramco for their permission to publish this article. The authors
would also like to thank the Southern Area Production Engineering Department and the Southern Area Well Completion
Operations Department for their great support during the jobs’
design and execution. Additionally, a special thank you goes to
the multistage fracturing team at Saudi Aramco, Wael El-Mofty
from Packers Plus and Stuart Wilson from Schlumberger.
This article was presented at the SPE Saudi Arabia Section
Annual Technical Symposium and Exhibition, al-Khobar,
Saudi Arabia, May 19-22, 2013.
REFERENCES
1. Al-Ghazal, M.A., Al-Ghurairi, F.A. and Al-Zaid, M.R.:
“Overview of Open Hole Multistage Fracturing in the
Southern Area Gas Fields: Application and Outcomes,”
Saudi Aramco Ghawar Gas Production Engineering
Division Internal Documentation, March 2013.
2. Al-Ghazal, M.A. and Abel, J.T.: “Stimulation Technologies
in the Southern Area Gas Fields: A Step Forward in
Production Enhancement,” Saudi Aramco Gas Production
Engineering Division Internal Documentation, October
2012.
3. Al-Ghazal, M.A., Al-Sagr, A.M. and Al-Driweesh, S.M.:
“Evaluation of Multistage Fracturing Completion
Technologies as Deployed in the Southern Area Gas Fields
of Saudi Arabia,” Saudi Aramco Journal of Technology,
Fall 2011, pp. 34-41.
4. Al-Jubran, H.H., Wilson, S. and Johnston, B.: “Successful
Deployment of Multistage Fracturing Systems in
Multilayered Tight Gas Carbonate Formations in Saudi
Arabia,” SPE paper 130894, presented at the SPE Deep
Gas Conference and Exhibition, Manama, Bahrain,
January 24-26, 2010.
5. Hamid, A.H., Kalil, M.E., Al-Mohammad, A.K., AlKhamees, S.A., El-Mofty, W., Johnston, B., et al.:
“Successful Drilling and Deployment of an Open Hole
Multistage Fracturing System in a Deep and Hostile
Sandstone Gas Reservoir,” SPE paper 149062, presented at
the SPE/DGS Saudi Arabia Section Technical Symposium
and Exhibition, al-Khobar, Saudi Arabia, May 15-18,
2011.
6. Rahim, Z., Al-Kanaan, A.A., Johnston, B., Wilson, S., AlAnazi, H. and Kalinin, D.: “Success Criteria for Multistage
Fracturing of Tight Gas in Saudi Arabia,” SPE paper
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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149064, presented at the SPE/DGS Saudi Arabia Section
Technical Symposium and Exhibition, al-Khobar, Saudi
Arabia, May 15-18, 2011.
7. Solares, J.R., Giraldo, C.A., Al-Marri, H., Al-Hussain, H.,
Abualhamayel, N., Ramanathan, V., et al.: “Successful
Multistage Horizontal Well Fracturing in the Deep Gas
Reservoirs of Saudi Arabia: Field Testing of a Promising,
Innovative, New Completion Technology,” SPE paper
114766, presented at the SPE Annual Technical Conference
and Exhibition, Denver, Colorado, September 21-24, 2008.
8. Al-Ghazal, M.A., Abel, J.T., Wilson, S., Wortman, S. and
Johnston, B.: “Coiled Tubing Operational Guidelines in
Conjunction with Multistage Fracturing Completions in the
Tight Gas Fields of Saudi Arabia,” SPE paper 153235,
presented at the SPE Middle East Unconventional Gas
Conference and Exhibition, Abu Dhabi, U.A.E., January
23-25, 2012.
9. Rahim, Z., Al-Kanaan, A.A., Al-Anazi, H., Al-Harbi, A.,
Ginest, N., Halim, A., et al.: “Integration of Drilling,
Completion, and Stimulation Technology Boosts Saudi
Arabian Gas Well Performance,” SPE 161793, presented at
the SPE International Petroleum Conference and
Exhibition, Abu Dhabi, U.A.E., November 11-14, 2012.
10. Al-Ghazal, M.A., Abel, J.T., Al-Buali, M.H., AlRuwaished, A., Al-Saqr, A., Al-Driweesh, S.M., et al.:
“Coiled Tubing Best Practices in Conjunction with
Multistage Completions in the Tight Gas Fields of Saudi
Arabia,” SPE paper 160833, presented at the SPE Saudi
Arabia Section Technical Symposium and Exhibition, alKhobar, Saudi Arabia, April 8-11, 2012.
11. Al-Ghazal, M.A., Al-Driweesh, S.M., Al-Ghurairi, F.A.,
Al-Sagr, A. and Al-Zaid, M.: “Assessment of Multistage
Fracturing Technologies as Deployed in the Tight Gas
Fields of Saudi Arabia,” IPTC paper 16440, presented at
the International Petroleum Technology Conference,
Beijing, China, March 26-28, 2013.
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BIOGRAPHIES
Mohammed A. Al-Ghazal is a
Production Engineer at Saudi Aramco.
He is part of a team that is responsible
for gas production optimization in the
Southern Area gas reserves of Saudi
Arabia. During Mohammed’s career
with Saudi Aramco, he has led and
several upstream projects, including pressure
participated in severa
control valve optimization, cathodic protection system
performance, venturi meter calibration, new stimulation
technologies, innovative wireline technology applications,
upgrading fracturing strategies, petroleum computer-based
applications enhancement and safety management
processes development.
In 2011, Mohammed assumed the position of Gas
Production HSE Advisor in addition to his production
engineering duties. During his tenure as HSE Advisor, he
founded the People-Oriented HSE culture, which has
brought impressive benefits to Saudi Arabia gas fields,
resulting in improved operational performance.
In early 2012, Mohammed went on assignment with the
Southern Area Well Completion Operations Department,
where he worked as a foreman leading a well completion
site in remote areas.
As a Production Engineer, Mohammed played a critical
role in the first successful application of several high-end
technologies to present new possibilities in the Kingdom’s
gas reservoirs. Mohammed’s areas of interest include
formation damage investigation and mitigation, coiled
tubing applications, wireline operations, matrix acidizing,
hydraulic fracturing and organizational HSE performance.
In 2010, Mohammed received his B.S. degree with
honors in Petroleum Engineering from King Fahd
University of Petroleum and Minerals (KFUPM), Dhahran,
Saudi Arabia.
He has also authored and coauthored several Society of
Petroleum Engineers (SPE) papers and technical journal
articles as well as numerous in-house technical reports.
Additionally, Mohammed served as a member of the
industry and student advisory board in the Petroleum
Engineering Department of KFUPM from 2009 to 2011.
As an active SPE member, he serves on the Production
and Operations Award Committee.
Recently, he won the best presentation award at the
production engineering session of the 2013 SPE Young
Professional Technical Symposium.
Mohammed is currently pursuing an M.S. degree in
Engineering at the University of Southern California, Los
Angeles, CA.
Saad M. Al-Driweesh is a General
Supervisor in the Southern Area
Production Engineering Department
(SAPED), where he is involved in gas
production engineering, well
completion, and fracturing and
stimulation activities.
Saad is an active member of the Society of Petroleum
Engineers (SPE), where he chairs several technical sessions
in local, regional and international conferences. He is also
the 2013 recipient of the SPE Production and Operations
Award for the Middle East, North Africa and India region.
In addition, Saad chaired the first Unconventional Gas
Technical Event and Exhibition in Saudi Arabia.
He has published several technical articles addressing
innovation in science and technology. Saad’s main interest
is in the field of production engineering, including
production optimization, fracturing and stimulation, and
new well completion applications. He has 26 years of
experience in areas related to gas and oil production
engineering.
In 1988, he received his B.S. degree in Petroleum
Engineering from King Fahd University of Petroleum and
Minerals (KFUPM), Dhahran, Saudi Arabia.
Fadel A. Al-Ghurairi is a Petroleum
Engineering Consultant and Technical
Support Unit Supervisor working on
gas fields. He has 24 years of
experience in production and reservoir
engineering. In the last 12 years, Fadel
has specialized in stimulation and
fracturing of deep gas wells.
In 1988, he received his B.S. degree in Petroleum
Engineering from King Fahd University of Petroleum and
Minerals (KFUPM), Dhahran, Saudi Arabia.
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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Illuminating the Reservoir:
Magnetic NanoMappers
Authors: Abdullah A. Al-Shehri, Dr. Erika S. Ellis, Jesus M. Felix Servin, Dr. Dmitry V. Kosynkin,
Dr. Mazen Y. Kanj and Dr. Howard K. Schmidt
ABSTRACT
The ability to map injected fluids in hydrocarbon reservoirs
with high resolution is a key goal for reservoir engineering and
optimization. Saudi Aramco is developing tools and methodologies to map the flood front, locate bypassed oil, monitor the
oil-water contact, and detect super-K zones and fracture corridors prior to early water breakthrough at producing wells. The
use of Magnetic NanoMappers (MNM) is a new approach exploiting Magnetic Nano-Particles (MNPs) as contrast agents
for mapping the flood front inside the hydrocarbon reservoir.
This approach takes advantage of the fact that the speed of
electromagnetic (EM) waves slows down when they pass
through magnetic media. Localizing MNPs within an injected
fluid could provide a detailed map of the fluid’s movements.
Lab tests have recently demonstrated the capability of MNM
to locate MNP volumes hidden within a 2,000 liter tank (reservoir model) with high resolution. This article will outline the
MNM concept, laboratory test bed, results and future plans.
INTRODUCTION
Tomography is a noninvasive imaging technique that allows
the visualization of a slice or section of the internal structures
of an object by using penetrating radiation. The technique is
based on the mathematical principle of tomographic reconstruction, first developed by Johann Radon in the early 20th
century1. Traveltime tomography is widely used in geophysical
studies to image subsurface velocity variation, mainly for seismic waves. It uses first arrival traveltime information from the
transmitted wave as input data to construct earth structure and
velocity models2.
Traveltime tomography measurements can be accomplished
using different kinds of waves, such as acoustic or electromagnetic (EM) waves. The basic theory of cross-well EM tomography
has been studied and detailed in many papers3-5. Also, several
types of equipment have been developed for cross-hole EM
tomography6. Most of this equipment uses a low frequency
controlled source EM (CSEM) method and system to image
subsurface and subsea conductivity7, 8.
To conduct traveltime measurements using EM waves, a
signal is launched into a medium by a source antenna and is
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recorded by a receiver antenna. This trace or waveform contains a first arrival signal as well as other signals eventually
produced from reflections or refractions of the radiated waves.
The waves are affected in terms of traveltime and amplitude by
variations in their propagation speed due to losses caused by
traveling through different media. This effect is governed by
the dielectric permittivity (є), magnetic permeability (µ) and
electrical conductivity (σ) of each medium. As the EM waves
travel from transmitter to receiver, the time delay of the first
arrival signal peak recorded at the receiver is used to determine
the velocity of wave propagation. The difference in time delays
with respect to a given medium can be inverted to build a tomographic representation of the medium9-11.
The review of prior works discussing traveltime tomography showed that all approaches were based on mapping electrical conductivity or permittivity. None considered mapping
variations in magnetic permeability. In our approach, we extended the prior works in a new way by employing variations
in magnetic permeability to generate new fluid imaging capabilities using Magnetic Nano-Particles (MNPs).
Magnetic NanoMappers (MNM) is a new approach exploiting the use of MNPs as contrast agents for mapping the
flood front inside hydrocarbon reservoirs. This approach employs EM wave traveltime tomography coupled with MNPs to
map the subsurface and so enable real-time monitoring of the
injected water in reservoirs. It can also be used as a tool to
locate bypassed oil, monitor the oil-water contact, and detect
super-K zones and fracture corridors prior to early water
breakthrough at producing wells. The MNM research program is a multidisciplinary solution that comprises the iterative
parallel development of chemical materials (the MNPs), hardware including EM sources, receiver antenna arrays and data
acquisition components as well as software, including signal
processing, forward modeling and inversion.
This article reports progress to date on the road to developing the MNM program, which will be subsequently deployed
in real reservoirs. In the lab, EM waves were used to successfully map a container of high permeability MNPs buried
within a 2,000 liter laboratory demonstration reservoir model
of water and sand that simulated field conditions. The first
arrival traveltimes of EM waves passing through the air, wet
sand, water and MNPs were measured and processed to generate
an accurate 1D image of the MNP volume within the lab scale
reservoir. 3D imaging and inversion experiments using the
same test bed are currently ongoing. The next step is to
demonstrate the concept in shallow wellbores in the field. This
article will outline the MNM concept, experimental test bed,
results and discussion.
MAGNETIC NANO-PARTICLES (MNPS)
MNPs are the enabling element in MNM technology. They are
used as contrast agents due to their super paramagnetic (high
µ) properties. Once they are injected (with the fluid) into the
fracture/reservoir, they will significantly slow the propagation
of EM waves between the transmitter and receiver as the waves
pass through the front. A matrix of traveltimes collected over
the entire reservoir should differentiate between sand/rock,
injection fluid and MNP-loaded volumes. We expect to use the
resulting matrix of time delays, with inversion, to create a 3D
image of the flood front.
The MNPs were selected because of the ease of preparing
them in large amounts, their high chemical stability in water in
the absence of oxygen and their high magnetic permeability,
Figs. 1 and 2. We adapted the preparation procedure described
in Lu, et al. (2007)12, to prepare a mixture of MNPs at a concentration of 10,000 ppm.
THE CONCEPT OF THE MNM PROGRAM
The MNM approach capitalizes on the MNPs’ super paramagnetic property to delay the propagation of EM waves while
passing through the injected fluid. EM waves travel at c =
3.0×108 m/s in a vacuum, but they slow down substantially
when they pass through a medium and interact with the atoms
Fig. 2. Super paramagnetic MNPs are attracted to a magnet outside the sample jar.
of the medium. This interaction denotes the permittivity and/or
permeability of the medium. Equation 1 describes the speed of
the EM waves in a given medium.
(1)
Fig. 1. TEM image of MNPs.
where c is the speed of light in a vacuum, V is the speed in the
medium, µr is the relative magnetic permeability of the
medium, and єr is the relative electrical permittivity of the
medium.
According to the above equation, as the EM waves pass
through the MNP concentration with high µ, the propagation
speed will decrease, showing an increased time delay in the
received signal along the MNP front. Figure 3 illustrates the
transmitter receiver array configuration of MNM across a
fluid injected in the reservoir and the resulting time delay as the
EM waves pass through the MNP front. A pulsed transmitter
is located in a borehole to emit the EM waves. The radiated
waves propagate through the reservoir and are detected at the
receiving array located in a parallel borehole. The first peak
arrival time information (first significant received signal peak
from the receiver array) is used to produce a matrix of traveltime vs. antenna position throughout the reservoir, which can
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Fig. 3. Schematic cross section of the transmitter receiver array configuration
across a fluid injected in the reservoir and the corresponding delay in the received
waveform as the EM waves pass through the MNP front.
be processed by 3D inversion software to produce the spatial
tomography maps11.
3D TOMOGRAPHY OF RESERVOIRS USING MNM
As previously mentioned inversion software is needed to
process and interpret the time delay measurements produced
from a MNM test and to produce tomographic maps of the
flood front. A tomographic inversion method that uses first
arrival traveltime information is the appropriate method to
analyze MNM collected data and surveys. There are many
inversion methods developed to extract the first arrival traveltime and amplitude spectra information from cross-hole radar
measurements to reconstruct electromagnetic velocity and
attenuation distribution in earth materials. These methods include straight-ray tomography13, curved-ray tomography14
and traveltime tomography11. Since the goal of MNM is to
map the variations in magnetic permeability using first arrival
traveltime information, the traveltime tomographic inversion
method will be used.
Fig. 4. 2,000 liter tank (reservoir model).
EXPERIMENTAL TEST BED
The experimental setup used a 2,000 liter tank half filled with
wet sand as a reservoir model. In addition, a PVC pipe was
placed through the center of the tank to mimic the borehole
for the transmission source, as depicted in Fig. 4. The tank was
divided into four quadrants, three of them containing a buried
five gallon plastic container each (diameter of 27 cm) filled with
different media: air, water and MNPs. The last quadrant was
empty, containing wet sand only. For each quadrant, the total
distance from the borehole (transmitter) to the volume side
was 13.5 cm. The distance from the opposite side of the volume to the outside wall of the tank was also 13.5 cm. Therefore, for shots directly through the volumes, the EM wave
traveled through 13.5 cm of wet sand and 27 cm of volume
medium plus an additional 13.5 cm of wet sand to the receiver
antenna (a total distance of 54 cm). This is depicted in Fig. 5.
An in-house built 1 kV spark gap with 3 cm loop was used
to generate 2 GHz pulsed EM waves with a wavelength of 15
cm, Figs. 6a and 6b. A single loop of 3 cm magnetic wire
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Fig. 5. Top-down schematic of volume placement in tank.
antenna was attached on top of and normal to the face of the
spark gap to record the magnetic portion of the transmission
waveform. The spark gap and its antenna were fixed to a
moveable sliding plate attached to a wooden slat placed down
the center of the PVC pipe (borehole) to easily change the position of the transmission source. The receiver antenna was
made of a 3 cm single loop of magnetic wire and placed outside the tank, positioned 90° radially from the spark gap face
to obtain the maximum far field magnetic signal. An Agilent
DSO7104 oscilloscope capable of 4 GHz time capture was
used to monitor transmission and receiver waveforms. Labview 2010 was used to control the scope and capture waveform data. MatLab software was used to filter and process the
image of a single quadrant of the tank to find the buried volume with respect to the vertical position of the transmitter and
receiver. In this case, the transmitter (spark gap) and receiver
antenna positions were varied over 10 vertical positions down
the tank in 10 cm increments, starting with air, moving
through the buried volume and then going below the volume
through wet sand only. This data presented a 1D vertical image of the MNP volume based on the time delay differences as
the transmitter and receiver moved vertically down the tank.
Figure 7 shows a schematic of the 1D imaging experiment.
RESULTS AND DISCUSSION
Fig. 6a. In-house built 1 kV spark gap with 3 cm loop used as a pulsed DC
transmission source.
The first phase results show fundamental time delay differences and corresponding material properties for four different
media: air, sand, water and MNPs. Figure 8 (top) shows the
signal from the spark gap transmitter antenna (Tx), and Fig. 8
(bottom) shows the entire received signals shot from Tx
through the center of each buried volume for each of the four
tank quadrants. The red dotted line represents the beginning of
the transmission pulse (time = 0). The first peak for each waveform was determined by a statistical Matlab subroutine and is
shown for each quadrant (medium) in Fig. 8 (bottom). The
time at which the first peak appears in Rx is the time delay for
the transmitted EM wave to travel through 27 cm of wet sand
plus 27 cm of volume medium. Note that although the entire
Tx and Rx waveforms are shown in Fig. 8, the area of interest
is the first peak of the Rx past Tx time = 0. The rest of the
waveform is ignored for traveltime tomography.
Fig. 6b. Actual photo of the in-house built 1 kV spark gap.
data; it includes a first arrival peak picking routine. For each
data set, 100 shots from the scope were captured and averaged
to improve the signal to noise ratio.
The experiment was performed in two phases. The first
phase of the experiment was to determine the time delays
based on the different media contained in the buried volumes.
For these tests, the transmitter and receiver antennas were
fixed on the tank with the EM waves shooting directly through
the middle of the buried volume (i.e., the signal passing
through both wet sand and the volume medium). This data
showed the basic differential time delays for air, sand, water
and MNPs, which inversely compared their respective material
properties (permittivity and permeability).
The second phase of the experiment was to create a 1D
Fig. 7. Experimental schematic of 1D MNP volume imaging in the lab scale
reservoir.
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Medium
µ Calculated from Measured
Time Delay
Air only
1.0
Air volume
1.1
Water volume
1.0
Wet sand
1.0
MNP volume
6.2
Table 2. The back calculated values of μ from measured time delays in the
T
reservoir model
Fig. 8. The Tx signal (top) and the Rx signal (bottom) for each of the four main
quadrants showing different measured arrival times for air, sand, water and
MNPs.
Time
Delay (ns)
Measured
Time
Delay (ns)
Calculated
Air only through 54 cm
near top of the tank
2
2
Air volume (27 cm) plus
wet sand (27 cm)
3.5
5
Wet sand (54 cm)
9.5
8-10
Water volume (27 cm)
plus wet sand (27 cm)
12
12
MNP volume (27 cm)
plus wet sand (27 cm)
24.5
16
Medium
Table 1. Measured vs. calculated time delays of different media in lab scale system
Table 1 shows the measured time delays (first peak from
Fig. 8 waveforms) and calculated time delays for EM waves
traveling through the air, wet sand, water and MNP volumes
in addition to the wet sand surrounding the volumes. The EM
waves traveled a distance of 54 cm; part of it was within the
volume medium, while the other part was in the wet sand surrounding the volume on both sides, as previously illustrated in
Fig. 5. Comparative time delay values for each medium were
calculated based on Eqns. 1 and 2 using the published values
of µ and є for air (1, 1.3), water (1, 80), wet sand (1, 25) and
MNP (2, 80), respectively.
d
t = __
(2)
V
where t is traveltime, V is the speed in the medium, and d is
the distance.
The є of wet sand was chosen as 25 for our calculation, from
published values that vary from 20 to 30 depending on the type
of sand15. The є of MNPs was the same as for water, 80, while
the µ could not be measured due to the large paramagnetic
properties of the fluid, but it was estimated to be 2.
It is noted that the delay for the air volume quadrant was
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Fig. 9. Vertical position vs. arrival time for the MNP quadrant of the tank
showing a 1D image of the MNP volume.
smaller than expected because the calculated time was a lineof-sight estimate neglecting multipath, refraction and air-short
effects. Such effects are apparently non-negligible in the case of
the air volume. In this case, the EM waves should have traveled through two different media (wet sand and immersed air
volume) in three stages: from the transmitter through 13.5 cm
of wet sand, then through the immersed air volume, and finally
through 13.5 cm of wet sand from the other side, Fig. 5. Subsequently, it seems that it traveled through the shortest path.
For the other three quadrants and for the entire air medium in
the top of the tank, the measured and expected delays are in
general agreement. This data show that the lab scale system
can accurately model propagation speeds of EM waves
through selected medium based on differences in their µ and є.
To verify known medium permeabilities with measured time
delays, a back calculation of Eqns. 1 and 2 was used to solve
for µ. The calculated values are shown in Table 2.
It is obvious that the back calculated µ for the air volume is
higher than the known permeability (Eqn. 1) for the same
reason as given for the difference between calculated and
measured time delay, as was seen in Table 1.
The second phase of the experiment was to image the volume of MNPs vertically through the tank, starting with the air
in the empty space at the top of the tank, moving down
through the volume and finally moving through the wet sand
underneath the volume. Figure 9 illustrates the vertical position of the transmitter and receiver vs. arrival times for the
MNP quadrant of the tank. The first five stations correspond
to wave propagation through air only. Stations 6 and 7 show
the time delays getting longer as the wave starts moving
through the neck, tapering off the volume, while the largest
time delay (24.5 ns) occurs at Station 8 when the wave moves
through the entire 27 cm diameter of the volume. Station 9 at
the interface of the bottom of the volume with the wet sand is
reflected in the time delay as the wave moves partially through
the MNPs and partially through wet sand. At Station 10, the
wave travels through the wet sand only, with the same time delay as obtained in the first phase of the experiment at 9.5 ns.
The plotted data thereby revealed a 1D image of the volume of
MNPs through the received time delays.
The success in accurately differentiating time delays with respect to different reservoir-like model media and the ability to
create a 1D image of the MNPs using traveltimes demonstrate
the concept of using MNPs in the injected fluids to spatially
map the flood front inside the reservoir.
CONCLUSION
Lab tests have demonstrated the capability of using traveltime
tomography to differentiate between different media in a 2,000
liter tank (reservoir model). The first arrival traveltimes of EM
waves passing through air, wet sand, water and MNPs were
accurately measured and processed to generate a 1D image of
the container within the lab scale reservoir at good resolution.
This achievement is a big step forward on the road to exhibiting
the concept in shallow wellbores in the field. The next phase
involves 3D vertical imaging of the tank quadrants using the
MNM system and specialized bh_tomo software to automate
first peak picking, data sequencing and inversion to create an
accurate 3D image of the lab scale reservoir. The first field test
in shallow wellbores is planned for the second quarter of 2013.
ACKNOWLEDGMENTS
The authors would like to thank the management of Saudi
Aramco for their permission to publish this article. We would
also like to acknowledge the valuable assistance received from
Jim J. Funk and Mohammed H. Subahi.
This article was presented at the SPE Middle East Oil and
Gas Show and Exhibition, Manama, Bahrain, March 10-13,
2013.
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2. Brzostowski, M.A.: “3D Tomographic Imaging of NearSurface Seismic Velocity and Attenuation,” Geophysics,
Vol. 57, No. 3, 1992, pp. 396-403.
3. Zhou, Q.: “Audio-Frequency Electromagnetic Tomography
for Reservoir Evaluation,” Ph.D. thesis, Lawrence Berkeley
Laboratory, University of California, Earth Sciences
Division, October 1989, p. 175.
4. Nekut, A.G.: “Electromagnetic Ray-Trace Tomography,”
Geophysics, Vol. 59, No. 3, March 1994, pp. 371-377.
5. Yu, L. and Edwards, R.N.: “On Crosswell Diffusive TimeDomain Electromagnetic Tomography,” Geophysical
Journal International, Vol. 130, No. 2, August 1997, pp.
449-459.
6. Takasugi, S., Miura, Y. and Arai, E.: “Conceptual Design
of an Electromagnetic Tomography System,” Journal of
Applied Geophysics, Vol. 35, Nos. 2-3, September 1, 1996,
pp. 199-207.
7. Wilt, M., Lee, K., Alumbaugh, D., Morrison, H.F., Becker,
A., Tseng, H.W. and Torres-Verdin, C.: “Crosshole
Electromagnetic Tomography: A New Technology for Oil
Field Characterization,” The Leading Edge, Vol. 14, No. 3,
March 1995, pp. 173-177.
8. Constable, S.: “Ten Years of Marine CSEM for
Hydrocarbon Exploration,” Geophysics, Vol. 75, No. 5,
2010, pp. A67-A81.
9. Zhou, C.G., Liu, L. and Lane, J.W.: “Nonlinear Inversion
of Borehole-Radar Tomography Data to Reconstruct
Velocity and Attenuation Distribution in Earth Materials,”
Journal of Applied Geophysics, Vol. 47, Nos. 3-4, 2001,
pp. 271-284.
10. Farmani, M.B., Keers, H. and Kitterød, N.O.: “TimeLapse GPR Tomography of Unsaturated Water Flow in an
Ice-Contact Delta,” Vadose Zone Journal, Vol. 7, No. 1,
2008, pp. 272-283.
11. Giroux, B., Gloaguen, E. and Chouteau, M.: “bh_tomo –
a Matlab Borehole Georadar 2D Tomography Package,”
Computers & Geosciences, Vol. 33, No. 1, January 2007,
pp. 126-137.
12. Lu, H.M., Zheng, W.T. and Jiang, Q.: “Saturation
Magnetization of Ferromagnetic and Ferromagnetic
Nanocrystals at Room Temperature,” Journal of Physics
D: Applied Physics, Vol. 40, No. 2, January 21, 2007, pp.
320-325.
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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45
13. Schmalholz, J., Stoffregen, H., Kemna, A. and Yaramanci,
U.: “Imaging of Water Content Distribution Inside a
Lysimeter Using GPR Tomography,” Vadose Zone
Journal, Vol. 3, No. 4, November 2004, pp. 1,106-1,115.
14. Hanafy, S. and Al Hagrey, S.A.: “Ground Penetrating
Radar Tomography for Soil Moisture Heterogeneity,”
Geophysics, Vol. 71, No. 1, January 2006, pp. 9-18.
15. Martinez, A. and Byrnes, A.P.: “Modeling DielectricConstant Values of Geologic Materials: An Aid to
Ground Penetrating Radar Data Collection and
Interpretation,” Current Research in Earth Sciences,
Bulletin 247: part 1, 2001.
BIOGRAPHIES
Abdullah A. Al-Shehri joined Saudi
Aramco in 2002 as a Communications
Engineer. He first worked with the
Communication Engineering &
Technical Support Department.
Abdullah undertook a number of
advanced development projects as well
implementation of the latest technologies
as the design and imp
related to satellite and wireless communications systems.
In late 2009, he moved to the Exploration and
Petroleum Engineering Center — Advanced Research
Center (EXPEC ARC) and joined the in situ sensing and
intervention focus area of the Reservoir Engineering
Technology Team. Abdullah participated in industry
leading research on nanotechnology to employ the concept
of sending nano-agents (Resbots™) through the reservoir
to collect data for engineering functions. Also, he worked
on the Magnetic NanoMappers research program in an
effort to develop new technology for tracking flood front in
the reservoir.
Abdullah received his B.S. degree from King Fahd
University of Petroleum and Minerals (KFUPM), Dhahran,
Saudi Arabia, in 2002, and his Applied Science M.S. degree
from Concordia University, Montreal, Quebec, Canada,
both in Electrical Engineering.
Dr. Erika S. Ellis is a Petroleum
Engineer working in Saudi Aramco’s
Reservoir Engineering Group
researching nano and micro electromechanical systems (NEMS/MEMS) to
help illuminate oil reservoirs. Prior to
joining the company in 2013, she
Argonne National Laboratory in Chicago,
spent 9 years at Argo
IL, developing thick-film gas micro-sensors for a variety of
applications. Erika spent the last 14 years in R&D in
Dallas, TX, developing and characterizing new materials
and process integration schemes for MEMS applications
for Fortune 500 semiconductor companies.
She received her B.S. degree in Applied Physics from
Lewis University, Romeoville, IL, and her M.S. degree in
Applied Physics from Northern Illinois University, Dekalb,
46
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
IL. Erika then received her Ph.D. degree in Materials
Science and Engineering from the University of Texas at
Arlington, TX.
JJesus M. Felix Servin has been working
with Saudi Aramco’s Reservoir
Engineering Technology Team focused
on in situ sensing since February 2012.
In this short time, he has made major
contributions in the ongoing success of
the Magnetic Nano-Mappers project,
hardware
design and in-house fabrication, instruiincluding
l di h
d
d
mentation, computer programming and data processing.
Jesus’s interests include the development of nano-scale
strategies for reservoir illumination and electromagnetic
methods for reservoir description and monitoring.
He received his B.S. degree in Engineering Physics from
Instituto Tecnologico y de Estudios Superiores de Monterrey,
Monterrey, Mexico, and a M.S. degree in Chemical and
Biological Engineering from King Abdullah University of
Science and Technology, Thuwal, Saudi Arabia.
Dr. Dmitry V. Kosynkin is a Petroleum
Engineer in Saudi Aramco’s Reservoir
Engineering Technology Division.
Before joining Saudi Aramco, he
worked as a Research Scientist at Rice
University, Houston, TX, studying
synthesis and applications of hybrid
nanomaterials.
t i l
Dmitry received his M.S. degree in Chemistry from M.V.
Lomonosov Moscow State University, Moscow, Russia, in
1989 and then received his Ph.D. degree in Organic Chemistry
from the University of Houston, Houston, TX, in 1997.
Dr. Mazen Y. Kanj is a Petroleum
Engineering Specialist with the
Reservoir Engineer Technology Team
of the Exploration and Petroleum
Engineering Center — Advanced
Research Center (EXPEC ARC). He is
the focus area champion on reservoir
iin situ
it sensing
i and
d iintervention. Before joining Saudi
Aramco in 2003, Mazen held a Senior Scientist position
with the Poromechanics Institute of the University of
Oklahoma, Norman, OK. He was an invited member of
the Poromechanics Committee of the American Society of
Civil Engineers and an Associate Editor for the Society of
Petroleum Engineer’s SPE Journal.
Mazen received his B.S. and M.S. degrees from the
American University of Beirut, Beirut, Lebanon, and a
Ph.D. degree from the University of Oklahoma, Norman,
OK, all in Civil Engineering.
Dr. Howard K. Schmidt is a Petroleum
Engineering Consultant with the
Reservoir Engineering Technology
Team of the Exploration and
Petroleum Engineering Center —
Advanced Research Center (EXPEC
ARC). He leads the Magnetic
NanoMappers
project
within the In-Situ Sensing and
N
M
j
Intervention (ISSI) focus area. Prior to joining Saudi
Aramco, Howard was at Rice University where he served
as Senior Research Fellow in the Chemical and
Biomolecular Engineering Department and Executive
Director of the Carbon Nanotechnology Laboratory. While
there, Howard also served as the founding Senior
Nanotechnology Advisor to the Advanced Energy
Consortium (AEC).
He received his B.S. degree in Electrical Engineering in
1980, and his Ph.D. degree in Chemistry in 1986, both
from Rice University, Houston, TX.
Howard has 50 peer-reviewed publications and a dozen
issued patents.
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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47
Fig. 1. A schematic of the ADR LWD tool.
response of a traditional LWD wave propagation tool in a 10
ohm-m formation that is bounded by two conductive beds of 1
ohm-m is shown in Figs. 3a and 3b. As explained in Bittar, et
al. (2007)12, as the tool approaches the resistive bed from the
top, the tool starts to read the high resistivity (polarization effect), and as the tool approaches the conductive lower formation at the bottom, the tool also starts to read high resistivity
(similar polarization effect). The tool reading is the same
whether the tool approaches the conductive formation from
the top or the bottom. This similarity comes from the lack of
azimuthal sensitivity, which consequently makes geosteering
uncertain.
The computed response of the ADR tool, which was used
on the same model, Fig. 3, is shown in Fig. 4. Figure 4a shows
the well trajectory, Fig. 4b shows the high side and low side
Fig. 2. Binning system.
imuthal measurement cover the entire range, from shallow to
very deep, allowing mapping of formation resistivity from near
the borehole to up to 20 ft away radially13, 14.
Resistivity readings are performed at 32 different angular
positions, or bins, which are regularly spaced, Fig. 2. Bin 1,
referred to as the up bin, is that sector for which the angle
between the coordinate vertical vector pointing upwards and
the magnetic moment of the tilted receiver (vector normal to
the surface of the receiver coil, using the right-hand convention
for the winding direction of the coil) is minimum in a deviated
well; similarly, bin 17, referred to as the down bin, is that sector for which this angle is maximum. In addition to the 32
azimuthal resistivity measurements, an average resistivity is
produced from the measured 32-bin phase difference or attenuation; the tool transforms them to phase and attenuation
resistivity, respectively, through homogeneous resistivity transforms. All azimuthal readings are equal if the measurements
are not affected by adjacent layers. When the well approaches
a layer boundary, azimuthal readings demonstrate characteristic differences that indicate a formation entrance or exit15.
Traditional LWD wave propagation tools lack the azimuthal
sensitivity that provides directional information12. The computed
Fig. 3a. Trajectory of a well in a three layer medium.
Fig. 3b. Response of a traditional LWD wave propagation tool.
Fig. 4a. Trajectory of a well in a three layer medium. Fig. 4b. Resistivity responses
of the azimuthal deep reading resistivity tool. Fig. 4c. Geosignal or directional
geosteering signal.
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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resistivities, and Fig. 4c shows the geosignal, or the directional
geosteering signal12. The geosignal is the difference between
measurements determined at the opposite azimuthal orientations
of the tool. The important point is that as the tool approaches
the bottom formation, the low side resistivity (resistivity from
bin 17) reads as a much lower resistivity, indicating that the
tool is approaching a conductive bed from the bottom of the
high resistivity zone. When the tool approaches the conductive
bed from the top of the high resistivity zone, the high side
resistivity (resistivity from bin 0) reads as a lower resistivity,
indicating that the tool is approaching the conductive zone
from the top of the high resistivity zone. Similarly, the directional
geosteering signal decreases as the tool approaches the conductive boundary from the bottom of the high resistivity zone and
increases as the tool approaches the conductive boundary from
the top of the high resistivity zone.
INVERSION METHODOLOGY
Before drilling a target well, offset wells drilled in the vicinity
can provide useful information, such as the expected resistivity
and thickness of formation layers, which can be used as
known parameters for a simple distance-to-boundary inversion. Although the distance-to-boundary inversion can be a
fast calculation, the accuracy of the inversion result is adversely affected if the actual resistivity values are different from
the assumed values. A flexible inversion method without resistivity input was developed to consider such conditions.
The inversion method introduced here targets the solution
of layer resistivities and boundary positions with a GaussNewton minimization scheme. For parameterization of formation unknowns, a three-layer model, Fig. 5, is used where Dup
is the distance to the up boundary and Ddn is the distance to
the down boundary, with the tool assumed to be in the intermediate layer. The inversion method is based on an iterative
1D forward model that minimizes the difference between the
raw measurement and the simulated response to obtain true
formation parameters. The inversion is done independently at
each logging point to avoid bias from past measurements. The
dip angle is input as a fixed value.
Fig. 5. Three layer formation model for boundary and resistivity inversion.
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
The 1D forward modeling response of the ADR tool can be
expressed as S while the formation parameter can be written
as, X , where: X ȏ {R1,R2,R3,Dup,Ddn}; and the cost function C
is defined as:
C = Wd . ( S _ M )
ȕ.
+
X
_
Xo
(1)
M represents the measurement, while || || is the L2 norm of the
misfit vector. The inversion is designed to optimize the parameter
vector X for minimization of Eqn. 1. The first part of the formula
is the misfit between the simulation data and the field logs, and
the second part is the regularization term designed to stabilize
the inversion, which may include any a-priori information. Xo
is the reference value of vector X , and ȕ represents the degree
of confidence of the reference value for each inverted parameter. The Gauss-Newton minimization approach is used for the
numerical optimization procedure. Both the resistivity and the
geosignal are required as inputs to the inversion to avoid ambiguities with the boundary positions. Wd is the weight matrix
for the data used to influence the measurement contribution
from each signal in the cost function.
The described inversion method can process simple formation structures with a single boundary, i.e., a two-layer formation model. This one-boundary inversion is known to handle
complex cases better when only one shoulder layer provides
the dominant effect on the response and the contribution of
another layer is too weak to estimate its property16.
The inversion method is demonstrated in the following
sections with two field test examples.
FIELD EXAMPLE 1
Figure 6 shows the field recorded ADR geosignal and resistivity log data for an interval of a well.
Figure 6a presents the up and down attenuation geosignal
curves of the 48” spacing, Ga48b1 and Ga48b17, for the operating frequency of 500 kHz. Figure 6b displays the average as
well as the up and down phase resistivity curves of the 16”
spacing at 500 kHz, Rp16b1, Rpavg16 and Rp16b17. Considerably large separations between up and down readings are
observed in both the geosignal and resistivity values at x700 ft,
Fig. 6. Raw responses (Example 1). Fig. 6a. Geosignal data from attenuation
readings of bins 1 (up) in green and 17 (down) in blue for the 48” transmitter
receiver distance. Fig. 6b. Phase apparent resistivity for the 16” transmitter
receiver combination for bins 1 (up) in green and 17 (down) in red. Also the
average of all bins is included in blue.
x800 ft, x900 ft and x1,600 ft, which indicate the tool is approaching a boundary. The overlap of responses in some other
sections indicates that the tool is far from the boundary or that
the logging point is at the electrical middle point, a point that
has canceling effects from the upper and lower layers.
The inversion method is used to obtain the resistivities of
the three layers and the distances to the up and down boundaries, where the dip angle is assumed to be 80°, which is adequate for the point-by-point inversion performed here. Figure
7a shows the overall well placement in the formation. The well
path is shown as the blue curve and the inverted up and down
boundary positions are shown in green and red, respectively. In
this case, the well trajectory is in a thin resistive layer, approximately 5 ft thick. It approaches the top layer (layer 1 in the
model of Fig. 5) at x700 ft and x900 ft, and approaches the
bottom layer (layer 3 in the model of Fig. 5) at x800 ft and
x1,400 ft. Figure 7b shows the resistivity obtained from the
inversion. This confirms that the hosting layer is more resistive
that the top and bottom layers.
Figure 8 shows the comparison between raw responses and
ADR simulation data, with inverted formation parameters for
verification and quality control purposes. In Fig. 8a, the raw
average resistivities of 16”, 32” and 48” (Rpavg16, Rpavg32
and Rpavg48, respectively) are plotted and compared with the
respective simulated data (Rpavg16s, Rpavg32s and Rpavg48s).
Figure 8b includes four curves: the raw up attenuation geosignal
of 48” (Ga48b1), the down attenuation geosignal of 96”
(Ga96b17), and their respective simulated responses (Ga48b1s
and Ga96b17s), with the final inverted resistivity and boundary position. There is good agreement among the measurements and simulation data for both the resistivity and
geosignal responses.
FIELD EXAMPLE 2
Fig. 7. Field Example 1.
Fig. 7a. Boundary position and well trajectory. Fig. 7b. Inversion results showing
the resistivity values of a three-layer model as presented in Fig. 5.
Figure 9 shows the field ADR geosignal and average resistivity
log data for a second well. The dip angle is assumed to be 80°,
which is adequate for the point-by-point inversion performed
here.
Figure 9a shows the up and down attenuation geosignal
curves of the 48” transmitter receiver pair at 500 kHz:
Ga48b1 and Ga48b17. Figure 9b shows the up, average and
down phase resistivity curves of the 16” transmitter receiver
pair at 500 kHz: Rp16b1, Rpavg16 and Rp16b17. Obvious
separations between the up and down readings are shown in
the geosignal values in the middle of the section, which indicate the tool is near a boundary. The overlapping responses at
the start and end of the section indicate that the tool is electrically far from the boundary (the boundary is beyond the depth
of investigation of the tool so the measurement is very small or
naught) or that the logging point is at the electrical middle
point of the zone (where the electrical effect of the top and
bottom boundaries of the hosting layer cancel each other). The
resistivity plot shows three curves: Rp16b1, Rp16avg and
Rp16b17. All are over 10 ohm-m. The down resistivity reading, Rp16b17, reaches extremely large values up to thousands
of ohm-m, which indicates the tool is very close to the boundary between two high contrast layers. The up resistivity reading is higher than the down resistivity reading at the section
from x020 ft to x080 ft and less than the down resistivity reading after x080 ft. This indicates that the well may have penetrated a layer boundary. Because the well is in the vicinity of a
single boundary, and ADR measurements are mainly affected
by the two layers, the one-boundary inversion method is suitable for handling this type of data.
Figure 10 presents the inversion results of the boundary
position and resistivity values of the two layers using the single
boundary inversion method. In Fig. 10a, the inverted boundary
Fig. 8. Comparison of field measurements and synthetic curves (Field Example 1).
Fig. 8a. Average apparent phase resistivities for 16”, 32” and 48” transmitter
receiver distance. Fig. 8b. Comparison of field and synthetic attenuation
geosignals for 48” and 96” spacings, up and down bins, 1 (green) and 17 (red),
respectively.
Fig. 9. Raw responses (Example 2). Fig. 9a. Field geosignals from attenuation for
the 48” transmitter receiver distance at 500 kHz up bin 1 in blue and down bin
17 in green. Fig. 9b. Phase resistivity for the 16” transmitter receiver distance at
500 kHz frequency: up bin 1 in green and down bin 17 in red, and the average of
all bins in blue.
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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51
96” down bin, bin 17, illustrates a good match even for the
96” spacing, which reads deeper into the medium in the downward direction and is included here for verification purposes.
CONCLUSIONS
Fig. 10. Inversion results for Example 2. Fig. 10a. Nearest boundary position
from inversion in green and well trajectory in blue. Fig. 10b. The inverted hosting
layer resistivity in blue and the nearest shoulder layer resistivity in green.
Fig. 11. Data comparison for Example 2. Fig. 11a. The phase apparent resistivity
for 16”, 32” and 48” transmitter receiver spacings for both raw and simulated
data. Fig. 11b. Comparison of geosignals from attenuation for 48” and 96”
spacings for the up bin (1) and down bin (17), respectively, for raw and simulated
data.
position plot, the well path in blue is plotted with the nearest
formation boundary location in green. The top layer is followed at 1 ft distances from x080 ft to x800 ft. An approach
to the shoulder layer is observed from x020 ft to x080 ft and
again briefly at x810 ft. The inversion results for the two resistivity layers, Rmid and Rmin, for the interval from x080 ft to
x800 ft are shown in Fig. 10b. Rmid, which is the resistivity of
the hosting layer in which the borehole well trajectory is moving, ranges from 30 ohm-m to 100 ohm-m. The shoulder layer
resistivity, Rmin, averages about 4 ohm-m.
In the interval between x020 ft and x080 ft and also at
x810 ft, the opposite behavior is observed: the shoulder layer
has a higher resistivity than the hosting layer, implying that the
well trajectory crossed from one layer to the other during
drilling. From the boundary and resistivity inversion results, the
well trajectory is observed to be in a highly resistive formation.
It exits this layer to enter the bottom low resistivity layer at
x020 ft; moves back up to the high resistivity layer at x080 ft;
and finally makes a transitory exit to the shale layer at x800 ft.
Figure 11a displays a comparison between the raw measurements and the simulated data for the inversion result in Fig.
10. The curve names are similar to those in Example 1. Again,
good agreement is observed in the comparison of the average
resistivity at 16”. As expected, the strong polarization effect
induces larger discrepancies for the average resistivity at 32”
and 48”, where the sensitivity is weaker at high resistivity
values. The comparison between the raw and simulated attenuation geosignals in Fig. 11b for the 48” up bin, bin 1, and the
52
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
A new inversion method has been developed that allows the
advanced interpretation of data from LWD propagation resistivity tools. The inversion method uses resistivity (average, up
and down) and geosignal measurements to locate and measure
the resistivity of shoulder beds. This method can be used along
with single and dual boundary formation models in appropriate scenarios. The new inversion method has been tested with
field data from multiple wells. The accuracy of the inversion
method was demonstrated by examining the raw responses,
then comparing the raw measurements with the simulated data
from the inversion results. Overall, the new interpretation
method is able to provide the resistivity and distance to the
boundary of formation layers without prior geological knowledge. This makes it possible to use LWD resistivity measurements for advanced formation evaluation and well geosteering.
ACKNOWLEDGMENTS
The authors would like to thank the management of Saudi
Aramco for their permission to publish this article. We would
also like to thank both Saudi Aramco and Halliburton for
funding the Cooperative Project on Advanced Reservoir
Resistivity Interpretation in High-Angle Wells. We appreciate
the very valuable comments by Denis Schmitt.
This article was presented at the SPE Saudi Arabia Section
Annual Technical Symposium and Exhibition, al-Khobar,
Saudi Arabia, May 19-22, 2013.
REFERENCES
1. Rodney, P.F., Wisler, M.M., Thompson, L.W. and Meador,
R.A.: “The Electromagnetic Wave Resistivity MWD Tool,”
SPE paper 12167, presented at the 58th Annual Technical
Conference and Exhibition, San Francisco, California,
October 5-8, 1983.
2. Fredericks, P.D., Hearn, F.P. and Wisler, M.M.: “Formation
Evaluation While Drilling with a Dual Propagation
Resistivity Tool,” SPE paper 19622, presented at the SPE
Annual Technical Conference and Exhibition, San Antonio,
Texas, October 8-11, 1989.
3. Rodney, P.F., Mack, S.G., Bittar, M.S. and Bartel, R.P.: “An
MWD Multiple Depth of Investigation Electromagnetic
Wave Resistivity Sensor,” paper 1991-D, presented at the
SPWLA 32nd Annual Logging Symposium, Midland, Texas,
June 16-19, 1991.
4. Bittar, M. and Rodney, P.F.: “The Effect of Rock
Anisotropy on MWD Electromagnetic Wave Resistivity
BIOGRAPHIES
Dr. Pedro Anguiano-Rojas joined
Saudi Aramco in 2011, where he is the
Resistivity Logging Specialist in the
Reservoir Description Division. His
main interests are inversion theory and
its applications, and modeling in
geophysics and petroleum engineering.
Prior to joining the ccompany, Pedro worked at the Mexican
Petroleum Institute in Mexico.
He received his B.S. degree in Geophysical Engineering
from the National Autonomous University of Mexico
(UNAM) in Mexico City, Mexico. Pedro then received his
M.S. in Geomathematics from Stanford University, Palo
Alto, CA, and a Ph.D. in Geophysics from the Colorado
School of Mines, Golden, CO.
Pedro is a member of Society of Petrophysicists and
Well Log Analysts (SPWLA) and the Society of Petroleum
Engineers (SPE).
Douglas J. Seifert is a Petrophysical
Consultant with Saudi Aramco, where
he works as the Petrophysics
Professional Development Advisor in
the Upstream Professional
Development Center (UPDC). Doug
specializes in real-time petrophysical
fluid analysis. Before joining Saudi
applications and flui
Aramco in 2001, he was the Western Hemisphere Regional
Petrophysicist for Pathfinder Energy Services in Houston,
TX, and the Eastern Hemisphere Regional Petrophysicist in
Stavanger, Norway. Doug also worked as the Senior
Petrophysicist for Mærsk Olie Og Gas in Denmark; for
Halliburton Energy Services in various operational,
research and technical support functions; and for Texaco in
their Technical Services and Production Operations.
Doug is the President of the Saudi Petrophysical Society
and the Saudi Arabian Chapter of the Society of
Petrophysicists and Well Log Analysts (SPWLA), and he
also serves on the SPWLA Technology Committee.
He received a B.S. degree in Statistics and a M.S. degree
in Geology, both from the University of Akron, Akron,
OH.
Dr. Michael Bittar is Senior Director
of Technology for Halliburton. He
joined Halliburton in 1990 and since
then has held various technical and
leadership roles, including Halliburton
Technology Fellow, Director of
Research and Senior Director of
Evaluation.
Formation Evaluatio
Michael received his B.S., M.S. and Ph.D. degrees, all in
Electrical Engineering, from the University of Houston,
Houston, TX, in 1983, 1986 and 1990, respectively. He
has more than 20 patents and is the author of more than
20 publications.
54
FALL 2013
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
Michael is a long-term member of the Society of
Petroleum Engineers (SPE) and the Society of
Petrophysicists and Well Log Analysts (SPWLA). He was
the recipient of the 2006 SPWLA Technical Achievement
Award and the 2009 Halliburton Outstanding
Commercialized Invention of the Year Award for his
invention and the development of the Azimuthal DeepReading Resistivity technology.
Dr. Sami Eyuboglu became a Program
Manager at the Halliburton Dhahran
Technology Center, Saudi Arabia, in
February 2012. He has been with
Halliburton Energy Services since April
2008. Sami specializes in both logging
while drilling and wireline pump-out
Prior to this, he was a Research Professor
fformation
ti ttesters.
t
P
at Ohio State University, where he worked in developing
computer programs for surface geophysical methods and
numerical modeling of ground penetrating radar (GPR).
These applications include national security issues (UXO
and tunnel detection) and the environment.
Sami received his B.S. and M.S. degrees in Mining
Engineering from the Hacettepe University, Ankara, Turkey,
and his Ph.D. degree in Applied Physics from the University
of Arkansas at Little Rock, Little Rock, AR.
Dr. Yumei Tang joined Halliburton as
a Scientist in the Electromagnetics
Group in 2008. She started working in
the processing and analysis of logging
data generated by electromagnetic
probes. Currently, Yumei is involved
with logging while drilling resistivity
modeling support.
interpretation and m
In 2008, she received her Ph.D. degree in Electrical
Engineering from the University of Houston, Houston, TX.
Dr. Burkay Donderici has been with
Halliburton for five years, where he
has worked in the position of Principal
Scientist in the Electromagnetics and
Acoustics Groups. He has been leading
the Electromagnetics Sensor Physics
Team for Halliburton since 2011.
Burkay
B
k iis currently
tl iinvolved in research and development
of technologies based on electromagnetics for oil field
applications.
He received his Ph.D. degree in Electrical and Computer
Engineering from Ohio State University, Columbus, OH.
Integrated Geology, Sedimentology and
Petrophysics Application Technology for
Multimodal Carbonate Reservoirs
Authors: Roger R. Sung, Dr. Edward A. Clerke and Dr. Johannes J. Buiting
ABSTRACT
The complexity and heterogeneity of carbonate reservoirs
makes them extremely difficult to characterize and develop.
The very large reserve base of carbonate fields in the Middle
East requires thorough field development strategies to optimize
ultimate recovery and meet rate forecasts. The very highest
quality 3D geological models and rigorous reservoir simulation
are required. The geological model must combine all geological, geophysical, core and rock property information together
with interpretation data to deliver the best 3D representation
of these complex carbonate reservoirs. These models rely on
pertinent lithofacies derived from core descriptions using sequence stratigraphic processes, and static and dynamic fluid
and pore architecture properties obtained from laboratory
analyses of core and log data. Current understandings of our
major limestone reservoirs have established that these reservoirs
commonly contain nested multimodal pore systems. Extensive
datasets have been obtained to determine and classify these
pore systems by Clerke et al., (2008)1 in a facies framework.
These data differentiate various macropore and micropore
throat families (the “porositons” of Clerke1-3), their statistics,
the pore throat to pore body relationships and their flow properties. Understanding the distribution of the hydrocarbon volumes in the various pore-type combinations identified in the
Rosetta Stone Petrophysical Rock Types (RSPRT) and then
establishing proper recovery analyses and techniques could improve the field development strategies, explain reservoir high
recoveries and lead to optimal recovery.
The new application and workflow presented in this article
describes the geological model construction process from the
sequence stratigraphic framework and facies to the billion-cell
geomodel and simulation. The process utilizes deterministic facies models derived from a sequence stratigraphic framework,
a facies controlled geostatistical population of static rock properties and RSPRT, followed by controlled stochastic pore system parameter assignments. The workflow depends heavily on
the use of abundant core description data available in a digital
format. Macroporosity and microporosity volumes are assigned to each geological model cell. Then, by incorporating
multimodal Thomeer petrophysical algorithms, critical reservoir attributes (permeability, relative permeability and time
dependent spontaneous imbibition recovery) are calculated at
each geocell2, 4. This technology unites the diverse geoscience
disciplines of geology, sedimentology, petrophysics and reservoir engineering and simulation. We are applying this technology to Saudi Aramco carbonate fields. Significant bottom line
impact is expected from this “Billions-to-Microns-toBillions”paradigm shift.
INTRODUCTION
Reservoir characterization and simulation for production requires a complete integration of all of the subsurface geoscience data and analyses. These subsurface disciplines —
geology, sedimentology, geophysics, petrophysics, reservoir
modeling and reservoir engineering — acquire their respective
domain data samples and have the data coded specific to their
discipline, which is not necessarily tied to reservoir integration.
Even in today’s production interpretation environment, obstacles continue to limit the fully integrated use of information
and observations by geologists, sedimentologists, petrophysicists, geological modelers and reservoir engineers.
In Saudi Aramco, the advent of very large computing and
simulation systems allows the reservoir simulation to occur at
nearly native vertical sampling rates with dense geocellular
grids, no longer restricting the use of all of the geoscience data.
This advance requires that our seminal geoscience data become
even more tightly integrated.
This article describes our efforts (workflows and systems) to
finely integrate our reservoir geoscience data and interpretation
for use in high resolution reservoir simulation. Particular attention is paid to a coherent multidisciplinary sampling strategy
that allows seamless information transfer across the disciplines.
Petrophysical and reservoir property samples and sample statistics are handled both by depth in wells and also by facies
memberships, modified by high frequency sequence stratigraphic parasequence indices. Reservoir model construction is
more detailed as layer properties after propagation are reviewed for consistency with facies and parasequence-based
reservoir statistics, as well as conventionally compared to
porosity and permeability statistics. The application and workflow technology in this article provides seamless and high vertical frequency digital integration and collaboration among the
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MODELING APPROACH
Days or weeks are usually spent on the computation of 3D
model attributes; despite this effort, the guiding geological facies models have not been generally well integrated5. Billions
of cell attribute calculations could be wasted due to inappropriate algorithms. Micron-level core analysis, while accurate,
generally lacks the proper sampling program to establish integration hooks to the rest of the digital interpretation and
modeling applications and systems. In these important nested
bimodal carbonate reservoirs, it has been shown that two distinct domains of waterflood production are evident2, 4. The
first mechanism is a time dependent spontaneous imbibition of
water and expulsion of oil from Type 1 micropores to adjacent
M macropores, and the second mechanism is a conventional
forced imbibition (a Buckley-Leverett piston-like displacement)
of oil by water in highly permeable macropores. The larger
macropore volumes (~ 75% of total pore volume) and their
displacement mechanism dominate the bulk of the oil production, but for these large carbonate reservoirs that are being
produced slowly for many decades or more, the slow dry oil
production by spontaneous water imbibition controlled by the
Type 1 micropores (~25% of the pore volume) is significant.
Samples studied by Clerke et al., (2013)2 demonstrate for a
variety of bimodal samples that the spontaneous imbibition
recovery ranged from 3% to 15% of the total pore volume.
Neglecting these pore systems in the reservoir model means
either neglecting a significant portion of the total oil recovery or
mischaracterizing that slower dry oil production by incorrectly
merging it with the forced imbibition production.
The conventional geostatistical approaches used in the past
are not sufficient to handle these necessary complications of
our nested multimodal carbonate reservoirs. The workflow in
this article integrates the geological model facies and applies the
geologically guided geostatistics, taking advantage of the unbiased
geostatistical distribution while following the geological framework, Fig. 2. This invention also incorporates algorithms
derived from micron-level digital core descriptions into the 3D
geological model system. The 3D model, with its cumulative
knowledge from the smallest core to the billions of sophisticated
calculations, gives a clear reservoir picture to guide the planning
for the ultimate recovery of the field, Fig. 3.
description may have also contained what is known as
“ground truth” information, but due to its written format, this
information made little contribution to the digital geological
modeling system. While these drawings and notes conveyed the
well core information, their static graphical image nature prevented analysts from applying manipulation functions, like those
known as stretching and squeezing, required in the geological
interpretation process. Because the graphical images of well core
data did not indicate the lithology in numerical form, they could
make no digital contribution to the 3D modeling process.
To address this issue, a digital application and workflow has
been established to capture new and legacy core description
data. Carbonate and clastic core description digital templates
have been generated. Sedimentologists utilize these workflows
to describe core samples using a tablet laptop with a digital
pen. The texture, mineral composition, grain size and pore
type of carbonate rocks, as well as sedimentary structure,
lithology, grain size and visual porosity, can be entered straight
into this application, Fig. 4. Furthermore, these valuable digital
descriptions are fully integrated with the rest of the reservoir
characterization and geological modeling applications to amplify the value of the ground truth.
Fig. 2. Facies modeling workflow.
ABUNDANT LEGACY CORE DESCRIPTION
The abundant core samples from the Saudi Arabian onshore
carbonate fields have been described in many formats and
styles. Many core descriptions were hand drawn and are thereafter available for use only in the form of a paper copy or, at
best, a scanned graphical image of the hand drawing. In other
cases, the completed well core data description in the form of
notes, comments and observations was provided to reservoir
analysts for their use in lithological modeling and geologic interpretation of subsurface formations of interest. The core
Fig. 3. Water saturation and permeability modeling workflow.
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consistent RSPRT realizations for each geocell.
At this juncture, multimodal Thomeer parameters are
loaded into each geocell, consistent with the pore system
modality and the RSPRTs, and all consistent with the facies.
Modality (monomodal, bimodal, trimodal) simply indicates
whether the number of required Thomeer parameters will be
three, six or nine for each geocell. The RSPRT porositon classification constrains the domain of the required Thomeer parameter values. Thomeer Pd values are constrained by the porositon
distributions first and by facies statistics as a refinement.
So, in each geocell of the reservoir, there now resides a complete set of three, six or nine Thomeer MICP parameters (Pd,
Fig. 4. Digital core description.
FULLY INTEGRATED PETROPHYSICAL DATA AND DATABASE FOR MULTIMODAL CARBONATE RESERVOIRS
Saudi Aramco has fully characterized the multimodal pore systems that comprise the Arab-D limestone1, 2, 4, 6-8 using a comprehensive database process. The multimodal pore types are
completely identified in every geocell. The recovery behavior of
the two pore types is distinct, and using a general averaging
process to inappropriately lump together the two different
production processes is avoided. Instead the specific pore type
controlled recovery mechanism — forced imbibition in the
macropores and spontaneous imbibition in the Type 1 micropores — is modeled using the pore system data.
This database is organized with data classified by the pore
system using the porositon classification of Clerke1-3 to define
the ultimate recovery strategies by petrophysical rock types.
The importance of this classification to the prediction of ultimate waterflood recovery is further expounded in Clerke et al.,
(2013)2. Additionally, all of these data are also classified according to their membership in the sequence stratigraphic depositional facies. Figure 5 shows a sedimentary example from
Lindsay et al., (2006)8. Statistics in each classification system
are available for thorough qualification of the propagated geocellular model, as illustrated in Figs. 6 to 9.
The geocellular model starts first with a deterministic or semideterministic facies model generated using carbonate sequence
stratigraphic techniques; it also contains wellbore porosity and
permeability data. Facies distributions are propagated to cover
the interwell areas using the sequence stratigraphic model. Then
porosity and permeability are stochastically distributed within
these facies, consistent with the facies-driven RSPRT propagation, which is also performed. This new model gradually becomes converted to a facies-based, well log and core data
constrained RSPRT model. For this purpose, the statistics for the
pore system modality probabilities by porosity and permeability,
and by facies to RSPRT are used as shown in the figures. At this
point, the model contains facies, porosity, permeability and facies
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Fig. 5. A single depositional cycle of the Arab-D identified the facies8.
Fig. 6. The Rosetta Stone Project characterized Arab-D limestone pore systems
using a large set of mercury injection capillary pressure data and found that
the maximum pore throat diameters were not random but exhibited modal
behavior termed “porositons1.” Clerke identified macroporosity controlling
sample permeability and three types of microporosity.
Fig. 7. Thomeer parameter statistics compiled in the Rosetta Stone study are
used to populate the geocellular model with Thomeer pore system parameters.
Shown here is the Rosetta Stone MICP entry showing pressure data vs.
porosity for all pore systems and subsystems.
Fig. 10. Once free water enters the pore system by water injection, the water
in close proximity to oil filled Type 1 micropores is spontaneously imbibed
from the macropore and the oil is expelled to the adjacent micropore9.
Fig. 8. The assigned facies can be inspected for their statistical probability of
being assigned a RSPRT1.
G, BV) along with a total porosity value and a permeability
value for a multimodal pore system that is consistent with the
sequence stratigraphic model and the depositional facies defined by the reservoir architecture model. In the next step, the
importance of this detailed pore system data on a geocellular
scale becomes evident. Using the algorithms and data developed
for waterflood recovery in these pore systems, Clerke (2009)4
has determined that the total waterflood recovery mechanism
is also bipartite, comprising a viscous force dominated component, characterized by a conventional relative permeability
curve, and a rate dependent, capillary pressure dominated
spontaneous imbibition component2. The relative permeability
and spontaneous imbibition properties are governed by the
pore system properties within a given wettability condition in
the reservoir. Therefore, these flow properties are calculated
for every geocell in the reservoir with the implicit knowledge
of the cell position with respect to the free water level and the
pore system (Thomeer parameters) properties.
GigaPowers’ multiporosity, multipermeability9 reservoir
simulation code has been developed to receive these detailed
geocellular models. Figure 10 shows the fluid movement in the
micropores and macropores.
CONCLUSIONS
Fig. 9. The RSPRTs (color Z axis) give an organized distribution on the
porosity and permeability crossplot (left); on the right, the same plot has the
facies color coded on the Z axis1. All samples know their memberships in
multiple reservoir attributes.
The ultimate recovery characterization loop described in this
article integrates traditionally independent processes and creates new applications and workflows to link and digitally
calibrate different reservoir components to generate a sound
scientific and business reservoir solution. Geocellular model
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strategy, potentially leading to substantially improved reservoir
recovery.
ACKNOWLEDGMENTS
The authors would like to thank Saudi Aramco management
for their support and permission to publish this article.
This article was presented at the International Petroleum
Technology Conference (IPTC), Beijing, China, March 26-28,
2013.
REFERENCES
1. Clerke, E.A., Mueller III, H.W., Phillips, E.C., Eyvazzadeh,
R.Y., Jones, D.H., Ramamoorthy, R., et al.: “Application
of Thomeer Hyperbolas to Decode the Pore Systems, Facies
and Reservoir Properties of the Upper Jurassic Arab-D
Limestone, Ghawar Field, Saudi Arabia: A Rosetta Stone
Approach,” GeoArabia, Vol. 13, No. 4, 2008, pp. 113160.
Fig. 11. 3D modeling application architecture integrating geological, sedimentological and petrophysical data and interpretation.
attributes, like permeability and relative permeability, are generated for each geocell using pore system parameters consistent
with the depositional model. The process incorporates the various geological facies interpretations at each model cell location. Therefore, the geological facies play an essential role in
determining the model parameter populations, Fig. 11. The
geological facies interpretations are guided by the well log data
and core descriptions, which contain the ground truth. The
process requires that all data be fully digital, so the application
has enabled all existing and legacy core descriptions to now be
captured and integrated. Once macroporosity and microporosity data from core plug analyses or specific well log analyses
are captured digitally for input, hydrocarbons contained in
macroporosity and microporosity systems and their distinct
recovery mechanisms are characterized and assigned by geocell. The new simulations that are being developed will fully
contain the production mechanisms and physics sufficient for
these very large and long-lived carbonate reservoirs, and so
will serve as a tool to maximize waterflood recovery.
This article highlights the application and workflow loop,
which takes large 3D geocellular models with facies and full
pore system attributes; performs calculations using pore system type guidance from digitally described cores and rock core
plugs to the sub-micron level; identifies and characterizes the
macroporosity and multiple microporosity types; then, using
developed multimodal 3D petrophysical modeling programs,
contributes to an optimal macro-micro reservoir recovery
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2. Clerke, E.A., Funk, J.J. and Shtepani, E.: “Spontaneous
Imbibition of Water into Oil Saturated M_1 Bimodal
Limestone,” IPTC paper 17162, presented at the 6th
International Petroleum Technology Conference, Beijing,
China, March 26-28, 2013.
3. Ahr, W.M., Allen, D., Boyd, A., Bachman, H.N., Smithson,
T., Clerke, E.A., et al.: “Confronting the Carbonate
Conundrum,” Oilfield Review, Vol. 17, No. 1, March 1,
2005, pp. 18-29.
4. Clerke, E.A.: “Permeability, Relative Permeability,
Microscopic Displacement Efficiency and Pore Geometry of
M_1 Bimodal Pore Systems in Arab-D Limestone,” SPE
Journal, Vol. 14, No. 3, September 2009, pp. 524-531.
5. Sung, R.R. and Lewis, K.A.: U.S. Patent No. 7,359,844,
“Real Time Earth Model for Collaborative Geosteering,”
April 15, 2008.
6. Cantrell, D.L. and Hagerty, R.M.: “Microporosity in Arab
Formation Carbonates, Saudi Arabia,” GeoArabia, Vol. 4,
No. 2, 1999, pp. 129-154.
7. Cantrell, D.L. and Hagerty, R.M.: “Reservoir Rock
Classification, Arab-D Reservoir, Ghawar Field, Saudi
Arabia,” GeoArabia, Vol. 8, No. 3, 2003, pp. 435-462.
8. Lindsay, R.F., Cantrell, D.L., Hughes, G.W., Keith, T.H.,
Mueller III, H.W. and Russell, S.D.: “Ghawar Arab-D
Reservoir: Widespread Porosity in Shoaling-Upward
Carbonate Cycles, Saudi Arabia,” in P.M. Harris and L.J.
Weber (Eds.), Giant Hydrocarbon Reservoirs of the World:
From Rocks to Reservoir Characterization and Modeling,
American Association of Petroleum Geologists, Memoir
88/SEPM Miscellaneous Publication, No. 8, 2006, p. 97137.
9. Fung, L.S.K., Middya, U. and Dogru, A.H.: “Numerical
Simulation of a Fractured Carbonate with the M_1
Bimodal Pore System,” SPE paper 142296, presented at the
SPE Reservoir Simulation Symposium, The Woodlands,
Texas, February 21-23, 2011.
BIOGRAPHIES
Roger R. Sung is an Exploration
System Consultant for the Reservoir
Characterization Support Group in
Saudi Aramco. Prior to joining the
company in 1999, he was an
Exploration Application Specialist
with Union Oil of California and
Cockrell Oil in Houston, TX. Roger’s areas of interest are
reservoir characterization, petrophysics, geosteering, realtime reservoir modeling and E&P integration.
He is also one of the Saudi Aramco’s Innovation Award
recipients.
Roger has organized and served as the Executive
Chairman of an industry-wide Technology Workshop on
Global Fractured Reservoir Development.
He is the inventor of the “GeoMorph: Real Time Earth
Model for Collaborative Geosteering” (U.S. Patent No.
7,359,844). In addition, Roger has four patents pending in
the final stage with the U.S. Patent & Trademark Office.
In 1980, he received a B.S. degree in Geology from the
National Taiwan University, Taipei City, Taiwan, and he
received his M.S. degree in Exploration Geophysics from
the University of Houston, Houston, TX, in 1985.
Roger has presented and published more than 40 papers
in various journals.
He is a member of the American Association of
Petroleum Geologists (AAPG) and Society of Petroleum
Engineers (SPE).
Dr. Edward A. Clerke has been named
by board approval to the position of
Principal Professional, Reservoir
Characterization Department/
Exploration, the highest technical
position within Saudi Aramco.
Prior to joining Saudi Aramco, he
held the positions of Head of Petrophysics and
Petrophysical Engineering Advisor for Pennzoil; Senior
Principal Petrophysicist with ARCO in Plano, TX; and
petrophysical engineering and research positions with Shell
Oil Co., USA.
Ed’s innovative “Rosetta Stone” work, which has
applied decoding techniques to unlock important
subsurface reservoir property links for major carbonate
fields for Saudi Aramco, has been published in GeoArabia
and the SPE Journal. These techniques are opening new
avenues for carbonate reservoir characterization and
carbonate reservoir simulation for ultimate oil and gas
recovery.
He has published articles in GeoArabia, SPE Journal,
Log Analyst, SPE Production Engineering, Physical
Review, Physica and the Journal of Physical Chemistry.
Ed received the Best Paper Award at the Middle East GEO
2006 and GEO 2004 for work presented on Arab-D
limestone pore systems and also received the 2006 Best
Paper Award at the SPWLA Carbonate Permeability
Topical Conference. Less recently, he received the 1993 Best
Paper Award from the West Texas Geological Society for
work in Permian Basin carbonates.
In 1982, Ed received his Ph.D. degree in Physics from
the University of Maryland, College Park, MD, under Prof.
Jan Sengers, after physics studies at Johns Hopkins and the
University of Massachusetts, Amherst, as well as stints at
Comsat Labs and Argonne National Labs. He went on to
join Shell’s Bellaire Research Center.
He holds five patents, four in the area of downhole
acoustic imaging technology, and is the initiating coinventor of the joint Saudi Aramco-Schlumberger software
for nuclear magnetic resonance analysis of carbonate pore
systems — CIPHER.
Ed, who has been a member of the Society of Petroleum
Engineers (SPE) since 1982, is also a member of the
American Association of Petroleum Geologists (AAPG),
Society of Petrophysicists and Well Log Analysts (SPWLA),
and the scientific research honor society, Sigma Xi.
Dr. Johannes J. Buiting is a Senior
Geological Consultant with Saudi
Aramco, working in the Reservoir
Characterization Department for the
past 9 years. Prior to this, he spent 18
years with Shell, working in operating
companies in the Netherlands,
Thailand, Brunei, the U.K. and Nigeria. Jan’s experience
includes the fields of reservoir physics, quantitative
interpretation, rock and fluid physics, seismic acquisition,
and processing and inversion.
He received his Ph.D. degree in Physics and
Mathematics from Radboud University, Nijmegen, The
Netherlands.
Jan has authored or coauthored over 250 journal
articles.
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Integration of Static and Dynamic Data
for Enhanced Reservoir Characterization,
Geological Modeling and Well
Performance Studies
Authors: Dr. Shouxiang M. Ma, Dr. Murat M. Zeybek and Dr. Fikri J. Kuchuk
ABSTRACT
A new methodology is presented for reservoir characterization,
geological modeling and well performance prediction by integrating a complete suite of petrophysical and pressure transient test data to build a detailed geological reservoir model
(RM) with anisotropy. Data used include cores, open hole logs,
wireline formation testing (WFT) pretests, vertical interference
tests (VITs), production logs, and downhole pressure buildup
and injection falloff tests. Core data were first integrated with
open hole logs and WFT pretests to build a detailed geological
model. Vertical and horizontal permeabilities derived from the
VITs were then integrated to produce a geological model with
anisotropy. Using this model, a numerical pressure transient
analysis (PTA) for a single well was performed by simultaneously
history matching the packer’s and the probe’s pressures, as well
as pressure derivatives, to identify the presence of tight reservoir
streaks and to quantify reservoir layer permeability ranges.
The model was further refined and validated by comparisons
with dynamic data derived from production logs, and downhole
pressure buildup and injection falloff tests. This validated RM
was used in single well reservoir simulation studies to predict
well performance and infer in situ reservoir scale and reservoir
condition petrophysical properties, such as relative permeability
and capillary pressure.
INTRODUCTION
Most carbonate reservoirs are layered and heterogeneous. The
lithology (lith) and porosity ( ), derived from cores and logs,
of a typical Arab-D carbonate reservoir are shown in Figs. 1a
and 1b, respectively. Characterizing reservoir layering and heterogeneity is essential in reservoir engineering. For example,
when addressing oil recovery by waterflood, the following
equation is often referred to:
E = EAEVEM
(1)
where E is oil recovery efficiency, subscript A is areal sweep
efficiency (the ratio of area swept to total field area), subscript
V is vertical conformance (the ratio of intervals swept to total
pay thickness), and subscript M is the microscopic displacement
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Fig. 1a. Typical Arab-D carbonate reservoir volumetrics (blue is limestone,
green is dolostone, and pink is anhydrite). Fig. 1b. Comparison between log
and core porosities. Fig. 1c. Schematic of a WFT and VIT setup showing a
packer-probe configuration applied to a section having four layers, including a
low permeability streak.
efficiency (defined as the saturation change with respect to
original oil saturation in the swept volume).
Note that even though many factors (including pore structure and wettability) may affect E microscopically, it is the
areal sweep efficiency and vertical conformance that dominate
the efficiency of oil recovery. Consequently, detailed reservoir
characterization is critical for better reservoir management.
Petrophysical reservoir characterization consists of data
acquisition, data processing and data distribution in space, or
modeling. Petrophysical data in reservoir characterization usually include lith, , water saturation (Sw), zone thickness (h)
and permeability (k), with k being the most challenging to
characterize, especially for carbonates due to the heterogeneous
pore structure caused by depositional environments and diagenesis (such as dolomitization, compaction, cementation and/or
fracturing).
The most commonly used techniques for in situ reservoir
permeability characterization are based on pressure transient
analysis (PTA); either wireline formation testing (WFT) with
measurements typically ranging from 10 ft to 50 ft away from
the well, depending on formation properties and duration of
production and buildup periods, or conventional well testing,
with a depth of investigation ranging from hundreds to thousands
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of feet1, 2. It is a common understanding for almost all petrophysical measurements that the greater the depth of the investigation, the poorer the vertical resolution. The WFT has much
better vertical resolution than conventional well tests.
There are basically two modes in WFT for estimating reservoir permeability: a pretest with probes and a vertical interference test (VIT) with a combination of packers and probes, Fig.
1c. A pretest requires a drawdown volume of less than 20 cm3
of fluid, most likely mud filtrate. As a result, mobility estimated from a WFT pretest is a near wellbore mobility indicator; at remaining oil saturation (ROS) if water-based mud were
used across an oil interval. On the other hand, during a VIT,
hundreds of liters of reservoir fluid are pumped out (at a rate
of 1 to 30 barrels per day (BPD) for up to 1 hour), providing a
reservoir permeability estimation up to 50 ft into the reservoir,
which is certainly much more representative of reservoir permeability (at connate Sw if measured across a pay zone). In
addition, unlike other reservoir petrophysical properties mentioned above, permeability is directional. Currently, the only
techniques that are used routinely for directional reservoir permeability characterization are based on PTA, such as a VIT.
Details of a nonlinear regression analysis of VIT PTA data for
determining formation parameters are given by Onur and
Kuchuk (2000)3.
The main objective of this article is to introduce a methodology to integrate static and dynamic petrophysical data to
build a comprehensive reservoir model (RM) for reservoir
characterization, geological modeling and well performance
prediction. Results reported in this article are part of a larger
project, and some of the details of the project have been published previously4, 5.
METHODOLOGY
Petrophysical properties derived from open hole logs and WFT
are calibrated with core analysis data before being distributed
in space to build a geological model. The established model
can be verified from borehole fluid flow profiles measured by a
production log, as shown in Eqn. 2, even though layers with
no flow or a low flow rate due to skin, low permeability or
low pressure may not be detectable by a production log:
(
n
i=1
)
kihi
Core, OH Logs,WFT
(
=
n
i=1
)
kihi
PL
(2)
The cumulative of the borehole flow profiles can be calibrated from the total kavgH determined from a well test:
(
n
i=1
) =(k H)
ki hi
PL
avg
WT
(3)
In Eqns. 2 and 3, H is the total reservoir thickness, h is the
individual layer thickness, n is the total number of reservoir
layers, subscript avg is the average of all layers, and subscript i
is the ith reservoir layer.
Details of the methodology introduced in this study for sin-
Fig. 2. Methodology for reservoir characterization, reservoir modeling and well
performance prediction.
gle well data integration, reservoir characterization, reservoir
modeling and well performance prediction are summarized
below and illustrated in Fig. 2.
1. Data Preparation and Integration:
• Core data are reviewed and quality controlled for
geological features (such as depositional environments
and layering), lith, pore types, , k and grain density.
• Open hole logs are reviewed, quality controlled,
processed and interpreted for lith, , grain density, Sw,
zoning and zone thickness (h).
• WFT pretest data are reviewed, quality controlled and
processed for estimating mobility, then for qualitatively
determining k.
• Together with other geological information, the above
core data, open hole logs and WFT pretests are
integrated for a foot-by-foot formation evaluation and
reservoir characterization.
2. Geological Model:
• A layered, single well geological model is generated
from the above detailed formation evaluation and
reservoir characterization.
• WFT and VIT data are analyzed to quantify vertical and
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horizontal permeabilities (kv and kh) for the layers
selected for the VIT.
• The geological model is updated with kv and kh
determined from analyses of all VITs.
• This layered anisotropic geological model is fine-tuned
by integrating geological features and the range of
permeabilities obtained from performing a single well
numerical PTA, with the pressure and pressure
derivatives as the history matching parameters, for each
VIT.
3. Reservoir Model:
• A RM is established by validating, iteratively, the finetuned geological model with kh from a production log
and the total KavgH from downhole pressure buildup
and falloff tests, as shown in Eqns. 2 and 3.
4. Use of the RM:
• By history matching downhole pressure and flow rate,
the RM can be used in a single well reservoir simulation
for well performance prediction or in any other
reservoir characterization and management studies4, 5.
TEST OF THE METHODOLOGY IN A STUDY WELL
The above methodology was developed in a joint research
project between Saudi Aramco and Schlumberger, and some
of the results of the project have been published4, 5. In this
article, the focus will be on the methodology of integrating
static and dynamic data for reservoir characterization and
modeling. In the process, it will be demonstrated that the VIT
is an extremely powerful tool for characterizing reservoir
heterogeneity1, 6-8.
Data Acquisition
As previously reported4, 5, a research well, Well-A, was drilled
in 2001 across the Arab-D carbonate reservoir, and a complete
set of petrophysical data was acquired in the following order:
1. Cores, open hole logs and WFT:
• Conventional cores were taken from the top 250 ft of
the target reservoir. Core description, petrographics, and
routine and special core analyses were performed on
selected core samples.
• Open hole logs acquired included caliper, spectral
gamma ray, bulk density, thermal neutron porosity,
sonic, array induction resistivity, micro resistivity,
resistivity imaging, mineralogy and nuclear magnetic
resonance tests.
• A total of 25 WFT pretests and eight VITs were
conducted.
2. Baseline production log. Following completion, the well
was allowed to produce oil for one day to clean out mud
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invasion, and then the baseline flow profile was established
from the production log.
3. Baseline buildup tests for KavgH at connate water saturation (Swc):
• The well was then shut-in to perform a buildup test for
total KavgH (at Swc) by using the downhole permanent
pressure gauge located just above the top of the tested
zone.
• After producing the well for a while, another pressure
buildup test was performed immediately before water
injection to confirm the determined KavgH (at Swc).
4. Water injection tests:
• A stepwise rate change was applied. Each injection rate
usually lasted 3 to 5 hours, depending on the time
required for the electrode resistivity array measurement4
and production log measurements.
• The initial injection rate was 1,000 BPD. With an
incremental of about 1,000 BPD, the final rate reached
8,200 BPD at the end of the eighth test.
• A production log was run to obtain the injection profile
during each test.
5. Falloff test for KavgH at ROS.
• The well was then shut-in for a falloff test to determine
the total KavgH at ROS and skin.
6. Final buildup test for KavgH at reduced Sw:
• All of the injected water and some oil were produced
back to the surface with a nitrogen lift for 14 days.
• During this water and oil production period, a
production log was run frequently to monitor fluids
produced.
• After the well stopped producing water, the well was
shut-in for a final pressure buildup test to estimate
KavgH at a reduced Sw close to, but usually larger than,
the original Swc.
Data Processing and Interpetation
Core Data. Core description and petrographic analysis were
conducted to extract information on reservoir depositional environment and rock typing, and to identify reservoir layers; an
example of this analysis is shown in Fig. 3. Conventional core
analysis under stress, Figs. 3a and 3b, on selected core samples
was performed to provide data for log calibration and reservoir layering(1). On a subset of cores, adjacent twin plugs were
taken, one horizontally and another vertically, for kh and kv
(1) In using core data to calibrate logs and/or well tests, it is noted that core data
may not be representative in very high and very low permeability rocks9. For rocks
with very high permeabilities (such as measures in Darcies), cores may not be available or pluggable due to their weak mechanical integrity. On the other hand, conventional laboratory measurements on very low permeability rocks (such as
measures in less than milli-Darcies) have large uncertainties.
Fig. 3. Example of core analysis data and associated core descriptions and
petrographics.
measurements, Fig. 3b. From Fig. 3, the following are observed:
1. Correlations between permeability and are strongly de
pendent on rock type.
2. The difference between kh and kv is not obvious at the core
plug scale. This may be attributed to the following:
• Laboratory permeability measurements have relative
large uncertainties, so the difference between kh and kv
is probably within permeability measurement
uncertainties.
• To ensure a plug’s mechanical integrity, samples are
typically taken in more homogeneous sections, where
rock anisotropy is less.
• Even though small-scale rock anisotropy can be
observed, for example, in thin sections, it is probably
true that the larger the scale, the more obvious the rock
anisotropy.
Open Hole Logs. As previously mentioned, a complete suite of
open hole logs was run. These logs were quality controlled,
processed and interpreted for lith, and Sw. Correlations were
also used to qualitatively predict reservoir permeability. Use of
the processed logs and core data in geological modeling has
been previously described5.
WFT Pretests and VITs. As summarized in Fig. 2 describing a
geological model built with geological and petrophysical data,
25 pretests were performed using probe 1, Fig. 1c, for formation
pressure profiling. Eight VITs were conducted with a configuration of a dual packer and two observation probes, probes 1
and 2, as shown in Fig. 1c; 13 additional pretests were also
performed using both probes during the VITs. A pump-out
module was used for fluid withdrawal to create pressure transients in the formation, which were monitored by crystal
quartz pressure gauges and strain gauges at the dual packer and
observation probes. Figure 4 shows the acquired downhole data,
including reservoir pressure (with an oil gradient of 0.32 psi/ft)
from the probes, from the packer and during the interference
Fig. 4. Composite display of open hole logs, reservoir layering, WFT pressures,
mobilities and VIT positions.
test (track 1); pretest drawdown mobilities (track 2); image log
and the positions of the VITs (track 3); reservoir porosity
(track 4); and formation resistivity (track 5). Reservoir porosity and formation resistivity data provide quantitative information for reservoir layering, while the image log is used to check
the reservoir layering qualitatively.
Pretest Applications. As shown in Fig. 4, pretest data can be
processed for formation pressure and fluid mobilities. Formation
pressure derived from the probe pretest is as accurate as that
obtained from a packer test or a well test (track 1 of Fig. 4);
therefore, it is routinely used for reservoir fluid typing, fluid
contacts identification and free water level determination.
On the other hand, the probe pretest drawdown mobility is
rather qualitative, due to its small volume drawdown (typically
5 cm3 to 20 cm3). It has a shallow depth of investigation, and
it is affected by formation damage in the invaded zone and by
near wellbore, small scale heterogeneity. Because of the small
volume drawdown, the mobility determined typically does not
include anisotropy. Consequently, pretest drawdown mobility
can only be qualitatively used for reservoir rock and fluid
characterization.
VIT Applications. As described in Fig. 2, VIT data can be
processed for reservoir rock anisotropy assessment. This VIT
data processing workflow is expanded in Fig. 5. To process the
VIT data, a robust geological model is essential to match the
packer’s and probe’s pressures and pressure derivatives with
predicted kv and kh. This matching is not only for one VIT, but
for all VITs, so an iterative process is necessary.
In a heterogeneous reservoir, pressure changes at the observation probes, especially the one with the farthest spacing, may
be very small. For a VIT to be successful in this situation, very
high precision pressure gauges are required, Fig. 6. Besides kv
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Layer
Fig. 5. Workflow for VIT data processing in a layered reservoir.
Fig. 6. Example of precise probe pressure measurement during a VIT.
H
Poro
kh
kv
kh/kv
1
8
0.16
7.2
4.03
1.8
2
2
0.05
3.2
0.96
3.3
3
45
0.25
940
432.4
2.2
4
2
0.12
2
0.18
11.1
5
4
0.25
736
58.88
12.5
6
1
0.2
0.15
0.02
7.5
7
7
0.25
497
49.7
10
8
2
0.24
2.9
3.19
0.9
9
7
0.24
160
16
10
10
1
0.1
3
0.06
50
11
6
0.23
463
96.45
4.8
12
1
0.15
3.5
0.07
50
13
13
0.2
980
490
2
14
1.5
0.1
16.2
15.39
1.1
15
14.5
0.25
164
22.08
7.4
16
5
0.12
4.5
9
0.5
17
11
0.17
55
11
5
18
1
0.13
8
0.06
133.3
19
6
0.23
139
34.75
4
20
3
0.1
5
0.55
9.1
21
15
0.25
716
27.72
25.8
22
5
0.1
3
2.5
1.2
23
11
0.12
114
2.05
55.6
24
11
0.1
48
7.97
6
25
10
0.1
8
5.28
1.5
26
2
0.05
1
0.1
10
27
6
0.09
3
0.3
10
28
7
0.07
2
0.2
10
29
2
0.12
14
2.8
5
30
27
0.05
2
0.2
10
31
10
0.07
1
0.1
10
32
1
0.03
1
0.1
10
33
8
0.07
58
4.64
12.5
34
60
0.03
0.5
0.15
3.3
Table 1. Final layered reservoir model with anisotropy
F
Fig. 7. Use of VITs in reservoir fluid flow regime identification and reservoir
heterogeneity characterization.
and kh determination as described in Fig. 5, VITs can also be
useful in reservoir fluid flow regime identification and detailed
reservoir heterogeneity characterization, as demonstrated in
Fig. 7, by examining the pressure and its derivative vs. buildup
time. From Figs. 6 and 7, the following can be summarized:
• Probe pressure changes of 0.1 psi are clearly observed, repeatedly, with the high resolution crystal quartz gauges.
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
• Measured packer and probe pressures are matched or
reproduced satisfactorily with the geological model.
• Fluid flow regimes are identified from features of
buildup pressure derivatives. The identified flow regime
is consistent with the geological model.
Final RM
By integrating geological information with data derived from
core description and core analysis, open hole logs, WFT
CONCLUSIONS
From this article, the following are concluded:
• At core plug scale, permeability anisotropy may not be
observable.
• A VIT with advanced WFT is a powerful tool for
reservoir heterogeneity characterization.
• To build a robust geological model, integration of all
geological and petrophysical data is critical.
Fig. 8. Reservoir model validation using kh from production logs (a) and
KavgH from downhole pressure and pressure derivatives (b).
• To test the internal consistency of a built RM, numerical
history matching of measured properties, such as
pressure and its derivatives, is a proved best practice.
• Total KavgH from a well test and ȃkh from a production
log flow profile are useful in validating RMs.
• A methodology is introduced that integrates static
and dynamic petrophysical data for reservoir
characterization, geological modeling and well
performance studies.
ACKNOWLEDGMENTS
Fig. 9. History matching of downhole pressure and flow rate during injection
and falloff4.
pretests and VITs, the RM in this study well was established,
following the methodology of Fig. 2, as shown in Table 1. This
model is considered accurate not only because it integrates all
relevant data, but more importantly because it is internally
consistent with VIT pressure and pressure derivatives.
The established RM, Table 1, is further validated in terms of
its production behaviors by comparing its data with the fluid
flow profile derived from production logs and the total KavgH
derived from numerical analyses of well test pressure as well as
pressure derivative, Fig. 8. Results show that the model
matches the well dynamic behavior very well, Fig. 8.
Application of the Validated Geological Model
The RM, Table 1, can be used in well performance studies, as
shown in Fig. 9, by matching and predicting the bottom-hole
pressure and flow rate. It has also been used in this study well
for identifying and characterizing reservoir heterogeneity, inverting reservoir scale and reservoir condition relative permeability and capillary pressure, assessing oil recovery by waterflooding, and monitoring water movement in situ in connection
with measurements of a specially designed electrode resistivity
array and permanent downhole pressure gauges4, 5.
The authors would like to thank the management of Saudi
Aramco and Schlumberger for their permission to publish this
article.
This article was prepared for presentation at the SPE
Annual Technical Conference and Exhibition, New Orleans,
LA, September 30 - October 2, 2013.
REFERENCES
1. Ayan, C., Hafez, H., Hurst, S., Kuchuk, F.J., O’Callaghan,
A., Peffer, J., et al.: “Characterizing Permeability with
Formation Testers,” Oilfield Review, Vol. 13, No. 3,
October 2001, pp. 2-23.
2. Kuchuk, F.J.: “Radius of Investigation for Reserve
Estimation from Pressure Transient Well Tests,” SPE paper
120515, presented at the SPE Middle East Oil and Gas
Show and Conference, Manama, Bahrain, March 15-18,
2009.
3. Onur, M. and Kuchuk, F.J.: “Nonlinear Regression
Analysis of Well Test Pressure Data with Uncertain
Variance,” SPE paper 62918, presented at the SPE Annual
Technical Conference and Exhibition, Dallas, Texas,
October 1-4, 2000.
4. Kuchuk, F.J., Zhan, L., Ma, S.M., Al-Shahri, A.M.,
Ramakrishnan, T.S., Altundas, B., et al.: “Determination of
In-Situ Two-Phase Flow Properties through Downhole
Fluid Movement Monitoring,” SPE paper 116068,
presented at the SPE Annual Technical Conference and
Exhibition, Denver, Colorado, September 21-24, 2008.
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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5. Zhan, L., Kuchuk, F.J., Al-Shahri, A.S., Ma, S.M.,
Ramakrishnan, T.S., Altundas, B., et al.: “Characterization
of Reservoir Heterogeneity through Fluid Movement
Monitoring with Deep Electromagnetic and Pressure
Measurements,” SPE Reservoir Evaluation & Engineering,
Vol. 13, No. 3, June 2010, pp. 509-522.
6. Kuchuk, F.J.: “Pressure Behavior of the MDT Packer
Module and DST in Crossflow-Multilayer Reservoirs,”
Journal of Petroleum Science and Engineering, Vol. 11,
No. 2, June 1994, pp. 123-135.
7. Kuchuk, F.J., Halford, F., Hafez, H. and Zeybek, M.: “The
Use of Vertical Interference Testing to Improve Reservoir
Characterization,” SPE paper 87236, presented at the Abu
Dhabi International Petroleum Conference and Exhibition,
Abu Dhabi, U.A.E., October 13-15, 2000.
8. Zeybek, M., Kuchuk, F.J. and Hafez, H.: “Fault and
Fracture Characterization Using 3D Interval Pressure
Transient Tests,” SPE paper 78506, presented at the Abu
Dhabi International Petroleum Conference and Exhibition,
Abu Dhabi, U.A.E., October 13-16, 2002.
9. Ma, S.M., Belowi, A., Pairoys, F. and Zoukani, A.:
“Quality Assurance of Carbonate Rock Special Core
Analysis — Lesson Learnt from a Multi-Year Research
Project,” IPTC paper 16768, presented at the 6th
International Petroleum Technology Conference, Beijing,
China, March 26-28, 2013.
BIOGRAPHIES
Dr. Shouxiang M. Ma is a Senior
Petrophysical Consultant in the
Reservoir Description Division and
serves in the Petroleum Engineering
Technologist Development Program
actively as a mentor and a member of
its Technical Review Committee. He
member of the Upstream Professional
was a founding mem
Development Center as the petrophysics job family
Professional Development Advisor from 2009 to 2012.
Before joining Saudi Aramco in 2000, he worked as a
Lecturer at Changjiang University, Jingzhou City, China,
and as a Lab Petrophysicist at the New Mexico Petroleum
Recovery Research Center, the Wyoming Western Research
Institute and Exxon’s Production Research Company.
Mark received his B.S. degree from China University of
Petroleum, Beijing, China, and his M.S. and Ph.D. degrees
from the New Mexico Institute of Mining and Technology,
Socorro, NM, all in Petroleum Engineering.
He is a member of the Society of Core Analysts and the
Society of Petroleum Engineers (SPE), and served on the
SPE’s Formation Evaluation Award Committee (as
Chairman in 2012) and the AIME/SPE Robert Earll
McConnell Award Committee.
Mark has more than 60 publications and several patents
in petrophysics. He was awarded the 2003 Department
Individual Achievement Award and 2011 SPE Saudi Arabia
Section Active Technical Involvement Award, and is a
technical journal reviewer for SPE Reservoir Evaluation
and Engineering (SPERE&E), Journal of Canadian
Petroleum Technology (JCPT), Journal of Petroleum
Science & Engineering (JPS&E) and the Arabian Journal
for Science and Engineering.
Dr. Murat M. Zeybek is a
Schlumberger Reservoir Engineering
Advisor and Reservoir and Production
Domain Champion for the Middle
East Region. He works on analysis
interpretation of wireline formation
testers, pressure transient analysis,
numerical
i l modeling
d li of fluid flow, water control,
production logging and reservoir monitoring.
He is a technical review committee member for the
Society of Petroleum Engineers (SPE) journal Reservoir
Evaluation and Engineering. Murat also served as a
committee member for the SPE Annual Technical
Conference and Exhibition, 1999-2001. He has been a
discussion leader and a committee member in a number of
SPE Applied Technology Workshops (ATWs), including a
technical committee member for the SPE Saudi Technical
Symposium, and he is a global mentor in Schlumberger.
Murat received his B.S. degree in Petroleum Engineering
from the Technical University of Istanbul, Istanbul, Turkey.
He received his M.S. degree in 1985 and his Ph.D. degree
in 1991, both from the University of Southern California,
Los Angeles, CA, also in Petroleum Engineering.
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
He has published more than 50 papers on analysis/
interpretation of wireline formation testers, pressure
transient analysis, numerical modeling of fluid flow, fluid
flow porous media, water control, production logging and
reservoir monitoring.
Dr. Fikri J. Kuchuk, a Schlumberger
Fellow, is currently Chief Reservoir
Engineer for Schlumberger Testing
Services. He was a consulting
professor at the Petroleum Engineering
Department of Stanford University
from 1988 to 1994, teaching
Advanced
Well
Testing.
Before joining Schlumberger in
Ad
dW
ll T
ti
1982, Fikri worked on reservoir performance and
management for BP/Sohio Petroleum Company.
He is a Distinguished and Honorary Member of the
Society of Petroleum Engineers (SPE), the Society for
Industrial and Applied Mathematics, the Russian Academy
of Natural Sciences and the American National Academy
of Engineering. Fikri received the SPE 1994 Reservoir
Engineering Award, the SPE 2000 Formation Evaluation
Award and the SPE 2001 Regional Service Award; the
Henri G. Doll Award in 1997 and 1999; and the Nobel
Laureate Physicist Kapitsa Gold Medal. He has been very
active in professional societies, serving as SPE International
Director-at-Large and SPE Northern Emirates Section
Director, and he is a member of the SPE Forum Series
Implementation Committee, the Middle East Oil Show &
Conference Executive and Program Committees, and many
SPE award, editorial, membership and technical
committees.
Fikri has published and presented more than 150 papers
on fluid flow in porous media, formation evaluation,
pressure transient well testing, production logging, wireline
formation testers, horizontal and multilateral well placement and performance, permanent reservoir monitoring,
water conformance and control, and reservoir engineering
and management.
He received his B.S. and M.S. degrees from the
Technical University of Istanbul, Istanbul, Turkey, and his
M.S. and Ph.D. degrees from Stanford University, Palo
Alto, CA, all in Petroleum Engineering.
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Solid Particle Erosion in a Partially Closed
Ball Control Valve
Authors: Dr. Ehab Elsaadawy, Dr. Marcello Papini and Dr. Abdelmounam M. Al-Sherik
ABSTRACT
Solid particulates carried with the flow in most hydrocarbon
pipeline systems can be potentially erosive to many engineering
materials used for pipeline components, such as pipeline bends
and control valves. Modeling particle-laden turbulent gas flow
is very challenging due to many inherent difficulties. First, the
lack of experimental data for the erosion resistance of engineering materials for some solid particles, such as the black
powder found in many sales gas pipelines, precludes implementing any of the erosion models for that particular particulate.
Second, the two-phase problem of solid/gas flow is not trivial
because it involves many competing phenomena, such as turbulent gas flow, erosion, particle-gas interaction, particle-particle
interaction and particle-wall interaction. In this article, a computational fluid dynamics (CFD) study of the erosion of a
pipeline ball control valve due to the impingement of solid
particles (black powder) is presented. A tailored experimental
program to measure the erosion resistance of different materials
under the impingement of black powder particulates was performed (the authors claim to provide the first literature on this
black powder erosion issue). From the results of those experiments, the coefficients of an erosion model were computed for
Stellite 12, and A-505 and A-105 carbon steel alloys. It was
shown that using Stellite 12 instead of A-105 and A-505 carbon
steels for the body and ball of the valve, respectively, could
considerably increase the operational life of the valve as a result
of the reduction of the erosion rate. Also, the work showed
that CFD is becoming a very useful tool for enhancing the
performance of equipment in the oil and gas industry, as it has
in many other industries.
INTRODUCTION
Erosion, due to the impact of solid particles, such as sand and
black powder, is a subject of concern in the oil and gas industry as it causes considerable damage to the critical components
of transport and processing equipment, such as valves and
chokes. Resolution of the erosion problem is particularly important for gas choke valves because gas when it is initially
compressed — typically to 200 bars to 500 bars — may reach
sonic velocities in various parts of the valve, dependent on the
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valve design. The fluid accelerates carried solid particles,
which hit the walls of the valve as well as the pipes downstream. Increasing the longevity of such components would
lead to significant savings. This can be achieved in two ways:
through the selection of erosion-resistant materials for components or through design optimization (flow path modification).
In multistage pressure reduction control valves, 3D flow
channels in the body of the valve trim are used to reduce the
flow pressure and provide erosion resistance. Atkinson et al.,
(2007)1, built and calibrated a testing facility that operated at
a high pressure of 40 bars of nitrogen and used silica sand as
an erodent. This test facility was used to investigate the erosion
of the complicated 3D channel configurations designed for erosion-resistant valves employed under natural gas and oil severe
service conditions. The results of this experimental work were
used to validate a computational fluid dynamic (CFD) model,
developed by the CFD code FLUENT 6.2, for predicting erosion in those channels. The realizable k-ε model with enhanced
wall treatment was then used to model the turbulent flow in
the channels. The particle-wall interaction was accounted for
by utilizing the stochastic discrete random walk model available
in FLUENT 6. The mass average particle size of the silica sand
erodent was 50 µm with a broad distribution, which was taken
into account in the computations. Channels were made from
acrylic1. The CFD model was able to reproduce the complicated
erosion patterns and actual weight losses in the early stages of
erosion.
Wallace et al. (2004)2, investigated the capabilities of the
then available CFD-based erosion models to predict erosion in
valve components for aqueous slurry flows. Two geometries
were studied both experimentally and computationally; the
first was a simple geometry with features similar to those of
real valves, and the second was a complex geometry like that
of a choke valve. Again, the commercial CFD code FLUENT
was used to perform the computations. For turbulence closure,
standard k-ε and re-normalization group k-ε turbulence models were used. Also, one-way coupling with the discrete random walk model was used to account for the fluid-particle
interaction. A series of tests on a range of material specimens
was carried out using liquid jet and air jet equipment. For the
liquid jet tests, samples were eroded using sand with an average size of 235 µm, jet velocities in the range 15 m/s to 24 m/s
and specimen angles between 30° and 90°. In the case of air-sand
jet tests, greater impact velocities, up to 268 m/s, were allowed;
however, the sand size was smaller, with an average size of 194
µm. The results of this study indicate that the modeling of the
flow field and of the particle trajectories was adequate; however, the model’s predictions of the erosion rate were inadequate.
The authors attributed this to the model’s neglect of the geometry changes that occur due to erosion and an inadequate
accounting for material erosion relationships.
Haugen et al. (1995)3, studied the sand erosion of choke
valves from both the material selection point of view and the
perspective of geometry optimization. Although a detailed
description of the experimental work to determine the erosion
resistance of 28 different materials was presented3, enough
details of the computational work was not presented. The 28
materials tested comprised six standard materials, 10 surface
coatings, three solid tungsten carbide (WC) materials and nine
ceramics. Of these materials, the most erosion resistant were
found to be the three solid WC materials and two of the ceramics, silicon nitride (Si3N4) and boron carbide (B4C). Only
one coating, a Degun WC layer, was found to give significantly
improved erosion resistance characteristics as compared with
the reference material, C-steel.
Not only does the solid particle erosion of control valves
determine the lifetime of the valve, but the erosion due to liquid droplets (flashing) can also in some cases determine the
lifetime of such valves. Nokleberg and Sontvedt (1995)4 studied
predictions of erosion depth in pressure reduction valves
(chokes) caused by both types of erosion: solids and large
amounts of droplets. They transformed the solid and droplet
erosion data for WC with 6% copper and 6% nickel and for
polycrystalline diamond (PCD) into correlations that were then
coupled with a CFD-based erosion model built into FLUENT
4.1 to determine the erosion depth due to solids and droplets.
Nokleberg and Sontvedt concluded that the solution to the
solids erosion problem in chokes is to reduce the impact angle
of the solids and/or apply PCD as the target material. As an
extension of this previous work5, a computational model was
developed using FLUENT 4.x to estimate the erosion and lifetime of chokes. The model was validated and tested utilizing
two types of chokes, needle and seat chokes and external
sleeve chokes. The model and the experimental data showed
that the external sleeve type of choke experienced more erosion attack under test conditions.
Another study of the solid particle erosion of oil field control valves aimed at design optimization and material selection
based on the CFD erosion model predictions6 expanded the
capabilities of the commercial CFD software used in the simulations by introducing Fortran subroutines into the software to
allow computing of the solid particle erosion. The valve studied
was a 3” (75 mm) control choke that was simplified through
the application of a symmetry plane. The choke openings were
25%, inducing a pressure drop of 68 bars when the suspension
fluid was gas.
Sand concentrations of 1% by weight were utilized, with the
particle distribution at the inlet assumed to be uniform. The
size distribution was 50 µm to 300 µm, divided into five
groups at 50 µm intervals. The particles were classified as subangular, being deformed from the sphere by 20%. The restitution
coefficients were modified to account for both impact angle
and material type. Also, the model allowed differing materials
to be specified within the computational domain. The study
showed that erosion is primarily velocity driven and that design optimization to reduce peak velocities while retaining the
overall pressure drop characteristics is desirable. Also, it was
shown that good correlation between experimental and predicted data could be achieved by modifying the erosion model
used within the computational CFD software.
The concern and attention directed towards the solid particle
erosion phenomenon is not confined to the oil and gas industry.
Many other industries suffer from the same problem. The differences are in the type of carrier fluid, and the particle type and size.
Solid particle erosion of steam turbine components, such as
nozzles, blades, radial spill-strips and control valves, has been
an area of concern to utilities for several years. It is generally
agreed that this kind of erosion damage is caused by oxide
scale exfoliation from boiler tubes and/or steam leads, which
becomes entrained in the steam flow to the turbine, causing
erosion of the steam path and turbine components, especially
control valves (main stop valves). Design modifications were
attempted using 2D CFD modeling7 and 3D CFD modeling8.
In both studies, the CFD commercial software FLUENT was
used to predict erosion and verify the effectiveness of the design modifications. The results from both studies showed that
an effective reduction in erosion rate, and therefore an increase
in the lifetime of the valve, can be achieved by manipulating
the flow path and therefore the particle trajectories, and that
CFD can actually be used in a predictive manner to optimize
the design and increase the lifetime of the component.
The control valves discussed so far have been of the choke
type. To the knowledge of the authors, erosion in the globe
type of valves has rarely been investigated. In the few studies
that do exist, the erosion due to solid particle impact was not
predicted, but instead the flow field and its turbulence were the
focus of study. In one of these rare studies, a numerical study
was performed9 by applying the commercial CFD code,
FLUENT, to obtain solutions of the 2D turbulent flow field
through a globe valve for its different openings in a gaseous
oxygen systems environment. The influence of pressure, flow
rate and the openings of the valve on the rise in temperature
and the eddy dissipation rate were determined for a compressible
flow range. The simulation for turbulence was done using k-ε
and k-ω turbulence models, and the results were compared. A
summary of available literature addressing the CFD modeling
of solid particle erosion is presented in Table 1.
In the current study, particle-laden turbulent gas flow in a
typical ball control valve for a sales gas pipeline was studied,
and the erosion rates were predicted, using CFD models. The
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Reference
2
Geometry
Code
Choke valve FLUENT
Valve (3D
channels)
7
3
FLUENT
Choke valve
Solid/Gas
Turbulence
Erosion Model
Sand
(235 µm)/
Air, Water
Std k-ε and/or
RNG - k-ε, oneway coupling,
discrete random
walk model
, liquid
jets: 15 m/s to 24 m/s,
sand-air jet, the range
extended to 268 m/s
(but with sand size of
194 µm)
Silica sand
(100 µm)/N2
Realizable k-ε,
one-way coupling, discrete
random walk
model
Valve material
is low alloy steel
Finnie erosion model for
with a layer of
ductile materials.
Stellite on the
working surface
Angular sand
(200 µm to
250 µm)
Standard k-ε
turbulence
model
, jet
velocity: 18 m/s to 20
m/s, 40 m/s to 45 m/s
and 200 m/s to- 225 m/s
E = M p .K .F (a ). V pn
8
Stop valve
3D flow
channels
1
Notes
WC DC(Z)05, AISI
4130 and ASTM
17.4 PH 105K
Empirical coefficients have been
developed for erosion rate modeling
purposes
FLUENT
Oxide scale (100
µm)
Valve was made
RNG - k-ε, oneof low alloy steel
way coupling,
Finnie erosion model for
with a layer of
discrete random ductile materials
Stellite on the
walk model
working surface
FLUENT
Silica sand (50
µm, 75 m/s to
200 m/s)/
Nitrogen at 40
bars
Realizable k-ε
with enhanced
wall treatment
E = M p .K .F (a ). V pn
Considered broad
particle distribution
Flow dynamics (No erosion prediction)
2D geometry
5
Choke
valves
FLUENT
Sand (50 µm)/
Gas
Stochastic tracking to account
for turbulence
effect on particles
9
Globe valve
FLUENT
O2 (gas) at
250 bars,
7 kg/s
k-ε and k-ω turbulence models
J=sand mass flux,
Considered broad
particle distribution
Table 1. Summary of the previous work on CFD modeling of solid particle erosion
T
gas used was the typical sales natural gas, while the solid particles were iron oxide (magnetite) spheres having a density of
5,150 kg/m3. Particles having a size variation between 2 m
and 20 m were simultaneously injected into the valve inlet at
10 m/s. The particles in five different sizes were carried by a 10
m/s inlet gas flow having a density of 61.8 kg/m3 and a viscosity of 1.33x10-5 Pa.s.
Simulations for two different sets of valve materials were
performed. In the first set, the valve body was made from A105 carbon steel and the ball was made from A-515 carbon
steel. The densities of both of these materials were considered
to be 7,850 kg/m3. In the second simulation, both the valve
body and the ball were made from Stellite 12, having a density
of 8,525 kg/m3. The erosion characteristics of these materials
were based on measurements made for 6.9 mm magnetite particles traveling at 90 m/s.
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
MATHEMATICAL MODEL
The commercial CFD software FLUENT was used to develop
and solve the mathematical model required for the prediction
of the erosion rates. The particle volumetric loading ratio was
very small, specifically 3.2x10-7. Therefore, the flow was considered a diluted gas-solid two-phase flow, and the dispersed
phase model of FLUENT was utilized. The gas, or the continuous phase, was modeled using the Eulerian approach, while
the dispersed phase, or the particles, was modeled using the
Lagrangian approach. The Lagrangian approach is based on
the calculation of the trajectories of several individual solid
particles through the flow field, after which the motion of the
tracked particles is used, along with an erosion model equation, to describe the average behavior of the erosion rate.
The governing equations of the continuous phase were the
incompressible continuity and momentum equations (NavierStokes equations)10:
(1)
(2)
To resolve the flow turbulence, the standard k-ɛ turbulence
model with enhanced wall functions was used. The equations
of turbulent kinetic energy, k, and turbulent dissipation, ɛ, are
as follows:
(3)
(4)
,
the Reynolds stress
, the turbulent viscosity
and
.
The standard values of the (empirical) constants in the k-ε
model are: cµ = 0.09, σk = 1.0 , σε = 1.30, cε1 = 1.44, and
cε 2 = 1.92.
While setting up the Lagrangian tracking and erosion
model, the following assumptions were made. Only the influence of turbulent fluid fluctuations on particle motion was
considered, using the stochastic tracking discrete random walk
model. The particle-particle interactions were neglected, and
any change in the flow turbulence caused by the particles was
not accounted for, i.e., one-way coupling was used. Non-reacting and non-fragmenting particles were considered. The geometry
alteration caused by the removal of wall material due to the
solid particles erosion was neglected; this means that the computational model geometry during the simulation was invariable.
To obtain a reasonable statistical distribution and to reduce
scatter in erosion predictions, a large number of particles are
normally required to perform the particle tracking. Each particle
is tracked through the flow domain separately, and the particle-wall interaction information is then recorded and used to
calculate the erosion. The particle trajectory is determined by
integrating the force balance on the particle. This force balance
equates the particle inertia with the forces acting on the particle,
as per Newton’s Second Law. This equation can be written as:
where
tensor
(5)
where mp is the particle mass, vp is the particle velocity vector,
and F is an external force acting on the particle. The forces
acting on a particle can be the drag force, the buoyancy (gravitational settling) force, the pressure gradient force, the added
mass force, Brownian diffusion (motion), the Saffman lift
force, the Basset force and the rotating reference frame force.
For small particles with a density ratio, țp /ț, much greater
than one, only the drag force and the gravitational settling
force will impact the trajectory of the particle; the other forces
will be negligibly small. Along a particle trajectory, the equation of motion, to be integrated, can be reduced to the following form:
(6)
Fig. 1. Measured erosion rate for 6.9 micron magnetite powder at 90 m/s.
The drag force per unit mass can be expressed as
where Rep is the particle Reynolds number,
Rep = țdp v-vp /µ , and CD is the drag coefficient. Although
Eqn. 6 is linear, the fluid velocity along the particle trajectory
must be known to solve it. As the velocity depends on the particle path itself, the general solution in even a simple turbulent
flow is not possible.
During the particle trajectory calculation, the particle-wall
interaction information, such as the impact speed, the impact
angle and the impact location, as well as the impact intensity,
is stored. This information is then applied to the appropriate
erosion equation(s) to compute the erosion. The removal of
wall material due to erosion (the erosion rate) is calculated
using the following equation10:
(7)
where Rerasion is the erosion rate given in units of the mass of
.
the target material removed per unit area per unit time, mp is
the particles’ mass flow rates, and Aface is the area of the cell
face at the wall. The functions C(d0) and g(a) must be specified
in consistent units to build a dimensionless group with the relative particle velocity and its exponent. Equation 7 can be rearranged in a dimensionless form as:
(8)
where E is the dimensionless erosion rate, defined as the target
material (mt) removed per unit of incoming particle mass (mp).
The function g(a) is an empirical polynomial function that describes the dependence of the erosion rate on the particle impact
angle. The values of C, b and g(a) were obtained by fitting the
experimentally obtained erosion measurements for the materials
selected for the current study, Fig. 1. Akbarzadeh et al. (2012)11,
provides details of the experimental programs and the results.
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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73
Fig. 2. Geometry of the ball valve, body (left) and ball (right).
Fig. 5. Top view of CFD predicted erosion rate (kg/m2.s) for A-515 carbon steel
valve ball. Flow direction is from bottom to top.
Fig. 3. Schematic of a cut-through valve (ball rotated 45°) and body valve.
Fig. 6. Top view of CFD predicted erosion rate (kg/m2.s) for A-105 carbon steel
valve body. Flow direction is from bottom to top.
Fig. 4. CFD mesh of the flow domain used in the simulations.
RESULTS AND DISCUSSION
In the current study, five simultaneous particle injections,
74
FALL 2013
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
representing actual field conditions, were released from the
pipeline inlet at a uniform velocity equal to that of the gas and
steadily tracked.
The geometry of the control ball valve was modeled, Fig. 2.
A cut-through schematic is shown in Fig. 3 with the ball rotated 45°. Because of the size of the geometry (a 1.5 m long
valve with inlet and outlet diameters of 60 cm) and the need to
also model a thin boundary layer as the flow Reynolds number
is high, a mesh with about 200,000 nodes was used, Fig. 4,
which allowed for the convergence of the velocity and continuity residuals to an acceptable value of 0.0015, and for the turbulent convergence to be less than 1x10-6.
For the first simulation, where the valve body and ball materials were A-105 carbon steel and A-515 carbon steel, respectively, Fig. 5 and Fig. 6 show contour plots of the erosion rates
on the valve’s ball and body. The maximum erosion rates were
approximately 8x10-6 kg/m2.s and 5x10-6 kg/m2.s in the valve
ball and body, respectively. The critical areas were on the inside wall of the ball directly downstream of the inlet, and on
the wall just before the outlet on the body.
In the second simulation, where both valve body and ball
were assumed made of Stellite 12, the contour plots of the erosion rates on the valve’s ball and body, Fig. 7 and Fig. 8, show
that the maximum erosion rates for the Stellite 12 were approximately 7x10-7 kg/m2.s in the valve ball and 1x10-7
kg/m2.s in the valve body. These are approximately an order of
Erosion Rate
Valve Part/Material
kg/m2.s
mm/year
Body/A-105
5 x 10-6
20.0
Ball/A-515
8 x 10-6
32.0
Body/Stellite 12
1 x 10-7
0.4
Ball/Stellite 12
7 x 10-7
2.6
Table 2. Maximum erosion rates of the ball control valve
magnitude lower than those of the carbon steels that were used
in the first simulation. A summary of the predicted maximum
erosion rates inside the valve for the two cases can be found in
Table 2.
This demonstrates that major savings in control valve life
can be achieved by a judicious materials selection. The critical
areas for erosion remained largely the same in both simulations, although there were some small variations in the locations
of the maximum rates, shifting slightly upstream or downstream. This was likely due to the difference in the angular
dependence of the maximum erosion rate for the carbon steels
when compared to the Stellite.
CONCLUSIONS
Fig. 7. Top view of CFD predicted erosion rate (kg/m2.s) for Stellite 12 steel valve
ball. Flow direction is from bottom to top.
A CFD study of black powder erosion of a pipeline ball control valve was performed. The erosion rate spatial distributions
showed that the critical areas, where the maximum erosion
rate takes place, were on the inside wall of the ball directly
downstream of the inlet, and on the wall just before the outlet
on the body (this while the valve was partially closed at 45°).
It was shown that using Stellite 12 instead of A-105 carbon
steel and A-505 carbon steels for both the body and ball of
the valve could considerably reduce the erosion rate of the
valve.
ACKNOWLEDGMENTS
The authors would like to thank the management of Saudi
Aramco for their permission to publish this article.
REFERENCES
1. Atkinson, M., Stepanov, E.V., Goulet, D.P., Sherikar, S.V.
and Hunter, J.: “High Pressure Testing of Sand Erosion in
3D Flow Channels and Correlation with CFD,” Wear, Vol.
263, Nos. 1-6, September 2007, pp. 270-277.
2. Wallace, M.S., Dempster, W.M., Scanlon, T., Peters, J. and
McCulloch, S.: “Prediction of Impact Erosion in Valve
Geometries,” Wear, Vol. 256, Nos. 9-10, May 2004, pp.
927-936.
Fig. 8. Top view of CFD predicted erosion rate (kg/m2.s) for Stellite 12 steel valve
body. Flow direction is from bottom to top.
3. Haugen, K., Kvernvold, O., Ronold, A. and Sandberg, A.:
“Sand Erosion of Wear-Resistant Materials: Erosion in
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
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75
Choke Valves,” Wear, Vols. 186-187, Part 1, July 1995,
pp. 179-188.
4. Nokleberg, L. and Sontvedt, T.: “Erosion in Choke Valves
— Oil and Gas Industry Applications,” Wear, Vols. 186187, Part 2, August 1995, pp. 401-412.
5. Nokleberg, L. and Sontvedt, T.: “Erosion of Oil and Gas
Industry Choke Valves Using Computational Fluid
Dynamics and Experiment,” International Journal of Heat
and Fluid Flow, Vol. 19, No. 6, December 1998, pp. 636643.
6. Forder, A., Thew, M. and Harrison, D.: “A Numerical
Investigation of Solid Particle Erosion Experienced within
Oil Field Control Valves,” Wear, Vol. 216, No. 2, April
1998, pp. 184-193.
7. Mazur, Z., Campos-Amezcua, R., Urquiza-Beltrán, G. and
García-Gutiérrez, A.: “Numerical 3D Simulation of the
Erosion due to Solid Particle Impact in the Main Stop
Valve of a Steam Turbine,” Applied Thermal Engineering,
Vol. 24, No. 13, September 2004, pp. 1,877-1,891.
8. Mazur, Z., Urquiza, G. and Campos, R.: “Improvement of
the Turbine Main Stop Valves with Flow Simulation in
Erosion by Solid Particle Impact CFD,” International
Journal of Rotating Machinery, Vol. 10, No. 1, January
2004, pp. 65-73.
9. Oza, A., Ghosh, S. and Chowdhury, K.: “CFD Modeling of
Globe Valves for Oxygen Application,” paper presented at
the 16th Australasian Fluid Mechanics Conference, Crown
Plaza, Gold Coast, Australia, December 3-7, 2007.
10. ANSYS FLUENT 12.0 Users’ Manual, ANSYS Inc., 2010.
11. Akbarzadeh, E., Elsaadawy, E., Sherik, A.M., Spelt, J.K.
and Papini, M.: “The Solid Particle Erosion of 12 Metals
Using Magnetite Erodent,” Wear, Vols. 282-283, April
2012, pp. 40-51.
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SAUDI ARAMCO JOURNAL OF TECHNOLOGY
BIOGRAPHIES
Dr. Ehab Elsaadawy is a Senior
Research Scientist at the Oil and Gas
Treatment R&D Division of the
Research & Development Center of
Saudi Aramco. He is currently leading
the Numerical Modeling of Separation
Flows project that focuses on
performance of the gravity separation vessels
enhancing the perfor
of Saudi Aramco’s gas-oil separation plants (GOSPs) under
the new operating conditions of increased water cuts.
Before joining Saudi Aramco, Ehab served as a Research
Engineer at Atomic Energy Canada Ltd. (AECL), Shock
River, Ontario, Canada. His research interests are fluid
dynamics of complex flows, turbulence modeling, solid
particle-laden gas flow, liquid-liquid two-phase flows and
multiphase flow modeling.
Ehab completed his B.S. degree (honors) and M.S.
degree (summa cum laude) in Mechanical Engineering at
Alexandria University, Alexandria, Egypt, with a focus on
turbulent free shear flows using Laser Doppler
Anemometer (LDA). He completed his Ph.D. studies
(summa cum laude) in Aerospace Engineering at Old
Dominion University, Norfolk, VA. The Ph.D. research
involved both experimental and computational studies of
the effects of intermittent turbulent flows on the
aerodynamic performance of airfoils.
Ehab is a Licensed Professional Engineer in Ontario
(PEO), Canada, and an active member of the Society of
Petroleum Engineers (SPE) and the National Association of
Corrosion Engineers (NACE). He has authored and
coauthored more than 30 publications in journals and
refereed conferences.
Dr. Marcello Papini is a Professor in
the Department of Mechanical and
Industrial Engineering at Ryerson
University, Toronto, Ontario, Canada,
where he has taught courses and
conducted research for 14 years. A
Tier II Canada Research Chair since
2007, Marcello is an internationally recognized researcher
2007
in the modeling of solid particle erosion, and abrasive air
and water jet processes. He is the author of more than 95
refereed journal publications in these areas.
Marcello’s research has a multitude of applications,
including development of methodologies for the reduction
of erosive wear in gas pipelines, the development of
abrasive jet technologies for the machining of microfluidic
chips, and opto-electronic and micro electromechanical
systems (MEMS) devices.
Since 2009, he has served as the only Canadian member
on the Wear of Materials Inc. steering committee, where he
is the Category Editor for Erosion, Cavitation and Impact
Wear.
Marcello received his M.A.S. and Ph.D. degrees from
the University of Toronto, Toronto, Ontario, Canada, in
1993 and 1999, respectively, both in Mechanical
Engineering.
Dr. Abdelmounam M. Al-Sherik joined
Saudi Aramco in 2004 and is currently
working for Saudi Aramco’s Research
and Development Center (R&DC) as a
Research Science Consultant with the
Materials Performance Group of the
Technical Services Division. Prior to
Aramco, he worked in Canada for over 15
jjoining
i i SSaudi
di A
years in several research positions in university, government
and industrial research centers. Abdelmounam has over 23
years of professional experience in the areas of materials
and corrosion.
He received his B.S. degree in Materials Science and
Engineering from Tripoli University, Tripoli, Libya, and his
M.S. and Ph.D. degrees in Materials and Metallurgical
Engineering from Queen’s University, Kingston, Ontario,
Canada.
Abdelmounam has authored or coauthored more than
60 journal and international conference publications in the
corrosion of pipelines and nano-structured coatings. He is
an active member of the National Association of Corrosion
Engineers (NACE), where he has chaired and vice chaired
several technical symposia. Abdelmounam is a member of
the Society of Petroleum Engineers (SPE).
SAUDI ARAMCO JOURNAL OF TECHNOLOGY
FALL 2013
77
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