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UNIVERSITY OF CALGARY
Impact of Point Bar Architecture on the Performance of SAGD
by
Yi Su
A THESIS
SUBMITTED TO THE FACULTY OF GRADUATE STUDIES
IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE
DEGREE OF DOCTOR OF PHILOSOPHY
GRADUATE PROGRAM IN CHEMICAL AND PETROLEUM ENGINEERING
CALGARY, ALBERTA
JANUARY, 2016
© Yi Su 2016
Abstract
The oil sands deposits of Western Canada are among the largest petroleum resource in the world
but face challenges with respect to production due to complex geology and high oil viscosity. In
the Athabasca oil sands deposit, the largest of the three main deposits in the province of Alberta,
the viscosity of the oil at original reservoir conditions is typically over 1 million cP. Another key
complexity of the Athabasca resource is the geology of the reservoirs which are often situated in
point bar depositional environments. To produce these reservoirs, given their low solution gas
content and other natural drive mechanisms, Steam-Assisted Gravity Drainage (SAGD) is the
method of choice. The research presented here examines the impact of point bar architecture on
the performance of SAGD; this subject has been explored by very few in the literature and yet an
understanding of the geology of the formation is fundamental to the performance of SAGD.
Four different research elements are explored. The first element deals with the impact of well
placement within the point bar. The second element consists of an examination of the impact of
orientation of a pad of SAGD wellpairs on its performance within the point bar system. The
third element explores the use of dual steam injection tubing strings on the performance of
SAGD in a point bar system. The fourth element explores the impact of steam outflow control
devices placed within injection wells on the performance of SAGD wellpairs.
The key outcomes of the research are first, the construction of a set of ultra-refined point bar
geological models for evaluation of SAGD and other recovery processes and an understanding of
the heterogeneities faced by SAGD in these systems; second, evaluation of the impact of point
bar architecture on the performance of SAGD; and third, dual tubing string steam injectors,
ii
inflow control devices can be used to improve the performance of SAGD. By developing a
better understanding of how SAGD is impacted by the geology of the oil sands reservoir, oil
rates, recovery factor, and thermal efficiency can be improved for these systems.
iii
Preface
The research work compiled in this PhD thesis was carried out to develop an ultra-defined point
bar deposit on the effect the SAGD performance. List of original publications arising from the
research documented in this thesis:
1. Su, Y., Wang, J., and Gates, I.D. SAGD Well Orientation in Point Bar Oil Sands Deposit
Affects Performance. Engineering Geology, 157:79-92, 2013.
2. Su, Y., Wang, J., and Gates, I.D. Orientation of a Pad of SAGD Well Pairs in an
Athabasca Point Bar Deposit Affects Performance. Marine and Petroleum Geology
54:37-46, 2014
3. Su, Y., Wang, J., and Gates, I.D. SAGD Pad Performance in a Point Bar Deposit with a
Thick Sandy Base. Presented at GeoConvention-Focus May 11. Submited to SPE
Reservoir Evaluation and Engineering.
4. Su, Y., Wang, J., and Gates, I.D.
Impact of Flow Control Devices on SAGD
Performance from Less Heterogeneous to Strongly Heterogeneous Reservoirs. SPE paper
174501 presented at the Heavy Oil Conference Canada, Calgary, Alberta, June 9-11,
2015
iv
Acknowledgements
I am deeply indebted to my supervisor Dr. Ian Donald Gates without whom this concept of
working in the area of an ultra-defined point bar deposit would not have taken birth in my mind.
I would like to sincerely acknowledge his valuable guidance, relentless support, discerning
thoughts and loads of inspiration that led me forward to delve deeper into the issue.
I am sincerely express my gratitude to Jacky Wang, my co-author, friend and colleague. He has
provided invaluable help during the five year of my PHD study. I appreciate his knowledge and
ideas which often inspired me on my work.
At this junction, my heartily appreciations goes to Suncor Energy, the Natural Sciences and
Engineering Research Council (NSERC) of Canada for financial support, providing me such a
good opportunity to study Doctoral programme. I would like to convey my deepest thanks to
Department of Chemical and Petroleum Engineering at University of Calgary for providing me
the financial support in terms of Graduate Teaching Assistantship for my Doctoral studies. And I
also acknowledge Schlumberger for use of its PETREL geological modeling package, thermal
reservoir simulator ECLIPSE 300, and Computer Modelling Group for use of its thermal
reservoir simulator, STARSTM.
I would like to express my warm appreciations for prime group members, my classmates, friends
who spared their times for moral support in the hours of need during my study.
v
DEDICATION
Dedicated to……
My Parents
vi
Table of Contents
Abstract ............................................................................................................................... ii
Preface................................................................................................................................ iv
Acknowledgements ..............................................................................................................v
Dedication .......................................................................................................................... vi
Table of Contents .............................................................................................................. vii
List of Tables .......................................................................................................................x
List of Figures and Illustrations ......................................................................................... xi
List of Symbols, Abbreviations and Nomenclature ......................................................... xxi
Epigraph .......................................................................................................................... xxii
CHAPTER 1: INTRODUCTION ....................................................................................1
1.1 Background ................................................................................................................1
1.2 Western Canadian Oil Resources ..............................................................................4
1.3 Steam-Assisted Gravity Drainage (SAGD) ...............................................................8
1.4 Research Questions ..................................................................................................13
1.5 Organization of Thesis .............................................................................................14
CHAPTER 2: LITERATURE REVIEW .......................................................................16
2.1 Introduction ..............................................................................................................16
2.2 Challenges faced by Steam-Assisted Gravity Drainage ..........................................17
2.2.1 SAGD Steam Conformance ............................................................................18
2.3 Point Bar Deposits ...................................................................................................19
2.3.1 Point bar Sedimentology .................................................................................20
2.3.2 Methodology of Point Bar Geology Model .....................................................29
2.3.3 Facies Analysis ................................................................................................32
2.4 Wellbore Completion technologies in SAGD .........................................................36
2.4.1 Wellbore Tubing String Design .......................................................................37
2.4.1.1 Single Tubing String Design..................................................................37
2.4.1.2 Dual-Tubing String Designs ..................................................................38
2.4.1.3 Slotted Liners .........................................................................................42
2.4.2 Limited Entry Perforations ..............................................................................43
2.4.3 Advanced Well Completion Design ................................................................45
2.4.3.1 Passive Flow Control – Inflow Control Device .....................................46
2.4.3.2 Active Flow Control –Flow Control Valve (FCV or ICV) ....................49
2.5 Studies of SAGD Process Optimization with Flow Control Devices ......................53
2.6 Field based Studies on Flow Control in SAGD .......................................................62
2.7 What is missing in the literature? ............................................................................69
2.8 Final Remarks ..........................................................................................................69
CHAPTER 3:
SUMMARY OF PUBLICATIONS ........................................................70
CHAPTER 4: SAGD WELL ORIENTATION IN POINT BAR OIL SANDS DEPOSIT
AFFECTS PERFORMANCE ...................................................................................74
4.1 Introduction ..............................................................................................................74
4.2 An Ultra-Defined Point Bar Geological Model .......................................................75
vii
4.2.1 Methodology....................................................................................................76
4.2.2 Facies Modeling ..............................................................................................78
4.2.3 Geology Model ................................................................................................83
4.3 Simulation Model Setting ........................................................................................86
4.4 Model Initialization and Well Constraints ...............................................................98
4.5 Results and Discussion ............................................................................................99
4.6 Final Remarks ........................................................................................................107
CHAPTER 5: ORIENTATION OF A PAD OF SAGD WELL PAIRS IN AN
ATHABASCA POINT BAR DEPOSIT AFFECTS PERFORMANCE ................108
5.1 Introduction ............................................................................................................108
5.2 Geological Data .....................................................................................................109
5.3 Geological Setting..................................................................................................110
5.4 Reservoir Simulation Models ................................................................................115
5.5 Results and Discussion ..........................................................................................121
5.6 Final Remarks ........................................................................................................127
CHAPTER 6: SAGD PAD PERFORMANCE ON POINT BAR DEPOSIT WITH A
THICK SANDY BASE ..........................................................................................129
6.1 Introduction ............................................................................................................129
6.2 Methodology ..........................................................................................................130
6.3 Reservoir Simulation Models ................................................................................133
6.3.1 Well Constraints and Model Initialization ....................................................141
6.4 Results and Discussion ..........................................................................................143
6.5 Final Remarks ........................................................................................................157
CHAPTER 7: IMPACT OF FLOW CONTROL DEVICES ON SAGD PERFORMANCE
FROM LESS HETEROGENEOUS TO STRONGLY HETEROGENEOUS
RESERVOIRS ........................................................................................................158
7.1 Introduction ............................................................................................................158
7.2 SAGD Completion Designs ...................................................................................159
7.3 Reservoir Simulation Model ..................................................................................168
7.3.1 Geological Setting .........................................................................................168
7.3.2 Reservoir Simulation Model..........................................................................170
7.4 Well Completions and Model Initialization...........................................................175
7.5 Results ....................................................................................................................182
7.5.1 FCDs in Clean Sand Model ...........................................................................182
7.5.2 FCDs in Point Bar Model ..............................................................................190
7.5.2.1 Uniformly-Spaced FCDs Cases ...........................................................190
7.5.2.2 Cases I5P10 and I10P5 in the Point Bar IHS Model ...........................196
7.5.2.3 Non-Uniform FCD spacing in the Point Bar Model ............................200
7.5.2.4 FCDs in Both Wells with Non-Uniform Spacing ................................204
7.6 Discussion of Results .............................................................................................207
7.7 Final Remarks ........................................................................................................210
CHAPTER 8: CONCLUSIONS AND RECOMMENDATION .....................................211
8.1 Conclusions ............................................................................................................211
viii
8.2 Recommendations ..................................................................................................213
REFERENCES ................................................................................................................214
APPENDIX ......................................................................................................................226
ix
List of Tables
Table 2.1 Results of Surmont Pad 102 well 04, 05 and 06 over the first three years of the
operation. Cumulative oil and cSOR are expressed in thousands of m3 and m3/m3,
respectively. ...................................................................................................................... 65
Table 4.1 Porosity versus horizontal permeability (in mD) correlations for each facies. ......... 84
Table 4.2 General properties of submodels. ............................................................................... 96
Table 4.3 Reservoir simulation model input parameters. ........................................................... 97
Table 5.1 Reservoir simulation model input parameters. ........................................................ 120
Table 6.1 Reservoir simulation model properties for each geological body. ........................... 140
Table 6.2 Reservoir simulation model input parameters. ........................................................ 142
Table 7.1 Several designs of passive flow control devices for steam-based recovery
processes. ........................................................................................................................ 164
Table 7.2 Porosity versus horizontal permeability (in mD) correlations for each facies. ....... 172
Table 7.3 Reservoir simulation model input parameters. ........................................................ 173
Table 7.4 Summary of simulation cases. All cases were done for the point bar IHS model
whereas only the first five (BC, I5, I10, P5, P10) were done for the clean sand model. 179
Table 7.5 Summary of results of cases over the first three years of the operation.
Cumulative oil and cSOR are expressed in thousands of m3 and m3/m3, respectively. .. 209
x
List of Figures and Illustrations
Figure 1.1 Total primary energy production in Alberta (ST98-2015 Alberta Energy
Regulator, 2015).................................................................................................................. 5
Figure 1.2 Location of the three major crude bitumen deposits in Northern Alberta (ST982015 Alberta Energy Regulator, 2015). .............................................................................. 7
Figure 1.3 In situ bitumen production by recovery method per year (ST98-2015 Alberta
Energy Regulator, 2015). Primary production refers to cold production of heavy oil
from lower viscosity heavy oil reservoirs (tend to have viscosities below 10,000 cP). ..... 8
Figure 1.4 Cross-sectional view of the Steam-Assisted Gravity Drainage (SAGD) process. ..... 10
Figure 1.5 Examples of steam chamber conformance interpreted from 4D seismic for several
SAGD operations in Alberta. ............................................................................................ 12
Figure 2.1 Schematic of SAGD operation (courtesy of MEG Energy). ...................................... 17
Figure 2.2 Point bar Deposit. From left to right: A is oil sand deposits within Alberta; B is
seismic time slice, black rectangle shows ancient point bar deposit buried
underground; C is modern meandering river. ................................................................... 20
Figure 2.3 Generalized stratigraphic column of Athabasca oil sands (Laracina). ....................... 22
Figure 2.4 Cross section of large scale estuarine point bar reservoir model of McMurray
Formation (from Wightman and Pemberton, 1997). ......................................................... 24
Figure 2.5 Core interval 153.5 to 156.8 m from AOSTRA BT06 well, UTF Phase B pilot.
Circled numbers indicate permeability sample locations. Box length is 75 cm. .............. 26
Figure 2.6 Core interval 147.1 to 150.5 m from AOSTRA BT06 well, UTF Phase B pilot.
Circled numbers indicate permeability sample locations. Box length is 75 cm. .............. 27
Figure 2.7 Core interval 141.1 to 144.7 m from AOSTRA BT06 well, UTF Phase B pilot.
Circled numbers indicate permeability sample locations. Box length is 75 cm. .............. 28
Figure 2.8 (a) Illustration of wells used for input data for point bar model, (b) plan view with
location of wells used to create the conceptual North-South stratigraphic cross section
A-B-C displayed in (c). The cross-section illustrates channel lag and inclined
heterolithic strata geometries based on well logs. ............................................................. 30
Figure 2.9 Well location s and major features identified in a seismic time slice. CPB counter point bar; SFC – Sandstone filled channels; AC – Abandoned channels or
Oxbows, and PBLM – Point bar that evolved through lateral channel migration. (from
Patruyo, 2010) ................................................................................................................... 31
xi
Figure 2.10 Examples of the four facies: A – cross-stratified sands, B – breccia lag – light
material is siltstone in bitumen saturated sand, C – massive to cross stratified very
fine to fine grained sands, and D – massive to bioturbated siltstone with sand
interbeds used to model the point bar (modified from Petruyo, 2010). Core boxes are
75 cm long. E and F show potential baffles to steam rise and oil drainage – these
intervals can be up to several meters thick........................................................................ 35
Figure 2.11 Inclined Heterolithic Stratification deposits (point bar deposits) can be
penetrated using horizontal well drilling. In the case of vertical wellbore, the
penetration is local and hence impedes the oil flow to the well (adapted from
Artindale et al. 1991)......................................................................................................... 36
Figure 2.12 Dual tubing injector completion with the heel and the toe tubing placed parallel
to each other (courtesy of ConocoPhillips Canada, 2008). ............................................... 39
Figure 2.13 Dual tubing injector completion with the heel and the toe tubing concentric to
each other (courtesy of ConocoPhillips Canada, 2008). ................................................... 40
Figure 2.14 Time lapse 4D seismic from ConocoPhillips’ Surmount SAGD project (courtesy
of ConocoPhillips, 2008). ................................................................................................. 41
Figure 2.15 Three different slotted liner patterns (courtesy of Addison Saws Ltd). ................... 43
Figure 2.16 Example of limited entry perforation design described in U.S. Patent 6,158,510
(Bacon et al. 2000). Steam is injected through pipe 12 from the surface. It flows
through the choke holes 14 and enters the annular space between pipe 12 and the
short pipe 18. Steam flows out to the reservoir through the wire-wrapped screens 22. .. 44
Figure 2.17 An example of a channel ICD design (courtesy of Baker Oil Tools). ..................... 46
Figure 2.18 An example of an orifice ICD design (courtesy of Weatherford). ........................... 47
Figure 2.19 Example design of an ICD in the production well (courtesy of Halliburton). ......... 48
Figure 2.20 Schematic of an intelligent well completion using ICVs (courtesy of
WellDynamics). ................................................................................................................ 50
Figure 2.21 Schematic of a typical sliding sleeve (courtesy of Halliburton)................................ 51
Figure 2.22 Intelligent injection well completion with 4 ICVs (courtesy of Halliburton). .......... 52
Figure.2.23 Comparison of steam chamber development, expressed in temperature profile
between control and no control case after 12, 18 and 24 months operation (used with
permission, Gotawala and Gates, 2009b). ......................................................................... 54
Figure 2.24 The schematic plot of a helical PICD (left), orifice PICD (middle), and
autonomous PICD (right) (courtesy of Baker Hughes)..................................................... 56
xii
Figure 2.25 Schematic diagrams of a steam splitter and ICD (courtesy of Southern Pacific
Resource Corporation). ..................................................................................................... 58
Figure 2.26 A schematic plot of passive inflow control device (courtesy of Schlumberger). ..... 59
Figure 2.27 Dual tubing string segmented well model (courtesy of Schlumberger). .................. 60
Figure 2.28 Schematic diagram of the injector and producer FCD-deployed liners at
ConocoPhillips’ Surmont Wellpair 102-06 (courtesy of ConocoPhillips Canada). ......... 64
Figure 2.29 Surmont 102-06 flow distribution control liner system. Red dots are open
screens in the injector whereas green dashes are open screens in the producer
(courtesy of ConocoPhillips Canada)................................................................................ 64
Figure 2.30 The 4D seismic interpretation of steam conformance of Surmont 102 North Pad
(courtesy of ConocoPhillips Canada)................................................................................ 66
Figure 2.31 A photo of control lines and steam diverter used in the Shell Orion SAGD
project (courtesy of Halliburton). ...................................................................................... 67
Figure 2.32 The seismic thermal profile, DTS temperature profile and steam injectivity of
four isolated zones in Shell Orion SAGD testing (courtesy of Shell Canada). ................ 68
Figure 4.1 (a) Illustration of wells used for input data for point bar model, (b) plan view with
location of wells used to create the conceptual North-South stratigraphic cross section
A-B-C displayed in (c). The cross-section illustrates channel lag and inclined
heterolithic strata geometries based on well logs. ............................................................. 77
Figure 4.2 Facies distribution within the inclined heterolithic unit from research area. Core
sample 5 to 15 present 285m to 308 m. Facies D, the interbedded siltstone, is outlined
in red reflect the location of the potential permeability barrier. ....................................... 80
Figure 4.3 Defined Facies logs in core B (Left) and core C (right) from core descriptions
(from Patruyo, 2010). ........................................................................................................ 81
Figure 4.4 Comparison by well between original facies log and upscaled facies logs. Well
log displayed from left to right, include gamma ray, deep resistivity, facies log and
upscaled facies log (Patruyo, 2010). ................................................................................. 82
Figure 4.5 Facies distribution in the geological model with mud-filled channel lines (scale in
vertical direction has been exaggerated 5 times). Given the scale of the model
(roughly 2.73 km by 3.245 km), shale and breccia lag facies are not visible. .................. 83
Figure 4.6 Porosity distribution in the geological model (scale in vertical direction has been
exaggerated 5 times). ........................................................................................................ 85
Figure 4.7 Water Saturation distribution in the geological model (scale in vertical direction
has been exaggerated 5 times)........................................................................................... 85
xiii
Figure 4.8 Location of the four submodels in the geological model (scale in vertical direction
has been exaggerated 5 times)........................................................................................... 86
Figure 4.9 Example of refined grid blocks surrounding SAGD wellpair (shown as grey line
in the middle of the refined grid). The color of grid blocks illustrates oil saturation
distribution. ....................................................................................................................... 87
Figure 4.10 Submodel 1 porosity distribution (scale in vertical direction has been
exaggerated 5 times). The SAGD wellpair is nearly orthogonal to the shale layers in
the model. .......................................................................................................................... 88
Figure 4.11 Submodel 1 horizontal permeability (in mD) distribution (scale in vertical
direction has been exaggerated 5 times). .......................................................................... 88
Figure 4.12 Submodel 1 oil saturation distribution (scale in vertical direction has been
exaggerated 5 times). ........................................................................................................ 89
Figure 4.13 Submodel 2 porosity distribution (scale in vertical direction has been
exaggerated 5 times). The SAGD wellpair is oriented nearly parallel to the shale
layers. ................................................................................................................................ 90
Figure 4.14 Submodel 2 horizontal permeability (in mD) distribution (scale in vertical
direction has been exaggerated 5 times). .......................................................................... 90
Figure 4.15 Submodel 2 oil saturation distribution (scale in vertical direction has been
exaggerated 5 times). ........................................................................................................ 91
Figure 4.16 Submodel 3 porosity distribution (scale in vertical direction exaggerated 5
times). The SAGD wellpair is nearly parallel to the shale layers within the submodel. . 92
Figure 4.17 Submodel 3 horizontal permeability (in mD) distribution (scale in vertical
direction has been exaggerated 5 times). .......................................................................... 92
Figure 4.18 Submodel 3 oil saturation distribution (scale in vertical direction has been
exaggerated 5 times). ........................................................................................................ 93
Figure 4.19 Submodel 4 porosity distribution (scale in vertical direction exaggerated 5
times). The SAGD wellpair is roughly perpendicular to the shale layers in the
submodel. .......................................................................................................................... 94
Figure 4.20 Submodel 4 horizontal permeability (in mD) distribution (scale in vertical
direction has been exaggerated 5 times). .......................................................................... 94
Figure 4.21 Submodel 4 oil saturation distribution (scale in vertical direction has been
exaggerated 5 times). ........................................................................................................ 95
Figure 4.22 Cumulative oil volumes produced from SAGD in each of the Submodels. ........... 100
xiv
Figure 4.23. Cumulative Steam-to-Oil Ratio (cSOR) profiles for each of the Submodels. ...... 100
Figure 4.24 Permeability, oil saturation, and temperature distributions versus time in the
plane of the SAGD wellpair in Submodel 1. S refers to the fluid phase saturations
(gas, water, and oil) whereas T refers to temperature. .................................................... 102
Figure 4.25 Permeability, oil saturation, and temperature distributions versus time in the
plane of the SAGD wellpair in Submodel 2. S refers to the fluid phase saturations
(gas, water, and oil) whereas T refers to temperature. .................................................... 103
Figure 4.26 Permeability, oil saturation, and temperature distributions versus time in the
plane of the SAGD wellpair in Submodel 3. S refers to the fluid phase saturations
(gas, water, and oil) whereas T refers to temperature. .................................................... 104
Figure 4.27. Permeability, oil saturation, and temperature distributions versus time in the
plane of the SAGD wellpair in Submodel 4. S refers to the fluid phase saturations
(gas, water, and oil) whereas T refers to temperature. .................................................... 105
Figure 5.1 Generalized stratigraphic column of the Western Canada Sedimentary Basin. ....... 111
Figure 5.2 Examples of the four facies: A – cross-stratified sands, B – breccia lag – light
material is siltstone in bitumen saturated sand, C – massive to cross stratified very
fine to fine grained sands, and D – massive to bioturbated siltstone with sand
interbeds used to model the point bar (modified from Petruyo, 2010). Core boxes are
75 cm long. E and F show potential baffles to steam rise and oil drainage – these
intervals can be up to several meters thick...................................................................... 112
Figure 5.3 Facies distribution in the geological model with mud-filled channel lines (scale in
vertical direction has been exaggerated 5 times). Given the scale of the model
(roughly 2.73 km by 3.245 km), shale and breccia lag facies are not visible. The inset
pink square indicates the location of extracted model (dimensions are 1 km by 1 km). 114
Figure 5.4 Porosity distribution of the extracted model (scale in vertical direction has been
exaggerated 2 times). ...................................................................................................... 115
Figure 5.5 Permeability distribution of the extracted model (scale in vertical direction has
been exaggerated 2 times). .............................................................................................. 116
Figure 5.6 Water Saturation distribution of the extracted model (scale in vertical direction
has been exaggerated 2 times)......................................................................................... 116
Figure 5.7 Map view of locations of SAGD well pairs in Submodel 1. Colors indicate
horizontal permeability (in mD) distribution (scale in vertical direction has been
exaggerated 2 times). ...................................................................................................... 117
Figure 5.8 Map view of locations of SAGD well pairs in Submodel 2. Colors indicate
horizontal permeability (in mD) distribution (scale in vertical direction has been
exaggerated 2 times). ...................................................................................................... 118
xv
Figure 5.9 Map view of locations of SAGD well pairs in Submodel 3. Colors indicate
horizontal permeability (in mD) distribution (scale in vertical direction has been
exaggerated 2 times). ...................................................................................................... 119
Figure 5.10. Production profiles for each the well pairs in Submodel 1. For top two plots, left
to right, cumulative steam-to-oil ratio (cSOR) and daily oil production rates. For
bottom two plots, left to right, steam injection rate (CWE) and cumulative oil
production. ...................................................................................................................... 122
Figure 5.11. Production profiles for each the well pairs in Submodel 2. For top two plots, left
to right, cumulative steam-to-oil ratio (cSOR) and daily oil production rates. For
bottom two plots, left to right, steam injection rate (CWE) and cumulative oil
production. ...................................................................................................................... 122
Figure 5.12. Production profiles for each the well pairs in Submodel 3. For top two plots, left
to right, cumulative steam-to-oil ratio (cSOR) and daily oil production rates. For
bottom two plots, left to right, steam injection rate (CWE) and cumulative oil
production. ...................................................................................................................... 123
Figure 5.13 (a) Average cumulative steam-to-oil ratio and (b) average cumulative volume of
oil produced for each submodel normalized to a single well pair (Submodels 1 and 2
consist of 9 well pairs whereas Submodel 3 has 7 well pairs). ....................................... 124
Figure 5.14 Temperature isosurface (at 200C) for well pairs in Submodel 1 at 1, 2, 4, and 6
years. Colors on domain are oil saturation. .................................................................... 125
Figure 5.15 Temperature isosurface (at 200C) for well pairs in Submodel 2 at 1, 2, 4, and 6
years. Colors on domain are oil saturation. .................................................................... 126
Figure 5.16 Temperature isosurface (at 200C) for well pairs in Submodel 3 at 1, 2, 4, and 6
years. Colors on domain are oil saturation. .................................................................... 126
Figure 6.1 Middle McMurray Estuarine Channels and Associated Point Bars at Firebag pilot
(Suncor, 2015). Core sample #26 from 304.35 m to 310.20 m. ..................................... 132
Figure 6.2 4D seismic survey for Pad 102 from Suncor Firebag pilot (Suncor, 2015) ............. 132
Figure 6.3. Facies distribution in the geological model with mud-filled channel lines (scale
in vertical direction has been exaggerated 5 times). Given the scale of the model
(roughly 2.73 km by 3.245 km), shale and breccia lag facies are not visible. The pink
square indicates the location of extracted model (dimensions are 1 km by 1 km). ........ 133
Figure 6.4 Porosity distribution of the extracted model (scale in vertical direction has been
exaggerated 5 times). The bottom 30 m is the basal sand zone (shown in top image)
and the upper 20 m are the IHS interval. ........................................................................ 134
xvi
Figure 6.5 Permeability distribution of the extracted model (scale in vertical direction has
been exaggerated 5 times). The bottom 30 m is the basal sand zone (shown in top
image) and the upper 20 m are the IHS interval. ............................................................ 135
Figure 6.6 Water Saturation distribution of the extracted model (scale in vertical direction
has been exaggerated 5 times). The bottom 30 m is the basal sand zone (shown in top
image) and the upper 20 m are the IHS interval. ............................................................ 136
Figure 6.7 Locations of SAGD well pairs in Submodel 1. Colors indicate the horizontal
permeability (in mD) distribution ................................................................................... 137
Figure 6.8 Locations of SAGD well pairs in Submodel 2. Colors indicate the horizontal
permeability (in mD) distribution. .................................................................................. 138
Figure 6.9 Locations of SAGD well pairs in Submodel 3. Colors indicate the horizontal
permeability (in mD) distribution. .................................................................................. 139
Figure 6.10 Locations of SAGD well pairs in Submodel 4. Colors indicate the horizontal
permeability (in mD) distribution. .................................................................................. 140
Figure 6.11 Cumulative steam-to-oil ratio for each SAGD well pair in each submodel. .......... 144
Figure 6.12 Cumulative produced water to injected steam (as CWE) ratio for each SAGD
well pair in each submodel. ............................................................................................. 145
Figure 6.13 Steam (CWE) injection rates for each SAGD well pair in each submodel. ........... 146
Figure 6.14 Cumulative produced oil rates for each SAGD well pair in each submodel. ......... 146
Figure 6.15 Cumulative produced water rates for each SAGD well pair in each submodel. .... 147
Figure 6.16 (a) Cumulative volume of steam injected (CWE), (b) average cumulative
volume of oil produced, and (c) average cumulative steam-to-oil ratio for each
submodel (Submodels 1 and 2 consist of 9 well pairs; Submodels 3 and 4 consist of 7
well pairs). ....................................................................................................................... 150
Figure 6.17 Temperature profile for well pairs 6 in Submodel 1 at 1, 2, 4, and 6 years (scale
in vertical direction has been exaggerated 3 times). ....................................................... 151
Figure 6.18 Temperature isosurface (at 200C) for well pairs in Submodel 1 at 1, 2, 4, and 6
years. Colours on domain are oil saturation (scale in vertical direction has been
exaggerated 2 times). ...................................................................................................... 152
Figure 6.19 Temperature isosurface (at 200C) for well pairs in Submodel 2 at 1, 2, 4, and 6
years. Colours on domain are oil saturation (scale in vertical direction has been
exaggerated 2 times). ...................................................................................................... 153
xvii
Figure 6.20 Temperature isosurface (at 200C) for well pairs in Submodel 3 at 1, 2, 4, and 6
years. Colours on domain are oil saturation (scale in vertical direction has been
exaggerated 2 times). ...................................................................................................... 154
Figure 6.21 Temperature isosurface (at 200C) for well pairs in Submodel 4 at 1, 2, 4, and 6
years. Colours on domain are oil saturation (scale in vertical direction has been
exaggerate ....................................................................................................................... 155
Figure 7.1 Slotted liner configuration (RGL 2014). .................................................................. 160
Figure 7.2 Dual-tubing string design used by Husky (2010): top image is injection well
whereas bottom one is the production well. .................................................................... 162
Figure 7.3 (a) Illustration of wells used for input data for point bar model, (b) plan view with
location of wells used to create the conceptual North-South stratigraphic cross section
A-B-C displayed in (c). The cross-section illustrates channel lag and inclined
heterolithic strata geometries based on well logs. ........................................................... 169
Figure 7.4 Facies distribution in the geological model with mud-filled channel lines (scale in
vertical direction has been exaggerated 5 times). Given the scale of the model
(roughly 2.73 km by 3.245 km), shale and breccia lag facies are not visible. The red
square indicates the location of extracted model (dimensions are 1000 m by 100 m). .. 170
Figure 7.5 Facies distribution for clean sand model (scale in vertical direction has been
exaggerated 3 times). Gray represents interbeded shale, and color yellow represents
sand. ................................................................................................................................ 172
Figure 7.6 Porosity distribution of the extracted model (scale in vertical direction has been
exaggerated 3 times). ...................................................................................................... 174
Figure 7.7 Permeability distribution of the extracted model (scale in vertical direction has
been exaggerated 3 times). .............................................................................................. 174
Figure 7.8 Water Saturation distribution of the extracted model (scale in vertical direction
has been exaggerated 3 times)......................................................................................... 174
Figure 7.9 Well Completion design for 5 FCD nozzles installed focus on lower properties
zone. Reference properties are Permeability, Porosity and Water Saturation. NICD is
another name for FCD. .................................................................................................... 177
Figure 7.10 Well Completion design for 5 FCD nozzles installed focus on higher properties
zone. Reference properties are Permeability, Porosity and Water Saturation. NICD is
another name for FCD. .................................................................................................... 178
Figure 7.11 Oil production profiles for clean sand cases with uniform distribution of FCDs
along the well pair. . ....................................................................................................... 183
xviii
Figure 7.12 Cumulative steam-to-oil ratio profiles for clean sand cases with uniform
distribution of FCDs along the well pair. ........................................................................ 184
Figure 7.13 Steam production profiles for clean sand cases with uniform distribution of
FCDs along the well pair. .............................................................................................. 185
Figure 7.14 Visualization of SAGD process for the base case in the clean sand model
(images are exaggerated 3 times in the vertical direction). ............................................. 187
Figure 7.15 Visualization of SAGD process for Case P10 in the clean sand model (images
are exaggerated 3 times in the vertical direction). .......................................................... 188
Figure 7.16 Visualization of SAGD process for Case I10 in the clean sand model (images
are exaggerated 3 times in the vertical direction). .......................................................... 189
Figure 7.17 Oil production profiles for point bar IHS cases with uniform distribution of
FCDs along the well pair................................................................................................. 191
Figure 7.18 Cumulative steam-to-oil ratio profiles for point bar IHS cases with uniform
distribution of FCDs along the well pair. ........................................................................ 191
Figure 7.19 Steam production profile for point bar IHS cases with uniform distribution of
FCDs along the well pair................................................................................................. 192
Figure 7.20 Visualization of SAGD process for the base case in the point bar IHS model
(images are exaggerated 3 times in the vertical direction). ............................................. 193
Figure 7.21 Visualization of SAGD process for Case P5 in the point bar IHS model (images
are exaggerated 3 times in the vertical direction). .......................................................... 194
Figure 7.22 Visualization of SAGD process for Case P10 in the point bar IHS model
(images are exaggerated 3 times in the vertical direction). ............................................. 195
Figure 7.23 Oil production profiles of Cases I5P10 and I10P5 in the point bar IHS model. .... 197
Figure 7.24 Cumulative steam-to-oil ratio profile of Cases I5P10 and I10P5 in the point bar
IHS model. ...................................................................................................................... 197
Figure 7.25 Steam production profile of Cases I5P10 and I10P5 in the point bar IHS model. . 198
Figure 7.26 Visualization of SAGD process for Case I5P10 in the point bar IHS model
(images are exaggerated 3 times in the vertical direction). ............................................. 199
Figure 7.27 Oil production profiles of base case and Cases I5(LP), I5(HP), P5(LP), and
P5(HP) in the point bar IHS model. ................................................................................ 201
Figure 7.28 Cumulative steam-to-oil ratio profiles of base case and Cases I5(LP), I5(HP),
P5(LP), and P5(HP) in the point bar IHS model. ............................................................ 201
xix
Figure 7.29 Steam production profiles of base case and Cases I5(LP), I5(HP), P5(LP), and
P5(HP) in the point bar IHS model. ................................................................................ 202
Figure 7.30 Visualization of SAGD process for Case I5(HP) in the point bar IHS model
(images are exaggerated 3 times in the vertical direction). ............................................. 203
Figure 7.31 Oil production profiles of base case and Cases I5(LP)P5(LP), I5(HP)P5(HP),
I5(LP)P5(HP), and I5(HP)P5(LP) in the point bar IHS model. ...................................... 204
Figure 7.32 Cumulative steam-to-oil ratio profiles of base case and Cases I5(LP)P5(LP),
I5(HP)P5(HP), I5(LP)P5(HP), and I5(HP)P5(LP) in the point bar IHS model. ............. 205
Figure 7.33 Steam production profiles of base case and Cases I5(LP)P5(LP), I5(HP)P5(HP),
I5(LP)P5(HP), and I5(HP)P5(LP) in the point bar IHS model. ...................................... 205
Figure 7.34 Visualization of SAGD process for Case I5(HP)P5(HP) in the point bar IHS
model (images are exaggerated 3 times in the vertical direction). .................................. 206
xx
List of Symbols, Abbreviations and Nomenclature
Abbreviations
Definition
CSS
cSOR
CWE
CWSR
FCD
FDC
ICD
ICV
IHS
OBIP
OOIP
PICD
SAGD
UTF
Cyclic Steam Stimulation
Cumulative Steam to Oil Ratio
Cold Water Equivalent
Cumulative Produced Water to Injected Steam Ratio
Flow Control Device, referred as ICD
Flow Distribution Control
Inflow Control Device, referred as FCD
Interval Control Valve
Inclined Heterolithic Strata
Original Bitumen in Place
Original Oil in Place
Passive Inflow Control Device, referred as FCD or ICD
Steam Assisted Gravity Drainage
Underground Test Facility
xxi
EPIGRAPH
May the Force be with You...
Star Wars
xxii
CHAPTER 1:
INTRODUCTION
1.1 Background
The International Energy Agency (IEA) has been using a World Energy Model to create longterm energy projects since 1993.The vast majority of energy is divided into fossil fuel options
such as natural gas, crude oil, and unconventional petroleum resources. Unconventional
petroleum resources include heavy oil, extra heavy oil (also referred to as bitumen), oil sands
hydrates, and tight rock. The World Energy Outlook reports that global oil production in 2014
was about 91.5 million barrels per day (WEO, 2015). In the New Policies Scenario, it grows by
about 12% from 2014, to over 100 million barrels per day by 2040, led by non-Organization of
the Petroleum Exporting Countries (OPEC) countries initially (to around 2020) and OPEC
beyond (WEO, 2015). However, this projection is uncertain given the surge of tight rock oil
production in the United States. The United States and European Union, as the largest current oil
consumers, experience the largest reductions in oil demand from 2013 to 2040. In the World
Energy Outlook report, oil and coal comprises about 83% of the global energy mix; by 2040, it is
projected that they relinquish 9% of the global energy mix with renewables growing by 5% and
gas and nuclear each growing by 2%.
The agreement that was made at the COP21 meeting in Paris in December 2015 called for
reduction of carbon dioxide emissions such that the global temperature rise is constrained to
1.5C (FCCC, 2015). With respect to fossil fuels, this implies that the whole industry should pay
1
more attention on how to increase the efficiency and lower the carbon emission while
maintaining or increasing production.
Despite calls for reductions of the use of fossil fuel due to requirements to lower carbon dioxide
emissions, projections for energy demand reveal that there will be a demand for petroleum
products including oil for the next 25 years (EIA, 2015). Thus, there is a need to ensure that oil,
and especially bitumen from unconventional sources such as oil sands reservoirs, is produced
with minimal carbon dioxide emissions.
The size of bitumen reservoirs in Western Canada makes the reserves of petroleum in Canada the
third largest in the world after that of Saudi Arabia and Venezuela (IEA, 2014). This resource is
of immense value to Canada providing over 27% of GDP to the nation. This means that it is a
resource that cannot be stranded for the economic growth of Canada. However, production of oil
sands reservoirs as found in Western Canada is both energy and emission intensive (Gates and
Larter, 2014). Bitumen, at original reservoir conditions, has viscosity typically in the millions of
centipoise and thus is not mobile and cannot be pumped to the surface by primary production or
water flooding. The first requirement of a recovery process for these types of reservoirs is to
lower the viscosity of the bitumen. This is done by injecting steam, at high pressure and
temperature, into the reservoir. When heated to over 200C, the viscosity of the bitumen drops
to less than 10 cP and it becomes mobile enough for gravity drainage or pressure-driven flow
within the reservoir.
2
Given average steam-to-oil ratio of about 3.3 m3/m3 (steam expressed as cold water equivalent)
across the province of Alberta for steam-based operations, the energy intensity of oil sands
production is equal to about 9 GJ/m3 oil produced which with about 44 GJ per cubic meter of
chemical energy in bitumen. This translates to an energy return of about 4.9 GJ out per GJ
invested. At a steam-to-oil ratio of about 3.3 m3/m3, the amount of carbon dioxide emitted to the
environment (form the combustion of natural gas to generate steam) is equal to about 0.5 tonnes
per m3 bitumen produced. This is roughly 20 to 25% greater than the emissions intensity of
conventional oil (Bergerson et al. 2012). Given COP21, there is a need to reduce the emissions
intensity of oil sands operations to lower than that of conventional oil extraction operations. The
largest source of emissions for oil sands extraction is associated with steam generation and thus,
the main target for emissions reduction is a reduction of the steam-to-oil ratio. This can be done
by two main methods. First, the use of additives such as solvents or non-condensable gas to the
steam where these additives serve to reduce the viscosity of the bitumen and thus replace the
requirement of steam to some extent but suffer from solvent recovery issues since the cost of the
solvents added to the steam often cost more than the bitumen to be extracted from the reservoir
(Gates and Chakrabarty, 2008; Govind et al., 2008; Gupta et al., 2005, 2010 and 2012). There
have been many studies on the use of additives to steam-based recovery processes for bitumen
reservoirs and most show that the steam-to-oil ratio is reduced between 5 and 50% depending on
the additive used and the operating conditions (Gupta and Gittins, 2006, 2007 and 2009; Zhao,
2007). Second, improve the utilization of steam within the reservoir so that it more effectively
contacts and mobilizes the rich-bitumen zones within the reservoir. (Gotawala and Gates, 2009;
Wei and Gates, 2010) This is equivalent to improving the conformance of steam within the
reservoir. Steam conformance within the reservoir is largely tied to the reservoir heterogeneity
3
and architecture as well as the position of the wells within the reservoir with respect to the
heterogeneity of the reservoir (Tamer and Gates, 2012; Su et al., 2012 and 2013). This has been
a rich subject of study (Zhang et al., 2005; Gates et al., 2008; Gotawala and Gates, 2009a and
2010; Ito, 2014) but nearly none have examined in detail the dynamics of steam chamber growth
in the reservoir associated with its architecture and how it affects steam chamber conformance
and furthermore how this impacts the steam-to-oil ratio of the recovery process. The second is
the main focus of the research documented in this thesis.
1.2 Western Canadian Oil Resources
Western Canada hosts over 1.8 trillion barrels of unconventional crude oil in the form of heavy
oil and bitumen (AER, 2015). Bitumen is mainly hosted in oil sand reservoirs; oil sand consists
of crude bitumen within an unconsolidated sand (typically mainly quartz) matrix. Despite the
size, however, only about 10% of the resource is recoverable under existing technology and
market conditions. Figure 1.1 shows the total primary energy production in Alberta (AER, 2015).
In 2014, Alberta produced 73.4 million m3 (462 million barrels) from in situ recovery processes.
The data reveals that the largest growth of petroleum from Albertan reservoirs over the past ten
years has been that of in situ bitumen production. This is mainly associated with the growth of
the use of the Steam-Assisted Gravity Drainage (SAGD) process in Northern Alberta.
4
Figure 1.1 Total primary energy production in Alberta (ST98-2015 Alberta Energy
Regulator, 2015).
Bitumen has an API (American Petroleum Institute) gravity lower than 10º, which implies that
its density is greater than that of water at standard conditions. For most reservoirs that are
targeted for production, the API gravity ranges from about 7 to 10API. For most bitumen
reservoirs, the viscosity of the oil is ranges from 100,000 to several million cP. Figure 1.2 shows
the three main oil sand deposits in Alberta: the Athabasca (mainly found in the McMurray
Formation), Cold Lake (mainly in the Clearwater Formation), and Peace River (mainly found in
the Bluesky Formation) deposits; shown in Figure 1.2. In the Athabasca deposit, the viscosity of
the bitumen ranges from about 500,000 to 8 million cP with the majority of it between 1 and 3
million cP. In the Cold Lake and Peace River deposits, the viscosities are slightly lower ranging
5
from 100,000 to 200,000 cP in the Cold Lake deposit and about 300,000 cP in the Peace River
deposit. In total, the three oil sand deposits occupy an area about 142,000 km2.
Depending on the depth of the deposit, either surface mining or in situ recovery methods are
used to recover bitumen. For oil sands deposits that are at depths about 70 m or less, surface
mining is used. This is the case for about 20% of the bitumen reserves in Alberta and is mainly
found North of Fort McMurray. Surface mining has high recovery factor (typically greater than
90%) and does not suffer from reservoir heterogeneities since all of the formation is processed in
surface extraction facilities to recovery the oil (AER, 2015). In typical practice, the overburden
above the oil sand reservoir is removed and the oil sand formation is pit mined by using truck
and shovel to move the ore to the processing facilities. The greatest environmental impact of
surface mining is the immense tailings ponds that result from the oil extraction process.
At depths greater than about 100 m, in situ recovery methods are employed. For bitumen
reservoirs, the two most used in situ recovery processes are Cyclic Steam Stimulation (CSS, also
referred to as huff’n’puff) and Steam-Assisted Gravity Drainage (SAGD). In both of these
processes, high pressure and temperature steam is injected into the deposit to heat the bitumen
and as a consequence, reduce its viscosity so that it can be mobilized and moved to a production
well. These two processes are quite different with respect to well design and operating conditions.
CSS is a single well process (both vertical and horizontal wells are used) where in the first part
of the process, steam is injected into the formation and in the second part of the process, fluids
are produced from the reservoir (Butler, 1997). SAGD, on the other hand, uses two horizontal
wells with continuous steam injection and fluids production (Butler, 1997).
6
Figure 1.2 Location of the three major crude bitumen deposits in Northern Alberta (ST982015 Alberta Energy Regulator, 2015).
In typical practice, CSS recovers about 30% of the bitumen before it is rendered uneconomic
whereas SAGD can reach as high as about 60% before it becomes uneconomic (Gates and Wang,
2013). CSS is mainly used in the Cold Lake and Peace River oil sand deposits whereas SAGD is
mainly used in the Athabasca deposit.
As shown in Figure 1.3, the growth of bitumen
production over the last ten years in Alberta is mainly associated with that of new SAGD
operations in the Athabasca deposit. In the research documented in this thesis, the focus of the
research is on SAGD in the Athabasca oil sands deposit.
7
Figure 1.3 In situ bitumen production by recovery method per year (ST98-2015 Alberta
Energy Regulator, 2015). Primary production refers to cold production of heavy oil from
lower viscosity heavy oil reservoirs (tend to have viscosities below 10,000 cP).
1.3 Steam-Assisted Gravity Drainage (SAGD)
The research documented here focuses on the operation of Steam-Assisted Gravity Drainage
(SAGD) well pairs in the Lower Cretaceous McMurray Formation in Alberta, one of the largest
oil sands accumulations in the world. Figure 1.4 displays a schematic of the cross-section of the
process; it consists of two horizontal wells one atop the other both parallel to each other. The
concept of SAGD was first proposed by Roger Butler while he worked at Imperial Oil Ltd. in
1978 (Butler, 1997). In the early 1980s, Imperial Oil conducted a vertical injection well and
horizontal production well pilot which proved the concept in the field (Butler, 1997). After
Butler (1997) retired from Imperial Oil and joined the Alberta Oil Sand Technology and
8
Research Authority (AOSTRA), SAGD was first piloted with dual horizontal wells in several
phases at the Underground Test Facility (UTF) with success. It has been commercially in use
since 2001 in the Athabasca oil sands deposit. From Figure 1.3, about 1,259,000 barrels/day of
bitumen was recovered by SAGD in 2014; this is 58% of in situ bitumen production in Alberta.
SAGD production increased by 26% and was responsible for 97% of the total growth of the in
situ production between 2013 and 2014 (AER, 2015). Because of the increased oil recovery
factor and thermal efficiency compared to that of CSS, SAGD technology is becoming the
process of choice for in situ oil sands recovery.
As shown in Figure 1.4, SAGD consists of two horizontal wells. The upper one is the steam
injection well whereas the lower one is the fluid production well. In typical practice, the wells
are vertically separated by about 4 to 6 m and the production well is drilled roughly 3 to 5 m
above the bottom of the oil column. The length of the injection/production wellpair is typically
between 500 and 1,000 m (Butler et al., 1981; Gates et al., 2007; Peacock, 2009). During SAGD
operation, steam injected into the oil sands reservoir travels to the cold edge of the depletion
chamber and releases its latent heat there (Gates et al., 2007; Peacock, 2009; Hubbard et al.,
2011; Gates, 2011). The released energy conducts outwards from the steam chamber into the
reservoir and heats the formation which consequently lowers the viscosity of the bitumen. In
most SAGD operations, the steam is injected between 185C and 230C which leads to a
reduction of the bitumen viscosity to lower than about 10 cP. Due to the density difference
between the steam in the chamber and the mobilized bitumen, the hot bitumen drains under
gravity to the bottom of the chamber where the production well is positioned which then
9
produces the oil to the surface (Gates et al., 2007). As the process evolves, the steam chamber
grows both vertically and laterally within the reservoir.
Figure 1.4 Cross-sectional view of the Steam-Assisted Gravity Drainage (SAGD) process.
SAGD is the ideal process for the ideal reservoir. In a uniform clean sand reservoir, the chamber
grows uniformly along the well pair and thus, the amount of bitumen contacted in the reservoir is
relatively high. In this situation, the steam conformance along the well pair will be high. On the
other hand, in reservoirs where there is strong heterogeneity, for example in the form of shale
and mud layers or brecciated intervals, steam will not flow uniformly along the well pair and
even when it is placed within the reservoir, it will not rise uniformly within the reservoir since
the shale and mud layers will serve as either barriers or baffles to flow. Furthermore, even if the
injected heat is transferred to the bitumen, these layers will act as barriers or baffles to bitumen
drainage. Thus, in bitumen reservoirs with geological heterogeneities, SAGD performance will
10
suffer. In nearly all bitumen reservoirs, there are strong geological heterogeneities, for example
in the form of point bar deposits, and thus in nearly all SAGD operations in Alberta, steam
conformance along well pairs is not ideal and the thermal efficiency, and therefore, the steam-tooil ratio, is not ideal. Figure 1.5 displays steam chamber conformance, interpreted from 4D
seismic surveys, from several oil sands operations in Alberta. The results reveal that nearly all
SAGD well pairs are not achieving uniform steam injection along the well pairs. Many have both
‘hot’ and ‘cold’ spots along the well pairs which indicate that the operations are not achieving
optimal steam contact of the bitumen and thermal efficiency within the reservoir.
The
interaction and dynamics of steam chamber development, steam-to-oil ratio, and reservoir
heterogeneity remains unresolved.
(a) 4D seismic results of Surmont project Pad 101 from ConocoPhillips (2015)
11
(b) 4D seismic results of Christina Lake project from Cenovus (2015)
(c) 4D seismic results of Firebag project from Suncor (2015)
Figure 1.5 Examples of steam chamber conformance interpreted from 4D seismic for
several SAGD operations in Alberta.
12
In SAGD, the most important performance factor is the steam-to-oil ratio (SOR) which measures
the amount of steam (always expressed as cold water equivalent) required per unit volume of
bitumen produced. The lower the SOR, the more efficient is the recovery process. The SOR also
provides an index for other performance parameters. The steam is the largest cost of the process
(associated with the cost of the fuel used to generate steam as well as the water treatment and
handling facilities) and thus the SOR also provides a measure of the cost per revenue ratio.
Natural gas is the fuel most used in the oil sands industry for steam generation in Alberta and
thus the SOR also provides a measure of the carbon dioxide emitted to oil ratio (the main
products of natural gas combustion is carbon dioxide and water). As shown by Akbilgic et al.
(2015), SORs for SAGD operations in Alberta range from about 2 to about 6 m3/m3. As shown
by Gates and Larter (2014), the theoretical limit for ideal SOR is equal to about 1 to 1.5 m 3/m3.
Thus, there is room for improvement in Albertan SAGD operations. Coupled with environmental
impact of these processes with respect to carbon dioxide emissions to the atmosphere, there is a
pressing need to reduce the SOR of SAGD operations.
1.4 Research Questions
The literature review described in Chapter 2 reveals that there are virtually no studies on the
dynamics of SAGD steam chambers in geologically heterogeneous reservoirs and in particular,
point bar deposits and the steam-to-oil ratio profile that results. The majority of Athabasca oil
sands deposits being targeted for recovery are point bar deposits.
addressed in the research documented in this thesis are as follows:
13
The research questions
1. How is the performance of a SAGD well pair impacted by the architecture of a point bar
deposit? How does the orientation of the well pair within the deposit affect process
performance?
2. How is heat and steam transport impacted by the shale layers found in a point bar deposit?
3. How is SAGD pad performance affected by its orientation within a point bar deposit?
4. Does dual-tubing string steam injection completion design improve SAGD performance?
5. Do in-well passive flow control devices improve the performance of SAGD in a point bar
deposit?
Another objective of the research was the construction of ultra-refined point bar deposit
Athabasca oil sands geological and reservoir models for well placement and recovery process
design research.
1.5 Organization of Thesis
The research contained in this thesis is documented in six chapters as follows. Chapter 2
consists of a literature review on SAGD, steam chambers conformance, challenges confronted by
SAGD, a brief introduction to point bar deposit geology, and well completion designs used and
being explored in SAGD operations. Chapter 3 lists research publications that have resulted
from this research. Chapter 4 documents the construction of an ultra-defined point bar deposit
geological model and explores how well pair orientation within the point bar model affects
SAGD performance. Chapter 5 describes a study on the effect of SAGD well pair pad orientation
within a point bar deposit. Chapter 6 describes the performance of SAGD in a point bar deposit
14
with a thick basal sand zone. Chapter 7 explores the benefits of passive flow control devices in
SAGD operations within a point bar deposit. For comparison, these devices are also evaluated in
a clean sand reservoir. Chapter 8 summarizes the major conclusions and recommendations that
arise from the research documented in this thesis.
15
CHAPTER 2:
LITERATURE REVIEW
2.1 Introduction
One key challenge faced by in-situ recovery operations for heavy oil and bitumen difficult is its
viscosity. In the Cold Lake and Peace River oil sands deposits in Alberta, the viscosity at
original reservoir conditions is typically between 10,000 and 500,000 cP whereas in the
Athabasca deposit, it tends to be greater than 1 million cP. Under drive mechanisms that can be
achieved in reservoirs (e.g. gravity, solution-gas drive, formation recompaction, thermal
expansion), it is virtually impossible to move oils with viscosities higher than ~50,000 cP in oil
sands reservoirs.
Oils with viscosity lower than ~50,000 cP with significant dissolved solution gas are cold
producible (solution gas drive is sufficient to move the oil to a production well under foamy oil
flow conditions). However, the solution gas contained in Athabasca bitumen is very small since
these reservoirs tend to be shallow and at relatively low pressure. Thus, solution gas drive is not
a viable mechanism for production from these reservoirs.
In oil sands reservoirs, to produce it to surface, the oil must be heated to reduce its viscosity. By
heating Athabasca bitumen to more than about 200C, its viscosity drops to less than 10 cP
making it sufficiently mobile enough to move under drive mechanisms such as formation
recompaction, gravity drainage, and thermal expansion. Since steam has a high latent heat, it is
presently the most used agent to deliver heat to oil sands reservoirs.
16
2.2 Challenges faced by Steam-Assisted Gravity Drainage
In the Steam-Assisted Gravity Drainage (SAGD) process, as shown schematically in Figure 2.1,
steam is injected into the reservoir through a horizontal well. Below and parallel to the injection
well is a production well. The steam travels from the steam injection well to the edge of the
depletion chamber and loses its latent heat there (Gates et al., 2007; Peacock, 2009; Gates, 2011).
Heat transfer to oil sands beyond the chamber heats the oil which in turn drops its viscosity
which in turn drains under the action of gravity to the production well at the base of the depletion
chamber.
Figure 2.1 Schematic of SAGD operation (courtesy of MEG Energy).
17
To prevent live steam production from the injection well, in field practice, a liquid pool is
maintained above the production well (Gates and Leskiw, 2010). This pool is maintained by
monitoring the temperature difference between the injected steam and the produced fluids,
referred to as the subcool temperature difference. If the temperature difference is small, this
means that the steam (gas) chamber is near the production well and there is a strong likelihood
that it will cone into the production well. This means that the injected steam never contacts
bitumen and thus, the thermal efficiency of the process suffers. If the subcool temperature
difference is high, then there is a large liquid pool above the production well and likely the
production rate can be raised to remove more of the mobilized oil from the chamber. The
subcool temperature difference is a key control variable in SAGD field operations and is
typically maintained between 15 and 30ºC (Gates et al., 2007).
As the process continues, the steam chamber grows upwards and outwards from the injection
well heating new unheated oil sand at the edge of the chamber (Gates et al., 2007). In typical
field operations, the separation between the injection and production wells is equal to about 5 m
and the length of the injection/production wellpair is between 500 and 1,000 m (Gates et al.,
2007; Peacock, 2009).
2.2.1 SAGD Steam Conformance
In SAGD, steam flows through the steam chamber and releases its latent heat at the edges of the
chamber. Butler (1987) derived a simple steam fingering theory for the length scale of the fingers
at the edge of the steam chamber. His theory predicted that steam fingers penetrate up to 6 m
18
into the cold oil sand beyond the chamber’s edge. Gotawala and Gates (2009a) corrected
Butler’s theory to reveal that the chamber grows into the reservoir as small steam undulations
with length scales of order of centimeters with conductive heating beyond the chamber edge. As
mobilized bitumen drains and more steam is injected, the boundary of depletion chamber
expands upwards and sideways within the reservoir. If the heat is not delivered to the bitumen
due to barriers or baffles that prevent steam injection and flow, then it stays at its original
viscosity and remains immobile. Thus, steam delivery to the reservoir is a critical component of
SAGD. Zhang et al. (2005) examined 4D and cross-well seismic and production data and showed
that steam conformance and oil recovery are strongly influenced by reservoir geology. In the
McMurray Formation, point bar deposits are the target for many SAGD operations which given
that its dominant drive mechanism is gravity-drainage, suffers in performance due to the
presence of extensive vertical barriers (Yang and Butler, 1992; Chen et al., 2008; Gotawala and
Gates, 2010).
2.3 Point Bar Deposits
The oil sands deposits in northeastern Alberta, Canada, are one of the largest petroleum
accumulations in the world (AER, 2015). The largest oil sands deposit, the Athabasca deposit, is
the main target for SAGD and largely consists of the McMurray Formation.
The middle
McMurray Formation is a heterogeneous unit which contains several sedimentological elements
such as point bar deposits, and abandoned mud channels (Strobl et al., 1997a; Fustic, 2007;
Fustic et al., 2012; Hubbard et al., 2011; Labrecque et al., 2011; Musial et al., 2011; Patruyo et
al., 2009; Hubbard et al. 2011). Point bar deposits largely consist of inclined heterolithic strata
19
(known as IHS), which is composed of interbedded sand and shale (Thomas et al., 1987). Due to
the presence of shale/siltstone interbeds, the reservoir commonly presents severe lateral and
vertical lithological heterogeneity.
2.3.1 Point bar Sedimentology
As a meandering stream becomes mature, the inertia of the flow moves the fastest water against
the outside of the stream channel. This causes erosion at the “cut bank” side of the channel and
deposition of solids at the inner bank. The inset photo in Figure 2.2 displays the result of this
action – a point bar. When the channels have grown close enough together, they merge and an
oxbow lake is formed from the remnant point bar channel. Since there is little to no flow in the
oxbow lake, it fills with mud.
Figure 2.2 Point bar Deposit. From left to right: A is oil sand deposits within Alberta; B is
seismic time slice, black rectangle shows ancient point bar deposit buried underground; C
is modern meandering river.
20
Figure 2.2 also shows a seismic time slice through the McMurray Formation several hundred
meters below the Earth surface which reveals ancient point bar deposits composed sand and
shale sequences and mud plugs which were once the oxbow lakes.
The Lower Cretaceous McMurray Formation is located in Northeast Alberta, Canada and is
found in the distal region of the Alberta foreland basin (Leckie and Smith, 1992; Smith et al.,
2009; Hubbard et al. 2011). As shown in Figure 2.3, the McMurray Formation overlies a
regional north to south trend unconformity that formed as a result of long exposure and erosion
of underlying Paleozoic carbonates (Leckie and Smith, 1992; Hein et al., 2000). Deposition of
the McMurray Formation of the Lower Mannville Group occurred as the Alberta foreland basin
subsided in the Barremian to Lower Albian time periods (Hubbard et al., 1999). The sediments
record a long-term sea level rise and the stratigraphic interval shows an upwards transition from
fluvial to marine deposits (Peacock, 2009; Musial et al., 2011; Labrecque et al., 2011). The most
significant elements of combined marine and non-marine deposits are tidally-influenced fluvial
channel belts and estuarine deposits (Hubbard et al., 2011; Musial et al., 2011). In general, point
bar deposits exhibit an overall upward-fining trend (Labrecque et al., 2011). The channels
formed in a broad paleo-valley that flowed to the north-northwest (Fustic, 2007; Patruyo, 2010;
Fustic et al., 2012).
21
Figure 2.3 Generalized stratigraphic column of Athabasca oil sands (Laracina).
The lower McMurray Formation member is mainly a fluvial-dominated sequence which is
preserved only at the base of the succession (Carrigy, 1959). These deposits are characterized by
breccia, which consist of mud fragments incorporated into a coarse sand matrix. They are
typically found at the base of channels that were confined within paleo-valleys the subCretaceous unconformity. The middle McMurray Formation unit is a more tidal-influenced
succession (Smith, 1987; Wightman and Pemberton, 1997) characterized by estuarine channel
22
complexes. These channel complexes developed within a high energy, tidally-influenced fluvial
system that transitioned to a more tidally-dominated system basinward (Wightman and
Pemberton, 1997). The Upper McMurray Formation member constitutes a more marginal marine
sequence characterized by laterally extensive beds of mudstone and interbedded argillaceous
marine sands (Flach and Mossop, 1985).
Overlying the McMurray Formation is the Wabiskaw Member shale and shoreface sands of the
Clearwater Formation which were deposited as a result of the ensuing southward transgression of
the boreal sea. Continued transgression deposited the Clearwater shale, which corresponds with
maximum flooding (Mossop and Flach, 1983). Most studies rely on outcrops to determine
widths, thickness, and lateral extent of point bar systems that could help to understand the
performance of analog petroleum reservoirs. When outcrops are not well exposed, determination
of these variables is difficult to achieve so that empirical data and spatial relationships are used
to estimate plan-view geometry and morphology of point bars (Pranter et al., 2007).
Recently Hubbard et al. (2011) published a study on the sedimentology of a tidally influenced
river deposit in the Lower Cretaceous Athabasca oil sands. They attribute these deposits to a
large-scale fluvial-estuarine system which consists of point bars with variable scale, geometry,
and composition. Inclined Heterolithic Strata (IHS) results from river point bar deposition
(Thomas et al., 1987). Given the orientations and length scales of IHS layers, they can impact
SAGD steam conformance and hence the recovery performance of the SAGD process. Thus,
detailed study on the nature of sedimentation is required for well placement and production of
23
bitumen from oil sands reservoirs. The McMurray Formation is 60 m to 130 m thick and is
composed mainly of unconsolidated sand and mudstones.
Strobl et al (1997a) characterized the McMurray Formation with a three component channel
model: Lower, Middle, and Upper Layers. The Lower Layer of McMurray Formation is a deeper
part of the incised valley and is mostly water-saturated whereas the Upper Layer consists of
mainly shallow marine mudstones (non-reservoir rock).
The unit displayed in Figure 2.4 represents a Middle McMurray Formation channel. This
channel consists of three major units as shown in Figure 2.4, large scale trough-cross-bedded
sands, a transition zone, and IHS, respectively.
Figure 2.4 Cross section of large scale estuarine point bar reservoir model of McMurray
Formation (from Wightman and Pemberton, 1997).
Strobl et al. (1997b) described the Underground Test Facility (UTF) Phase B reservoir as three
component channel deposit where the IHS unit extends to the base of the channel. In their study,
24
core samples from the AOSTRA BT-6 observation well were used to analyze the IHS interval
(Figure 2.5 to 2.7). The trough cross-bedded unit appears massive in core (Figure 2.8) but in
outcrop where weathering enhances sedimentological features, large-scale cross-bed sets up to
1.5 meters thick can be observed (Strobl et al., 1997b). Mudstone draping cross-bed sets appear
to have a short lateral extent. They found that a continuous cemented siltstone bed extended
more than 200 m. This could have serious impact on the growth of SAGD steam chambers.
The unit displayed in Figure 2.5 is rich in bitumen making it favourable for oil production. The
corresponding sedimentary facies are considered to be channel sand facies. The data from the
UTF SAGD pilots suggest that the placement of wellpairs in this zone is favourable for uniform
steam distribution (Strobl et al. 1997a).
The transition zone consists of smaller cross-beds (10 to 30 centimeter thick bed sets) and
rippled sands and may contain interbedded mudstones and clast intervals. A localized mudstone
clast interval marking the contact between the transition zone and the IHS unit has a lateral
continuity of approximately 50 meters based on detailed correlation of lithofacies (Figure 2.6).
There is a discontinuity in mudstone clasts which arises from sequential sedimentation from
estuarine lower channel deposition to point bar deposition. Continuous inclined heterolithic beds
have consistent eastward and northeastward dips of 5°to 12°(Figure 2.7). The sand dominated
and mudstone dominated IHS are characterized by lateral continuity perpendicular to paleo flow
direction over a distance of approximately 150 meters in the east-west direction. Composed of
25
ripple-laminated sands and mudstones (proportion of mudstone increasing upwards), the IHS
unit is interpreted to record lateral accretion along a point bar.
Figure 2.5 Core interval 153.5 to 156.8 m from AOSTRA BT06 well, UTF Phase B pilot.
Circled numbers indicate permeability sample locations. Box length is 75 cm. (Strobl et al.,
1997b)
26
Figure 2.6 Core interval 147.1 to 150.5 m from AOSTRA BT06 well, UTF Phase B pilot.
Circled numbers indicate permeability sample locations. Box length is 75 cm. (Strobl et al.,
1997b)
27
Figure 2.7 Core interval 141.1 to 144.7 m from AOSTRA BT06 well, UTF Phase B pilot.
Circled numbers indicate permeability sample locations. Box length is 75 cm. (Strobl et al.,
1997b)
28
2.3.2 Methodology of Point Bar Geology Model
The digital point bar constructed in this research is divided into two units: first, the channel lag
unit and second, the inclined heterolithic strata (IHS) unit. The mud-filled abandoned channel is
not explicitly included in the model but forms one of the boundaries on the digital point bar
model (Figure 2.8). The argillaceous sands above the IHS unit are not considered in the point
bar model. The lithology observed is divided into four facies (A, B, C, and D). Core from the
research area, the Kinosis area of Nexen’s Long Lake SAGD operation, is displayed in Figure
2.10.
The point bar modeled in this research is located in eastern Alberta, south of Fort McMurray
(Figure 2.8), encompassing 7 square km and 35 to 40 m in thickness. Through high quality
seismic time slices (Figure 2.8) it is possible to identify not only sedimentological features such
as counter point bars, abandoned mud- and sand-filled channels, and associated interchannel
deposits, but also point bar geometries (Smith et al., 2009). The 3D geometry and sedimentology
of the point bar modeled here is suggestive of sedimentation within a high energy, tidallyinfluenced meandering-fluvial system formed in a low gradient coastal plain setting influenced
periodically by tidal processes. To the west, the point bar is constrained by a mud-filled channel
(Figure 2.9). To the north-northeast, the point bar succession was partially cannibalized by the
northward-migrating counter point bar. This counter point bar acts as a permeability barrier
constraining most of the resource within the point bar.
29
Figure 2.8 (a) Illustration of wells used for input data for point bar model, (b) plan view
with location of wells used to create the conceptual North-South stratigraphic cross section
A-B-C displayed in (c). The cross-section illustrates channel lag and inclined heterolithic
strata geometries based on well logs.
30
Figure 2.9 Well location s and major features identified in a seismic time slice. CPB counter point bar; SFC – Sandstone filled channels; AC – Abandoned channels or Oxbows,
and PBLM – Point bar that evolved through lateral channel migration. (from Patruyo,
2010)
31
2.3.3 Facies Analysis
Facies A and B pertain primarily to the channel lag. Facies C and D are representative of the
inclined heterolithic strata unit. The cross section shown in Figure 2.8(c) is oriented north-south
and illustrates the geometry and distribution of the channel lag and the inclined heterolithic unit
across the point bar.
Facies A: Breccia-dominated sandstone
This facies typically consists subangular to subrounded clasts with diameter ranging from around
3 to 4 mm and it is commonly located in the channel lag. Through core observation it is evident
that Facies A is located at the base of the channel succession as shown in Figure 2.10 at the base
of channel in Well A. Bioturbation is minor to absent in this rock type and mudstone clasts
occupy about 30% of the facies.
The maximum thickness of this facies is equal to about 10 m. The permeability of this facies is
typically between about 0.5 and 4 D. For thermal recovery processes, this facies represents an
interval where the overall oil saturation is slightly lower than that of a clean sand facies since a
fraction of the volume is occupied by rock which serve as non-productive heat sinks. Thus, this
facies lowers the thermal efficiency of the recovery process relative to that of clean sand with
high oil saturation.
32
Facies B: Mudstone clasts
This facies consists of angular to sub-rounded mud rip-up clasts, as shown in Figure 2.10, in a
matrix of fine to medium-grained bitumen-saturated sand with up to 0.5% coarser grained sands.
Mud clasts are present and are up to 8 cm across and a few centimeters thick. However, some
fraction of the mud clasts is larger than the diameter of the core. Small-scale sedimentary
structures are not common. Some siderite nodules are found and bioturbation is rare to none in
this facies. This facies is an oil-rich interval containing about 16.5 wt.% bitumen on average.
However, similar to the brecciated sandstone (Facies A), for thermal recovery processes, this
facies represents an interval where a large fraction of the volume is occupied by rock which are
non-productive heat sinks. Thus, this facies also lowers the thermal efficiency of the recovery
process relative to that of clean sand with high oil saturation.
The permeability of the sand in this facies is generally between 0.25 and 1 D. The thickness of
this facies is typically from 3 to 6 m.
Facies C: Cross-stratified sands
Facies C largely consists of medium-grained sandstone and coarse grains. Some ripple crossstratified sands and planar laminated sands are evident with low-angle cross stratification also
present near to the top of the channel lag. Most sand in this facies is bitumen saturated although
in some instances, gas-containing sands are found at the top of the IHS unit capped by
argillaceous sands of the upper McMurray Formation. Bioturbation is rare and in general, the
33
porosity in this facies reduces upsection. The permeability of the sand in this facies ranges from
4 to 10 D.
The thickness of this facies tends to be between 1 and 5 m. For thermal recovery processes, this
facies is a productive interval which can be considered as relatively thermally efficient since the
majority of the energy is directed to productive oil sands.
Facies D: Interbedded sand and siltstone
As shown in Figure 2.10, this facies consists of interbedded fine-grained sandstone and siltstone
with bitumen-saturated sands. Massive to planar laminated siltstone intervals are also present in
this facies. The thickness of this facies ranges from 1 to 4 m. There are local occurrences of soft
sediment deformation and mud rip-up clasts.
Many siltstone intervals in this facies are
extensively bioturbated. Bioturbation in this facies increases upsection being more pervasive in
siltstones interbedded with sand laminae. Bioturbation in the sand interbeds is moderate but
tends to be masked by bitumen staining. The permeability of this facies is generally between 3.5
and 8 D.
For thermal recovery processes, this facies contains baffles and barriers that retard or prevent
steam flow and oil drainage, respectively, within the reservoir. The thickness of the baffles and
barriers can be several meters thick thus they can also represent significant impediments to heat
transfer within the reservoir.
34
Figure 2.10 Examples of the four facies: A – cross-stratified sands, B – breccia lag – light
material is siltstone in bitumen saturated sand, C – massive to cross stratified very fine to
fine grained sands, and D – massive to bioturbated siltstone with sand interbeds used to
model the point bar (modified from Petruyo, 2010). Core boxes are 75 cm long. E and F
show potential baffles to steam rise and oil drainage – these intervals can be up to several
meters thick.
35
2.4 Wellbore Completion technologies in SAGD
SAGD wellpairs are usually drilled horizontally and involve open-hole completions with slotted
liner installed. Horizontal wells extend the capability of gravity drainage processes and contact
sufficient reservoir to produce commercial amounts of oil over that of vertical wells (Artindale et
al. 1991).
Horizontal wells also have the potential to reduce the impact of geological
heterogeneities in SAGD processes. For example, as shown in Figure 2.11, horizontal wells can
cut through the IHS in point bar systems providing multiple points of contact to the bitumenbearing oil sand which would not be the case with a vertical wellbore. The horizontal wellbore
penetrates such drapes allowing more effective drainage of the point bar.
Figure 2.11 Inclined Heterolithic Stratification deposits (point bar deposits) can be
penetrated using horizontal well drilling. In the case of vertical wellbore, the penetration is
local and hence impedes the oil flow to the well (adapted from Artindale et al. 1991).
36
One avenue to improve the thermal efficiency and economics of SAGD is by modifications to
the well completion design. This can be done in several ways including tubing string design,
perforation design, and well placement within the reservoir.
2.4.1 Wellbore Tubing String Design
Tubing strings enable can be landed with their open ends at any point along the wellbore. This
means that they can be used to place steam at targeted points along the SAGD well pair. The
only issue is that since the steam is delivered to a point in the annular space in the well, the steam
may flow along the well before it enters the reservoir. In general, the addition of one or more
tubing strings has been done to attempt to improve the uniformity of steam injection along the
well pair. It still remains unclear as to the optimal place to land the open ends of the tubing
strings.
2.4.1.1 Single Tubing String Design
In early SAGD steam injection well design, a single tubing string was simply installed into the
injection well to deliver steam to the heel of the well. Similarly, single tubing strings were
installed with open end at the heel or the toe of the production well to ensure production of fluids
from either of those locations along the well. For the injection well, with a single tubing string
landed at the heel of the well, steam travels the entire length of the horizontal well (usually about
500 to 1000 m) to reach the far end of the toe. As a consequence of the loss of heat and pressure
while moving down the well, the quality of the steam decreases and less heat is delivered to the
37
toe of the well than is the case at the heel of the well. As a consequence, a non-uniform steam
chamber develops since reservoir heterogeneity leads to variable injectivity of steam along the
well and the steam is not able to spread evenly along the horizontal well from the heel to toe.
Therefore, as observed from 4D seismic interpretation of SAGD steam chambers, only a fraction
of the total well length will be able to achieve effective steam conformance (ConocoPhillips
Canada, 2013). For the production well, if the tubing string is landed at the toe of the well, the
fluid at the toe of the wellbore experiences much higher pressure drop due to friction and is
much closer to the tubing and lift system, compared to the fluid at the heel. This means that the
fluid at the heel flows more readily compared to that at the toe. As a consequence, gas invasion
from the steam chamber (and water coning from a bottom water zone) is more likely to occur at
the heel. Because of the non-uniform inflow in the wellbore, steam chamber growth and the
liquid level above the producer are not uniform. This will make it harder to maintain steam trap
control along the well pair. In this case, steam injected from the single short tubing may directly
enter the production tubing at heel and back to the surface, instead of doing its job of heating up
bitumen. Therefore, thermal efficiency of SAGD process for delivering steam latent heat energy
to the oil sand can be relatively low depending on the tubing string placement.
2.4.1.2 Dual-Tubing String Designs
Over the past five to ten years, SAGD operators in Alberta, Canada have improved steam
conformance along well pairs by installing dual-tubing strings in the injection and production
wells. In these well configurations, a short tubing string is installed at the heel of well and a long
tubing string is set at toe of well where steam can flow from the heel of the well as well as at the
38
end of the tubing string (ConocoPhillips, 2008). There are two configuration options for placing
the second tubing string within the slotted liner: The first one would be to place the toe tubing
parallel to the heel tubing as shown in Figure 2.12. The second option is to use a concentric
tubing design with the toe tubing inside the heel tubing as described in Figure 2.13.
For both
configurations, two tubing string are installed into the well so that steam is delivered to both the
heel and toe of the well. However, this well design has little or no capability to control fluid
injection into several targeted regions of the reservoir along the entire length of the wellbore.
The long tubing string at the toe can be dragged back to inject steam at different points along the
well pair.
Figure 2.12 Dual tubing injector completion with the heel and the toe tubing placed
parallel to each other (courtesy of ConocoPhillips Canada, 2008).
39
Figure 2.13 Dual tubing injector completion with the heel and the toe tubing concentric to
each other (courtesy of ConocoPhillips Canada, 2008).
It is obvious that the second tubing landed at the toe can yield improved steam distribution
within the injection well which likely improves steam conformance. For injection, steam is now
able to be instantaneously injected not only at the heel but also the toe of well pair. This can be
done with different volumes injected into each tubing string to attempt to obtain a uniform steam
profile along the well pair. As a result, the steam conformance at the toe end is significantly
improved compare to the injection by single short tubing deployed at heel only. As mentioned
above, the steam conformance improved by injection at both heel and toe end can quickly
increase the effective length along the SAGD well pair which in turn increases the oil production
40
rate. Another benefit is that steam trap control becomes easier and more efficient with two
injection points along the well bore to manipulate. For production, fluid is drawn from both ends
of the well bore which can benefit by dual tubing deployed. The improvement reflected in the
fluid withdrawal rate increases and inflow conformance becomes more uniform along the
horizontal well. Figure 2.14 shows the time lapse 4D seismic for Surmount project which
demonstrates the areal growth of the steam chamber with time.
Figure 2.14 Time lapse 4D seismic from ConocoPhillips’ Surmount SAGD project
(courtesy of ConocoPhillips, 2008).
41
Although dual tubing well bore designs improve SAGD performance over that of the single
tubing string designs, there are still issues involving steam conformance and inflow uniformity.
This is because steam travels from either the heel or toe towards the middle regions which given
the lengths of the horizontal well yields losses of heat and steam quality along the well pair.
Thus, the steam chamber may grow faster at the heel and toe locations and slower in the middle
regions. One simple logic to solve this issue is adding even more tubing strings into the well.
However, there is a limitation on the number of tubing strings that can be placed in the wellbore
due to the diameter of the liners, costs, and maintenance issues. Therefore, dual-tubing design
appears to be the popular choice for SAGD projects at present.
2.4.1.3 Slotted Liners
The most common completion design for SAGD wells is the slotted liner within which the inner
tubing strings are deployed. Slotted liners are primarily used in the horizontal sections of SAGD
well pairs to control sand production. Slotted liners are manufactured by cutting a series of
longitudinal slots, typically 0.30–0.46 mm (0.012–0.018 inch) wide by about 50–70 mm (2–2.75
inches) long, into the liner pipe. In some cases, the width of the slots is followed the order of
millimeters. Slot width is selected based on the oil sand formation’s grain-size distribution and
clay content (Xie, 2007). In general, there are two types of slotted liners: straight and staggered
patterns as shown in Figure 2.15.
42
Figure 2.15 Three different slotted liner patterns (courtesy of Addison Saws Ltd).
2.4.2 Limited Entry Perforations
To improve steam injection uniformity, limited entry perforations have been considered for use
in steam-recovery processes such as SAGD (Bacon et al. 2000). An example is shown in Figure
2.16 – these devices are typically simply chokes, usually of order of an inch in diameter, which
are placed along the well. In practice, several limited entry perforations are positioned along the
length of the well. These devices consist of a choke through which steam flows at sonic
conditions; the steam flow rate is solely dependent on the upstream pressure within the well.
43
This means that the steam flow rate through each choke does not depend on the reservoir
pressure adjacent to the well.
Figure 2.16 Example of limited entry perforation design described in U.S. Patent 6,158,510
(Bacon et al. 2000). Steam is injected through pipe 12 from the surface. It flows through
the choke holes 14 and enters the annular space between pipe 12 and the short pipe 18.
Steam flows out to the reservoir through the wire-wrapped screens 22.
As Figure 2.16 shown, the limited entry perforation device also has a blast joint to direct steam
flow from the choke along the well bore as well as wire-wrapped screens through which the
steam then enters the reservoir. Since there are fewer perforations along the well, the pressure is
44
more uniform along well and the steam delivery rate along the well should be, in theory, more
uniform. However, since the flow on production is usually subsonic, then the flow rate depends
on the reservoir pressure adjacent to the well. In this way, reservoir heterogeneity can affect
steam conformance along the well pair.
2.4.3 Advanced Well Completion Design
Recent work suggests that providing downhole inflow (inflow refers to flow into the well, in
other words production) control by advanced well completions can lead to improvements in
SAGD performance and steam conformance. Inflow is controlled by restricting fluid flow from
the annulus into tubing within the well bore. These devices are designed to enhance sweep
efficiency and prevent unwanted liquid or gas production along the entire wellbore. In other
words, they are design to hopefully improve steam conformance along the well pair.
The two major types of advanced completions are Inflow Control Devices (Al-Khelaiwi and
Davies, 2007) and Interval Control Valves (Gao et al., 2007). The names of the devices vary
from different supplier to supplier but in general, they are referred to as Flow Control Devices
(FCDs). Inflow control devices are sometimes referred to as ICDs and outflow control devices
(injection devices) are sometimes referred to as OCDs.
45
2.4.3.1 Passive Flow Control – Inflow Control Device
There are many recent developments in the area of ICDs and many of them are complex and
expensive relative to slotted liners and tubing string designs. An ICD is a well completion
technology that restricts fluid flow from the annulus into tubing string to distribute even inflow
along the length of well pair. ICDs usually consist of channels, as shown in Figure 2.17, or
nozzles/orifices, as displayed in Figure 2.18, that restricts flow and create additional pressure
drop across device to equalize the inflow along the well length. Liquid flow in the oil sand is
normally laminar, thus the relationship between the flow velocity and the pressure drop is linear
(Birchenko et al., 2010). On the other hand, the flow regime through an ICD is turbulent which
implies that inertia plays a role and thus there is a quadratic relationship between the velocity and
pressure drop. As demonstrated in Figures 2.17 and 2.18, the designs are relatively complex.
Figure 2.17 An example of a channel ICD design (courtesy of Baker Oil Tools).
46
Figure 2.18 An example of an orifice ICD design (courtesy of Weatherford).
For a standard completion, if the drawdown pressure drop is uniform along the well, the flow
into the well is controlled by the flow resistance. This in turn is comprised of the flow resistance
across the well and the reservoir permeability profile along the well. For the ICD displayed in
Figure 2.19, fluid inflow has a limited entrance area to travel through first and then into the
wellbore and tubing. Each ICD can be designed with different orifice or channels dimensions so
that the inflow profile is more uniform along the well. However, this flow resistance is preconfigured when the ICD is installed into the well and cannot be adjusted without recompleting
the well. Stalder (2013), in his review of the operation of FCDs in a SAGD well pair, found that
a lower subcool temperature difference was obtained over most of the completion length for
extended periods of the time than that achieved in regular slotted liner well pairs.
47
Figure 2.19 Example design of an ICD in the production well (courtesy of Halliburton).
48
2.4.3.2 Active Flow Control –Flow Control Valve (FCV or ICV)
Flow Control Valves (FCVs), also referred to as Interval Control Valves (ICVs), are surface
controlled down-hole flow control valve that can adaptively alter inflow and outflow from wells.
ICVs are a key component of intelligent (or smart) well technology. As shown in Figure 2.20,
the completion interval of intelligent well is divided into zones by packers and the inflow into
each zone is controlled by an Interval Control Valves.(ICV) are adjustable flow valves that can
be tuned to actively control the inflow or outflow from multiple completion intervals (zones). In
general, there are simpler ICVs where the operation is either open or closed and more complex
ones where the openings can be varied to alter flow rates through the devices. ICDs are
considered passive flow control device which cannot be adjusted after install, remotely operated
ICVs are active control devices where adjustments can be made as the recovery process evolves.
ICVs have been used only in a few cases in SAGD injection well to distribute steam injection
along horizontal well and it is not yet known in the public domain if their benefits offset the
additional costs of these well designs.
49
Figure 2.20 Schematic of an intelligent well completion using ICVs (courtesy of
WellDynamics).
One example of a commercial ICV configuration is the sliding sleeve arrangement shown in
Figure 2.21. The sliding sleeve ICV has two modes, open or closed. The opening action of the
ICV is controlled by a hydraulic line connected to the surface whereas the closing action is
controlled by a common hydraulic line that also controls closure of other ICVs along the
injection well. This means that fluid injection or production can be targeted to regions of the
reservoir where it is needed.
For example, in regions where injected steam has not been
effective, with ICVs it would be possible to target steam to that region by opening one or two
ICVs and closing off the remaining ones. An example of an injection well completion with four
ICVs is shown below in Figure 2.22.
50
Figure 2.21 Schematic of a typical sliding sleeve (courtesy of Halliburton).
Figure 2.22 displays four ICVs deployed along a 4½” injection tubing string within a 7” slotted
liner. Five ¼” ICV hydraulic control lines and four ¼” distributed temperature sensor lines also
run through the tubing string connecting the ICVs. In this design, three steam diverters (packers
designed for steam isolation) are placed between each pair of ICVs. The steam diverter divides
the horizontal well into four isolated intervals. The steam injected flows out to its interval
through each ICV. The adjustment of the ICVs is done through time in response to daily or
weekly injection, production, and pressure data. Thus the steam conformance along the entire
51
length of injection well can be dynamically controlled. This device has been tested at Shell’s
Orion SAGD field pilot (now owned by OSUM). The results from the field tests demonstrate a
20 to 40% reduction of cSOR and 5 to 10% increase in oil recovery can be been achieved by
using these devices (Clark et al., 2010).
Figure 2.22 Intelligent injection well completion with 4 ICVs (courtesy of Halliburton).
Some ICV devices have multiple discrete valve positions each one controllable at surface (Clark
et al., 2010). In this way, steam injection into each well interval can be customized in a
continuous and variable manner. Thus, this permits a great degree of control of flow in or out of
the well. Multiple setting ICV devices have been used in conventional oil recovery operations
(Clark et al., 2010).
52
The key issue faced by adjustable flow control devices such as interval control valves is their
cost. These systems installed on well pairs can raise the price drastically of the well pair and
given the only publically available data at present, it remains unclear if the benefits achieved, for
example by the Orion Pilot, warrant the extra expense of the wells. Therefore, most of the oil
sands industry appears to be focused on passive flow control devices at present.
2.5 Studies of SAGD Process Optimization with Flow Control Devices
Gotawala and Gates (2009b) and Gotawala and Gates (2010) presented a simulation study of
SAGD with 6 ICVs along the length of the wellpair. They proposed to use multiple injection
points along the injection well, with each injection point deployed with an internal control valve
(ICV). The concept is similar with the multiple-valve-position ICV that has been introduced
previously. A proportional-integral-derivative (PID) feedback controller is used to manipulate
steam injection pressure to enforce subcool between the injection and production wells. The
injection well is divided into six equal intervals, each being controlled by an ICV. If the subcool
temperature difference is too large along an interval, this implies that locally there is excessive
liquid hold-up in the steam chamber whereas if the difference is too low, then live steam could
be produced at the production well (Gates and Leskiw, 2010; Gates, 2011). These improvements
in SAGD performance were achieved by modifying the steam distribution along SAGD injection
well by using automatically-controlled ICVs.
Their results indicate up to a 20% reduction of the cSOR and nearly 30% increase in oil recovery
when ICVs are used compared to the case when no ICVs are used. However, the authors pointed
53
out that after 2 years of operation, the cSOR profiles are closer to each other and they concluded
that the control algorithm only works well in the early stages of the process since the error is
based on the subcool temperature difference which only has impact in the near-wellpair region.
The authors observed that in the controlled case, the steam chamber is not uniform in height
above the well pair after 12 months of controlled operation, as shown in Figure 2.23, and they
proposed that since the setpoint is the interval subcool and the control is focused to the near well
pair region. Thus, even with an enforced subcool, SAGD beyond early stage would not be
effectively controlled by the algorithm and additional data reflecting the behavior of the steam
chamber further away from the wellpair is required for effective control. This could potentially
be done by using temperature data from observation wells.
Figure.2.23 Comparison of steam chamber development, expressed in temperature profile
between control and no control case after 12, 18 and 24 months operation (used with
permission, Gotawala and Gates, 2009b).
54
Gotawala and Gates’ work shows an effective control on steam conformance in the early stage of
SAGD, through multiple FCVs coupled together to the PID control algorithm. However, control
is limited to early stages of SAGD. As soon as the steam chamber grow beyond the near
wellbore region, steam trap control loses its effect since temperature difference between the
injector and producer only reflects steam conformance around the near wellbore areas. Thus,
new control algorithms are needed to optimize SAGD beyond its early growth stage. In addition,
Gotawala and Gates (2009b) only used ICV in the injection well – nothing was done for inflow
control in the production well.
Banerjee (2013) studied passive inflow control devices (PICDs). The author summarized the
three key pressure drops critical to controlling injection and production fluid front in horizontal
wells:
1. As the pressure drop through the horizontal completion, inflow/injection coning occur at the
heel of the well. This behavior is commonly known as “heel-toe” effect.
2. The reservoir pressure drawdown that is created by the heterogeneities in the reservoir along
the length of the wellbore. An uneven fluid front will be generated due to the absence of the
heel-toe effect caused by reservoir heterogeneities.
3. The pressure drop across the completion interface, which involves the pressure drop across
inflow control devices, convergence flow across any sand screen, perforated casing or the
slotted liner.
55
Banerjee also summarized three categories of PICD available today, displayed schematically in
Figure 2.24:
1. Helical-channel/baffled. This type of PICD depends on friction to generate a pressure drop
over a large area as opposed to the near instantaneous loss through orifice or nozzles.
2. Orifice or nozzle. This type of PICD uses constrictions to generate a differential pressure
across the device.
3. Autonomous PICD. In this type of PICD, the pressure drop depends on the properties of the
produced fluids; the pressure drop changes whether oil, water, or gas is flowing through the
device.
Figure 2.24 The schematic plot of a helical PICD (left), orifice PICD (middle), and
autonomous PICD (right) (courtesy of Baker Hughes).
Banerjee (2013) pointed out that the deployment of PICDs in the injector has an immediate
improvement of steam conformance along the length of the horizontal well over that achieved in
a slotted liner completion. Furthermore, the deployment of PICDs in the production well creates
a synergistic effect by equalizing production along the wellbore length and reinforcing a uniform
56
and flat inflow profile from heel to toe of the well. This uniform fluid profile also helps to
maintain a liquid level above the production well and minimizes the risk of live steam
production. However, most of these are results based on flow models but there is no field data to
support many of the claims.
Kyanpour and Chen (2013) have examined the design of steam splitters and ICDs for SAGD.
Steam splitters are used to customize steam distribution in the injector. The only physical
difference between steam splitters and ICDs is a shroud as shown in Figure 2.25. The shroud is
an outer casing on the steam splitter which deflects steam and prevents it from damaging the
liner. This concept is the same as the blast collar described by Bacon et al. (2000). The authors
proposed a method to determine the size and position of the steam splitters for injection wells
and ICDs on production wells by using the oil production potential, OPP, as defined by CMG
(CMG, 2012):
𝑂𝑃𝑃 = 𝑘𝑏(𝑁𝑇𝐺)𝑀𝑜 𝑃𝑔𝑏 𝑆𝑜 𝜙𝑛
2.1
Where k is the average horizontal permeability, b is the thickness of the grid block, NTG is the
net-to-gross ratio, Mo is the oil phase mobility, Pgb is the grid block pressure, So is the oil
saturation,  is the porosity, and n is the net pay thickness.
57
Figure 2.25 Schematic diagrams of a steam splitter and ICD (courtesy of Southern Pacific
Resource Corporation).
In their study, Kyanpour and Chen (2013) investigated the quantity and impact of steam splitters
and ICD on SAGD by using reservoir simulation in simple oil sands model. The authors
concluded that having one ICD alone increases production by 11.5 per cent and that having one
steam splitter alone increases production by 38 per cent for the Senlac heavy oil reservoir. They
also stated that a combination of two will increase production by 45 per cent. Also, they
concluded that optimum steam distribution can be obtained by setting the steam injection rate
(from the ICDs) proportional to the oil production potential. However, these improvements are
much more than that obtained with ICVs as shown in the Orion Pilot (Clark et al., 2010) and
thus, it remains unclear if the findings are valid for realistic oil sands reservoirs.
58
Stone and his colleagues (2010-2014) in a series of simulation studies used advanced well
control strategies to evaluate well completions with flow control devices in a simplified oil sands
reservoir model. A simplified view of the passive ICD is shown in Figure 2.26. Stone (et al.,
2010) investigated the use of flow control valves (FCVs) in early stage SAGD (the steam
circulation stage and production up to one year when steam chamber is beginning to grow). In
the study, actively controlled FCVs in the injection tubing string were used where the FCV
device has the capability of multiple valve positions. Also, the injection well was divided into
multiple intervals, similar to the well completion in the Orion Pilot project. For the production
well, passive inflow control devices were deployed to improve the inflow profile. Following
Gotawala and Gates (2009b), Stone and Guyaguler’s completion design used proportional
integral-derivative (PID) feedback control for steam injection.
Figure 2.26 A schematic plot of passive inflow control device (courtesy of Schlumberger).
59
Their results showed that an ICD-deployed producer provides more even inflow because of
better controlled subcool. In their model, the well bore was modelled with multiple segments;
each segment might contain several FCDs which were converted into a single equivalent device.
The length of the annulus segments was taken to be the length of a single joint multiplied by the
orifice area of the joint and the flow rate through the nozzles were scaled to correctly model the
pressure drop across the lumped devices by increasing the effective nozzle diameter
(Schlumberger, 2014). A diagram of their completion design is shown in Figure 2.27.
Figure 2.27 Dual tubing string segmented well model (courtesy of Schlumberger).
In Figure 2.27, the long tubing string consists of Segments 2 to 8 and the annulus consists of
Segments 9 to 15. Segment 16 is a boundary segment with an additional chord that connects the
annulus to the short tubing strong. Segments 9 to 15 are connected to the reservoir. The purpose
60
of this special segment is to allow additional steam injection from the short tubing to the well as
well as circulating fluids return back to surface during the start-up period.
The multisegment well model used by Stone (et al. 2010) allows for multiphase flow within the
well bore using a drift-flux flow model (Schlumberger, 2014).
The pressure drop in this
multiphase flow model is given by the sum of the friction (viscous drag) and a form component
associated with the geometry of the system (including the effects of valves or other constrictions
in the flow):
𝐿
∆𝑃 = 2𝑐𝑢 𝑓 𝐷 𝜌𝑚𝑖𝑥 𝑣|𝑣| + λSρmix 𝑞|𝑞|
2.2
where cu is the unit conversion factor to calculate the frictional pressure loss, f is the fanning
friction factor, L is a ‘friction length’ of the device, D is the hydraulic diameter of the flow
channel, ρmix is the density of the fluid mixture, v is the mixture flow velocity, λ is a strength
multiplier used in the form pressure loss across a generic flow device, S is the base strength of
the flow control device, and q is the volumetric flow rate of the fluid mixture flowing through a
device. Gravity is also taken into account in the pressure drop calculations used in this wellbore
flow model.
61
2.6 Field based Studies on Flow Control in SAGD
Stalder (2013) described that the standard SAGD well design used at ConocoPhillips’ Surmont
SAGD project employs slotted liners with lengths ranging from 800 to 1000 m with toe-heel dual
tubing strings. For temperature measurement along the wells, thermocouples, and occasionally
fiber-optic sensors are used within the horizontal completions. Also, 4D seismic is used to
monitor steam chamber growth. Examinations of temperature and seismic data revealed that on
average the distribution of the steam chamber growth was less than 50 per cent of the full
completion length of the wells. In other words, less than 50% well pair utilization was achieved
at their operation.
To test FCDs in a field operation, in the SAGD 102-06 well pair, the injection liner used 62
joints of 6-5/8” base pipe of which 41 joints had helical restrictor and 21 joints were blank pipe
spaced throughout the liner. The size is smaller than the standard 8-5/8” injection slotted liners
typically used at the Surmont operation. The production well liner consisted of 59 joints of 65/8” base pipe, each having a helical restrictor and a 17’ sand exclusion screen. The size is close
to the Surmont standard 7” liner. Schematics of the injection and production wells are shown in
Figure 2.28. The toe tubing strings in both the injector and producer were removed from the liner
after steam circulation leaving only the heel tubing. The FCDs were deployed on the liner instead
of the tubing string of the completion, which is slightly different from the advanced completion
designs described above. The advantages of the liner-deployed FCD include:
62
1. The entire base pipe is available for fluid flow without the toe tubing string occupying part of
the pipe.
2. The liner size can be reduced when compared to tubing-deployed completion since no toe
tubing string is involved.
3. No requirement for packers to restrict flow in the annulus between the tubing string and liner
to effectively distribute steam.
4. It eliminates the risk of pulling out a tubing-deployed FCD in the producer that might
experience thermal deformation and solids accumulation inside the liner.
The key disadvantage of a liner-deployed FCD is that if remediation is required, it would not
offer the same flexibility as that of the tubing string deployed FCD.
In ConocoPhillips’ completion design, one feature is the limited perforation on the liner shown
in Figure 2.29. The typical Surmont liner design is a slotted liner with slots cut throughout the
surface of every joint in both the producer and injector – more than 90% of the liner length is
slotted. In contrast, the Surmont 102-06 well pair has only a fraction of the length of the liners
open for fluid flow. In the producer, only 36% of the length is open screen and 64% is blank
pipe. In the injector, only 0.7% of its length is open screen and 99.3% is blank pipe.
63
Figure 2.28 Schematic diagram of the injector and producer FCD-deployed liners at
ConocoPhillips’ Surmont Wellpair 102-06 (courtesy of ConocoPhillips Canada).
Surmont 102-06 Liner (30 m thick reservoir, Aspect Ratio = 1)
Injector Open Screen Sections
Heel
Producer Open Screen Sections
Meters from Heel
Toe
Magnified Section centred at 400 m
Injector: 41 Joints with 6” open screen
per 47’ joint + 21 blank joints
Producer: 59 Joints with 17’ open screen per 47’ joint
Meters from Heel
Figure 2.29 Surmont 102-06 flow distribution control liner system. Red dots are open
screens in the injector whereas green dashes are open screens in the producer (courtesy of
ConocoPhillips Canada).
64
The steam conformance achieved by Surmont well pair 102-06 is shown in Figure 2.30. Well
pairs 102-04 and 102-05 have similar reservoir qualities as that of well pair 102-06. Well pairs
102-04 and 102-05 were steam circulated in June 2007 and were put on SAGD production in
October 2007. Also, all well pairs, except for well pair 102-06, were completed with the standard
heel-and-toe dual tubing strings in both injection and production wells. Thus, a comparison
between the 102-04, 102-05 and 102-06 well pairs suggests that uniform steam conformance is
achieved with FCD-deployed liner without the toe tubing. From Table 2.1, the field results also
show that the 102-06 well pair also achieves the highest cumulative oil production and lowest
cSOR, as compared to well pairs 102-04 and 102-05, the other two most productive well pairs in
Surmont 102 North Pad. However, the results show benefit for the first three years of the
operation – later, since the chambers merge, the impact of FCDs on performance becomes less
clear.
Table 2.1 Results of Surmont Pad 102 well 04, 05 and 06 over the first three years of the
operation. Cumulative oil and cSOR are expressed in thousands of m3 and m3/m3,
respectively.
Case Name
102-04
102-05
102-06
Cum. Oil, Yr. 1
30700
30975
37647
Cum. Oil, Yr. 2
69224
75016
100047
Cum. Oil, Yr. 3
109710
123052
158537
cSOR, Yr. 1
3.35
3.64
2.07
cSOR, Yr. 2
2.68
3.37
2.44
cSOR, Yr. 3
2.62
3.17
2.57
65
Figure 2.30 The 4D seismic interpretation of steam conformance of Surmont 102 North
Pad (courtesy of ConocoPhillips Canada).
Clark et al. (2010) investigated interval control valves (ICVs) for SAGD completion in the Shell
Orion SAGD field operation (now owned by OSUM), located in the Cold Lake oil sands area of
south-central Alberta. The ICV deployed at the Orion SAGD project is quite different from the
devices used in any other SAGD project – they used active flow control devices with on/off
control. The ICVs used at Orion field is a type of sliding sleeve design capable of withstanding
high temperatures and pressure associated with steam injection. The communication to surface is
done via hydraulic lines that connect each ICV. There are two hydraulic lines on each ICV: one
controlling the opening action and one controlling the closing action. For multiple ICV devices,
there is one unique line for the opening control and a common line for the closing control of all
66
devices. Thus, for a tubing string deployed with four ICVs, a total number of 5 hydraulic lines
are required. The active ICV-deployed injection tubing string is shown in Figure 2.31.
Figure 2.31 A photo of control lines and steam diverter used in the Shell Orion SAGD
project (courtesy of Halliburton).
In the Orion SAGD pilot, three steam diverters were deployed along the injection well each one
spaced equidistant between the ICVs. Thus, four isolated well intervals, or zones referred to as
A, B, C, and D (A is heel and D is toe) were created along the well length with one ICV located
at the center of each zone. To evaluate the performance of the active ICV deployed at injection
tubing string, Clark et al. (2010) first analyzed the injectivity and temperature profile of the four
zones. The results indicated that Zones C and D towards the toe end of well had higher steam
injectivities and higher temperatures along the wellbore when compared to Zones A and B
towards the heel end of wellbore. The results of 2D seismic, DTS temperature profiles, and
steam injectivity tests are shown in Figure 2.32.
Based on the analysis of zone performance, a new steam injection strategy was devised. The
schedule consisted of cycles of:
67
1. Three weeks of steam injection into only Zones A and B at heel.
2. One week of steam injection into all four zones, and
3. One day wellpair shut-in to obtain DTS temperature profiles.
After two cycles, the results indicated that 30 to 70% improvement of injectivity into Zones A
and B was achieved. A 10 to 20ºC increase of the temperature was obtained in the heel zones and
20% reduction of the cSOR was achieved as compared to those steam strategy was applied
before. The performance of actively controlled ICV in Orion SAGD testing confirmed the
advantage of multiple, isolated well intervals along injection wellbore. The ability of steam
injection into each individual zone significantly improved steam conformance and cSOR over
uncontrolled steam injection.
Figure 2.32 The seismic thermal profile, DTS temperature profile and steam injectivity of
four isolated zones in Shell Orion SAGD testing (courtesy of Shell Canada).
68
2.7 What is missing in the literature?
The literature review reveals that although there has been a lot of ongoing work in the area of
steam conformance in SAGD associated with the heterogeneity of the reservoir, an
understanding of how geological heterogeneity, in the context of the architecture of oil sand
point bar systems, affects the performance of SAGD with respect to steam conformance and
process performance e.g. oil rate and steam-to-oil ratio, remains unclear. Also, an understanding
of how FCDs can be used in geologically heterogeneous oil sands point bar reservoirs to improve
SAGD performance also remains unclear.
2.8 Final Remarks
This chapter discusses the existing literature in the public domain on the SAGD recovery process
and steam conformance in point bar systems. The non-uniformity of steam delivery from SAGD
well pairs has been clearly demonstrated in field operations from interpretations of 4D seismic
data. If the latent heat of steam is not delivered to bitumen, it never becomes mobile (under the
action of gravity) and thus is never moved to a well for production to surface. In this Chapter,
the background information to construct the ultra-defined point bar deposit geological model has
been discussed in detail. Advanced well completion designs introduced in this chapter to
improve non-uniform conformance along SAGD wellpairs were also reviewed.
69
CHAPTER 3: SUMMARY OF PUBLICATIONS
The research documented in this thesis has resulted in four papers: two accepted in peerreviewed journals and in print and two submitted papers. A brief summary of these papers is
given as follows.
Paper 1: Su, Y., Wang, J., and Gates, I.D. SAGD Well Orientation in Point Bar Oil Sands
Deposit Affects Performance. Engineering Geology, 157:79-92, 2013.
The creation and evolution of point bar reservoir systems is well understood in meandering river
deposits. A large fraction of Athabasca oil sands deposits are ancient point bar systems
characterized by bedded, sandstone-dominated strata with interbedded siltstone layers. The
recovery process of choice for these deposits is the Steam-Assisted Gravity Drainage (SAGD)
process due to the high viscosity of the oil, low solution-gas ratio, and often caps rock not
sufficient to withstand injection pressures of Cyclic Steam Stimulation (CSS).
However,
because of the presence of siltstone interbeds, these reservoirs commonly have lateral and
vertical lithological heterogeneity which interfere with the formation of uniform steam chambers
along SAGD wellpairs. Other units in point bar deposits that impact SAGD chamber
development within the formation include remnant channel succession and channel lag. The
objective of this research is to construct a detailed three-dimensional point bar model to
determine how its heterogeneity impacts SAGD performance. Here, the point bar model is based
on the Lower Cretaceous Middle McMurray Formation in the Athabasca oil sands deposit in
Alberta, Canada. Single SAGD wellpair submodels at different locations and orientations were
70
extracted from the detailed point bar model. The results of the reservoir models simulation
suggest that attention must be paid to SAGD wellpair placement in point bar systems.
Paper 2: Su, Y., Wang, J., and Gates, I.D. Orientation of a Pad of SAGD Well Pairs in an
Athabasca Point Bar Deposit Affects Performance. Marine and Petroleum Geology, 54:3746, 2014.
It has been shown that the performance of a Steam-Assisted Gravity Drainage (SAGD) well pair
is affected by its orientation and position within a point bar deposit. In typical commercial
operations, multiple horizontal wellpairs, usually arranged parallel to each other, are arranged in
pads within oil sands reservoirs. Thus, the overall performance of the recovery process in a point
bar is not represented by a single well pair but how the set of well pairs interact with the
structure and geometry of the point bar notably including the arrangement of inclined heterolithic
strata relative to the SAGD well pairs. This research describes how the point bar structure
impacts the performance of a pad of SAGD wellpairs and the impact of pad orientation on
performance of the pad. Also, the results show that the variability of the performance of the well
pairs within the pad is large and thus, single well pair models do not provide sufficient analysis
of the SAGD process performance due to the heterogeneity of the point bar. In other words, padscale models are required for recovery process evaluation and design.
Furthermore, the
variability of performance obtained from the models provides an estimate of the variability that
may result for systems where seismic data is not available or is not sufficient to fully characterize
the point bar.
71
Paper 3: Su, Y., Wang, J., and Gates, I.D. SAGD Pad Performance in a Point Bar Deposit
with a Thick Sandy Base. Submitted to SPE Reservoir Evaluation and Engineering.
The Lower Cretaceous McMurray Formation in Alberta comprises one of the largest bitumen
accumulations in the world. The Middle McMurray Formation is a heterogeneous unit which
contains several sedimentological elements such as point bar deposits which in turn consist of
inclined heterolithic strata of interlayered sand-shale/siltstone sequences and abandoned mud
channels. Due to shale/siltstone interbeds, the reservoir commonly presents lateral and vertical
lithological heterogeneity. Point bar deposits are the target for many SAGD operations in the
McMurray Formation which given that its dominant drive mechanism is gravity-drainage, suffers
in performance from extensive vertical barriers. Here, we have constructed a detailed point bar
reservoir model (~96 million cells) conditioned to fluid compositional, logs, core, and seismic
data from an oil sands formation. As part of an ongoing study on the performance of SAGD in
point bar systems, we have evaluated the impact of the geology on pad performance in a clean
sand unit (20 m thick) with an overlying highly heterogeneous point bar deposit (30 m thick).
Many SAGD operations are being planned for similar deposits thus an understanding of its
performance within these deposits is crucial for optimal wellpair planning. Also, given the
structure of heterogeneity within the point bar, optimizing the operating strategy to maximize
process performance is important. The results clearly demonstrate that the performance of a pad
depends on the orientation of the pad within the point bar. Depending on the orientation and
wellpair placement within the point bar, IHS shale/siltstone baffles can harm the performance of
the recovery process.
72
Paper 4: Impact of Flow Control Devices on SAGD Performance from Less Heterogeneous
to Strongly Heterogeneous Reservoirs. Submitted to SPE Journal.
Steam Assisted Gravity Drainage (SAGD) has proven itself to be a commercial success in
McMurray oil sands reservoirs. In this process, steam delivered into the reservoir mobilizes
bitumen which then flows under gravity to the production well. A countercurrent flow situation
results where steam rises and bitumen and condensate drains within the reservoir. Given the
vertical and horizontal flow within the reservoir, SAGD performance is strongly affected by
reservoir heterogeneity. In the field, poor SAGD performance commonly arises from two
challenges: first, steam breakthrough from the injector to the producer and second, non-uniform
chambers along the length of the well pairs. Flow control devices (FCDs) offer the potential to
improve SAGD performance but it remains unclear how to place and design these devices to
maximize steam conformance and minimize steam-to-oil ratio. Here, to understand the behavior
of FCDs in SAGD operations, detailed reservoir simulations, including wellbore hydraulic
modeling, are conducted in a simple clean sand model and a detailed point bar model dominated
by inclined heterolithic strata. The study includes the use of FCDs on the injector only, the
producer only, as comparisons to conventional well completions cases. The results indicate that
SAGD performance improved by using FCDs with better control of steam breakthrough between
the wells.
73
CHAPTER 4: SAGD WELL ORIENTATION IN POINT BAR OIL SANDS DEPOSIT
AFFECTS PERFORMANCE
4.1 Introduction
This chapter is related to the publication: Su, Y., Wang, J., and Gates, I.D. SAGD Well
Orientation in Point Bar Oil Sands Deposit Affects Performance. Engineering Geology, 157:7992, 2013.
The Middle McMurray Formation is a heterogeneous unit which contains several
sedimentological elements such as point bar deposits composedof inclined heterolithic strata
(IHS). (Strobl et al., 1997a; Fustic, 2007; Fustic et al., 2012; Hubbard et al., 2011; Labrecque et
al., 2011; Musial et al., 2011; Patruyo et al., 2009). Because of the presence of shale/siltstone
interbeds, the reservoir commonly presents severe lateral and vertical lithological heterogeneity.
Point bar deposits are the target for many SAGD operations in the McMurray Formation which
given that its dominant drive mechanism is gravity-drainage, suffers in performance from
extensive vertical barriers (Yang and Butler, 1992; Chen et al., 2008; Gotawala and Gates,
2010). For the SAGD process, displayed in cross-section, heat transfer to oil sands is enabled by
steam injection into the oil sands formation through the upper horizontal well (Gates et al., 2007;
Peacock, 2009; Hubbard et al., 2011; Gates, 2011). In typical practice, the separation between
the injection and production wells is equal to about 5 m and the length of the
injection/production wellpair is usually between 500 and 1,000 m (Gates et al., 2007; Peacock,
2009).
74
In this work, we have constructed an ultra-defined point bar reservoir model conditioned to point
bar geological (fluid compositional, logs, core, and seismic) data of an oil sands formation and
evaluated the impact of SAGD wellpair orientation on its performance. Many SAGD operations
are being planned for point bar depositional environments thus an understanding of SAGD
performance within these deposits is essential for wellpair planning. Also, given the structure of
the heterogeneity within the point bar system, optimizing the operating strategy to maximize
process performance is important.
4.2 An Ultra-Defined Point Bar Geological Model
The Lower Cretaceous McMurray Formation is located in Northeast Alberta, Canada and is
found in the distal region of the Alberta foreland basin (Leckie and Smith, 1992; Smith et al.,
2009). For this work, the focus is on the McMurray Formation in the Long Lake area and the
model is a modified version of a point bar model created by Patruyo (2010). As mentioned in
literature, the McMurray Formation overlies a regional north to south trend unconformity surface
formed as a result of subaerial exposure and erosion of Paleozoic carbonate units (Leckie and
Smith, 1992). The most significant depositional elements of the McMurray Formation are
tidally-influenced fluvial channel belts and estuarine deposits (Hubbard et al., 2011; Musial et
al., 2011). Point bar deposits exhibit an overall upward-fining trend (Labrecque et al., 2011). The
channels were present along a broad paleo-valley that flowed to the north-northwest (Fustic,
2007; Patruyo, 2010; Fustic et al., 2012).
75
4.2.1 Methodology
The McMurray Formation in the Long Lake area is penetrated by are more than 375 vertical
evaluation wells over 154 km2 (Figure 4.1). From Patruyo (2010) research thesis, different
source data distinguished into four categories:
1.
Seismic data: In total, 30 high quality seismic time slices are spaced at 1 millisecond
intervals or at 1 meter intervals in terms of depth. These time slices are used to delineate the
geometry of internal point bar architecture, and descries sedimentological features.
2.
Geometric trends: Colored contour lines are used to build geometries that mimic point bar
accretion surfaces. These contour lines follow the circumference equation. In some places
they are altered to produce the sigmoidal shape that typically characterizes the inclined
heterolithic strata.
3.
Core samples: Seven cores were logged and drafted to identify facies and stratigraphic tops.
A total of 44 wells were cored across the research area. The tops is the model include: top of
middle McMurray Formation (as top of the point bar model), the base of the IHS, the top
and base of breccia lag. Five of the cores were sampled to clarify grain size variations,
bitumen content and porosity (Figure 4.2).
4.
Well log data: Digital logs from all 375 wells from across the research area include gamma
radiation, deep resistivity, neutron and density. These are used to generate facies log.
76
Figure 4.1 (a) Illustration of wells used for input data for point bar model, (b) plan view
with location of wells used to create the conceptual North-South stratigraphic cross section
A-B-C displayed in (c). The cross-section illustrates channel lag and inclined heterolithic
strata geometries based on well logs.
The 3D seismic volume, partially visible in Figure 4.1 (b), constrains the distribution of the
depositional elements: point bar, abandoned channel or oxbow lake, and counter point bars
(Patruyo et al., 2009; Patruyo, 2010; Hubbard et al., 2011). The core data was analyzed with a
focus on lithology and structure.
77
4.2.2 Facies Modeling
The digital point bar constructed in this research is divided into two units: first, the channel lag
unit and second, the inclined heterolithic strata (IHS) unit. The mud-filled abandoned channel is
not explicitly included in the model but forms one of the boundaries on the digital point bar
model. The argillaceous sands above the IHS unit are not considered for the point bar modeling.
The lithologies observed are divided into four facies (A, B, C, and D), Breccia-dominated
sandstone, mudstone clasts, cross-stratified sands, interbedded sand and siltstone, respectively.

Facies A consists mainly of breccia-dominated sandstone with subangular to subrounded
clasts of diameter ranging from ~3 to 4 mm; it is commonly located in the channel lag.
Bioturbation is minor to absent in this rock type and mudstone clasts occupy about 30% of
the facies. The permeability of Facies A is between 0.5 and 4 D.

Facies B mainly consists of mudstone clasts with angular to sub-rounded mud stone rip-up
clasts in a matrix of fine to medium-grained bitumen-saturated sand with up to 0.5% coarser
grained sands. Mud stone clasts 8 cm across and a few centimetres thick are present in this
facies. Some mud stone clasts can be larger than the diameter of the core. Also in this facies,
some siderite nodules are found and bioturbation is rare. The permeability of the sand in this
facies ranges from 0.25 to 1 D.

Facies C is largely made up of medium-grained sandstone with ripple cross-stratification,
planar lamination and low-angle cross stratification present. In this facies, bitumen saturates
most of the sand although some gas-bearing sands are also present at the top of the IHS unit.
78
Bioturbation is rare, and in general, the porosity in this facies reduces upsection. The
permeability of the sand in this facies is between 4 and 10 D.

Facies D comprises interbedded fine-grained sandstone and siltstone. Massive to planar
laminated siltstone intervals are also found in this facies with many siltstone intervals
extensively bioturbated.
This facies also hosts local occurrences of soft sediment
deformation and mud stone rip-up clasts. Bioturbation in this facies increases upsection being
more prevalent in siltstones interbedded with sand laminae which tends to be bitumen stained.
The permeability of Facies D tends to be between few mD and 3.5 D.
Breccia-dominated sandstone and mudstone clasts pertain primarily to the channel lag. Crossstratified sand and interbedded siltstone are representative of the inclined heterolithic strata unit,
which are significant in facies modeling. The cross section shown in Figure 4.1 (c) is oriented
north-south and illustrates the geometry and distribution of the channel lag and the inclined
heterolithic unit across the point bar.
In order to populate the geometrical model of point bar, facies logs were constructed based on
core descriptions. However, there is a limitation regarding facies differentiation within the core,
related to the facies thickness. Based on geostatistical analyses, the minimum bed thickness that
can be modeled ranges from 1 to 1.5 m depending on the layering used. Facies thinner than 1 m
are not resolved in the final model. Figure 4.3 shows some thin facies (about 0.8 m in thickness)
that are not modeled; however, they are important in correlation of the facies log with wireline
log signatures.
79
Figure 4.2 Facies distribution within the inclined heterolithic unit from research area. Core sample 5 to 15 present 285m to
308 m. Facies D, the interbedded siltstone, is outlined in red reflect the location of the potential permeability barrier.
80
Once all the facies logs created from core descriptions are calibrated with their corresponding
wireline logs, it is possible to identify typical wireline log responses for each facies. For the most
part, bitumen saturated sandy intervals display GR values lower than 60 API, no separation
distance between neutron and density porosity logs, and deep resistivity values higher than 75-80
ohm-m. Siltstone layers display GR values higher than 60 API, broader separation between
neutron and density porosity logs (about 4 units or higher), and abrupt drops on the deep
resistivity curve indicating values as low as 2025 ohm-m. A serrated pattern on the GR logs
along with a greater separation distance between neutron and density porosity logs indicates the
presence of breccia, particularly when this pattern is identified at the base of the channel.
Figure 4.3 Defined Facies logs in core B (Left) and core C (right) from core descriptions
(from Patruyo, 2010).
81
The purpose of facies log upscaling is to assign facies values to all of the 3D cells penetrated by
the well. The average method used is the Most-of method, which means that just facies with the
higher occurrence within the 3D cell will be upscaled. The upscaling process utilised here
satisfactorily replicates the discrete facies log created previously (Figure 4.3). Observation from
Figure 4.4 at arrow point 1, 2 and 3 is overestimation of Facies C (Yellow) and underestimation
of Facies D (Gray)
Figure 4.4 Comparison by well between original facies log and upscaled facies logs. Well
log displayed from left to right, include gamma ray, deep resistivity, facies log and upscaled
facies log (Patruyo, 2010).
82
4.2.3 Geology Model
The geology model of the point bar system described here is built in a geological modeling
package (Schlumberger, 2011). In the geological model, there are 546 cells in the east to west
direction and 649 cells in the north to south direction – the dimensions of the model domain are
equal to roughly 2.73 km by 3.245 km. In the horizontal directions, each geological cell has
dimensions equal to 5 m by 5 m. In the vertical direction, there are 238 cells, most of them with
thickness equal to about 1.5 m or less. The total cell count of the geological model is equal to
84,336,252.
Figure 4.5 present facies distribution populated regarding to facies upscaled
mentioned earlier.
Figure 4.5 Facies distribution in the geological model with mud-filled channel lines (scale
in vertical direction has been exaggerated 5 times). Given the scale of the model (roughly
2.73 km by 3.245 km), shale and breccia lag facies are not visible.
83
Based on semivariograms determined from log data, sequential Gaussian simulation was used to
populate the distributions of the porosity and water saturation throughout the point bar model.
Based on analysis of core data, correlations between permeability and porosity, listed in Table
4.1, were established for each facies in the geostatistical model. Also based on averaging all of
the core data, the vertical-to-horizontal permeability ratio for this model was set equal to 0.7. The
distributions of porosity and water saturation in the point bar deposit are displayed in Figures 4.6
and 4.7. The visualization of the model demonstrates that the highest water saturation layers are
associated with shale barriers in this model where porosity (and permeability) is lower than
sandstone layers.
Table 4.1 Porosity versus horizontal permeability (in mD) correlations for each facies.
Φ
A(Brecciadominated
sandstone)
B (Mudstone
clasts)
C(Crossstratified
sands)
D (Interbedded
sand and
siltstone)
0.05
10.8
17.3
17.5
5.1
0.075
0.1
0.125
36.2
85.5
166.5
61
149.2
298.6
63
156.5
317.1
24
71.9
168.3
0.15
286.9
526.5
564.7
337.4
0.175
0.2
0.225
454.6
688.2
962.5
850.4
1,288.3
1,858.4
919.7
1,403.3
2,037.1
607.6
1,011.1
1,584.7
0.25
1,318.2
2,579.1
2,843.3
2,368.6
0.275
0.3
0.325
0.35
1,752.0
2,271.5
2,884.5
3,598.7
3,469.1
4,547.3
5,832.9
7,345.1
3,844.2
5,062.8
6,522.2
8,246.0
3,407.2
4,748.4
6,443.9
8,549.2
0.375
4,421.6
9,103.2
10,258
11,123
0.4
5,360.9
11,127
12,582
14,228
84
Figure 4.6 Porosity distribution in the geological model (scale in vertical direction has been
exaggerated 5 times).
Figure 4.7 Water Saturation distribution in the geological model (scale in vertical direction
has been exaggerated 5 times).
85
4.3 Simulation Model Setting
After the geological model is complete, the next step is to import the model into a thermal
reservoir simulator (CMG, 2011). With over 80 million geological cells, and given that we do
not want to lose any resolution of the geology by upscaling the model, the resulting reservoir
simulation model is too large for practical reservoir simulation execution time. Therefore, four
submodels, each one displayed in Figure 4.8, were extracted from the full geological model. The
extracted submodels were selected with dimensions sufficiently large enough to hold a single
750 m long SAGD wellpair.
Each submodel has the following orientations and general
properties. All 4 submodels have grid refined around the wellbore, shown in Figure 4.9.
Figure 4.8 Location of the four submodels in the geological model (scale in vertical
direction has been exaggerated 5 times).
86
Figure 4.9 Example of refined grid blocks surrounding SAGD wellpair (shown as grey line
in the middle of the refined grid). The color of grid blocks illustrates oil saturation
distribution.
Submodel 1
The SAGD wellpair lies in East to West direction. A view of this submodel is shown in Figure
4.10 to 4.12. The total number of grid blocks in the extracted submodel is equal to 1,004,598.
This submodel contains more sandstone with large blocky sections with relatively high
permeability with lower permeability blocks sandwiched in between. The wellpair orientation is
orthogonal to the IHS mud layers and thus the wellpair crosses nearly all of the high permeability
regions in this submodel’s domain. To ensure that heat transfer and flow behaviour is resolved
by the grid, Submodel 1 was refined to 1 m dimension grid blocks in the cross-well direction in
the 45 m by 1005 m domain directly surrounding the wellpair. After the grid is refined, the total
number of grid blocks in the refined reservoir simulation submodel is equal to 2,726,766.
87
Figure 4.10 Submodel 1 porosity distribution (scale in vertical direction has been
exaggerated 5 times). The SAGD wellpair is nearly orthogonal to the shale layers in the
model.
Figure 4.11 Submodel 1 horizontal permeability (in mD) distribution (scale in vertical
direction has been exaggerated 5 times).
88
Figure 4.12 Submodel 1 oil saturation distribution (scale in vertical direction has been
exaggerated 5 times).
Submodel 2
The wellpair lies in North to South direction and is displayed in Figure 4.13 to 4.15. The total
number of grid blocks in the extracted submodel is equal to 1,004,598. This submodel contains
more similar blocky sections with relatively high permeability to that in Submodel 1 except that
now the wellpair is parallel to the direction to the IHS drapes. This potentially leads to vertical
separation of parts of the wellpair from the relatively high permeability zone.
Similar to
Submodel 1, Submodel 2 was refined to 1 m dimension grid blocks in the cross-well direction in
the 45 m by 1005 m domain directly around the wellpair. The refinement of the grid resulted in
2,726,766 grid blocks in the refined Submodel 2 reservoir model.
89
Figure 4.13 Submodel 2 porosity distribution (scale in vertical direction has been
exaggerated 5 times). The SAGD wellpair is oriented nearly parallel to the shale layers.
Figure 4.14 Submodel 2 horizontal permeability (in mD) distribution (scale in vertical
direction has been exaggerated 5 times).
90
Figure 4.15 Submodel 2 oil saturation distribution (scale in vertical direction has been
exaggerated 5 times).
Submodel 3
The wellpair is oriented in the Southwest-Northeast direction near the downstream portion of the
point bar paleo-flow and is shown in Figure 4.16 to 4.18. The total number of gridblocks in the
extracted submodel is equal to 3,015,936. In particular, this submodel is parallel to the paleoflow and IHS near the downstream end of the point bar.
The wellpair intersects several
relatively high permeability zones although there are large amounts of lower permeability
regions within the domain. Potentially, if the IHS drapes are extensive, then they present
themselves as barriers for flow of steam to upper high permeability zones. As described above,
Submodel 3 was refined to 1 m dimension grid blocks in the cross-well direction in the 45 m by
800 m domain directly around the wellpair. This led to 3,421,266 grid blocks in the refined
Submodel 3 reservoir model.
91
Figure 4.16 Submodel 3 porosity distribution (scale in vertical direction exaggerated 5
times). The SAGD wellpair is nearly parallel to the shale layers within the submodel.
Figure 4.17 Submodel 3 horizontal permeability (in mD) distribution (scale in vertical
direction has been exaggerated 5 times).
92
Figure 4.18 Submodel 3 oil saturation distribution (scale in vertical direction has been
exaggerated 5 times).
Submodel 4
This wellpair is oriented in the Southeast-Northwest direction near the downstream end of the
point bar paleo-flow and is displayed in Figure 4.19 to 4.21. The total number of gridblocks in
the extracted submodel is equal to 3,071,390. This submodel is orthogonal to the paleo-flow
near the downstream end of the point bar. The wellpair in this submodel appears to cut across
the IHS and higher permeability reservoir sections. Submodel 4 was refined to 1 m dimension
grid blocks in the cross-well direction in the 45 m by 800 m domain directly around the wellpair.
The resulting refined Submodel 4 model contained 3,648,541 grid blocks.
93
Figure 4.19 Submodel 4 porosity distribution (scale in vertical direction exaggerated 5
times). The SAGD wellpair is roughly perpendicular to the shale layers in the submodel.
Figure 4.20 Submodel 4 horizontal permeability (in mD) distribution (scale in vertical
direction has been exaggerated 5 times).
94
Figure 4.21 Submodel 4 oil saturation distribution (scale in vertical direction has been
exaggerated 5 times).
Figures 4.22 to 4.24 display distributions of the porosity, horizontal permeability and oil
saturation of the four submodels. The faint black lines within the images indicate the locations
of the SAGD wellpairs within the submodels. Table 4.2 lists average reservoir properties for
each of the submodels. The data reveals that Submodel 4 has the highest average porosity and
average horizontal permeability whereas Submodel 2 has the lowest average porosity and
average horizontal permeability. With respect to oil in place, Submodel 1has the higher amount
compare with Submodel 2, whereas Submodel 4 has higher amount compare with Submodel 3.
95
Table 4.2 General properties of submodels.
Properties
Submodel 1
Submodel 2
Submodel 3
Submodel 4
Porosity
0.299
0.275
0.297
0.306
kh, mD
5,609
4,685
5,092
5,627
kv, mD
3,926
3,279
3,565
3,939
Original Oil in
Place, m3
64,629
50,558
169,860
205,330
Due to the unconformity of breccia-dominated sandstone at the base of the model, the thickness
of the productive oil column of the point bar deposit is between 30 and 40 m. The production
wells in each submodels are located 2 m above the unconformity and the injection wells are
positioned 5 m vertically above the production wells. Table 4.3 summarizes the fluid, rock/fluid
properties, and other properties used in the reservoir models. The bitumen viscosity, oil-water
relative permeability curve endpoints, solution gas solubility in the oil phase (given by Kvalues), and other reservoir properties are typical of that used for Athabasca oil sands deposits
and are listed in Table 4.3.
The reservoir simulation submodels were run on a 12-core personal computer with 2.4 GHz
processors. The average execution time for the simulations was about 60 hours for Submodels 1
and 2 and about 100 hours for Submodels 3 and 4.
96
Table 4.3 Reservoir simulation model input parameters.
Item
Value
Well length, m
Separation between injector and producer, m
Reservoir thickness, m
Initial Reservoir Temperature, C
Initial Reservoir Pressure at top of model, kPa
Depth of top of model, m
Sorw
Swc for Facies A
Swc for Facies B
Swc for Facies C
Swc for Facies D
Sorg
Sgc
krwro
krocw
krogc
krg(Sorg)
Three phase relative permeability model (CMG, 2010)
750
5
~30
10
2,300
282
0.25
0.3
0.5
0.2
0.4
0.005
0.005
0.1
0.992
0.834
1
Stone Model 2
Rock and overburden/understrata heat capacity, kJ/m3C (Butler,
1997)
2,600
Rock, overburden, understrata thermal conductivity, kJ/m dayC
(Butler, 1997)
660
Bitumen thermal conductivity, kJ/m dayC (Butler, 1997)
Solution Gas to Oil Ratio, m3/m3
kv 4
Methane K-value correlation, K-value =
kv1 T  k v 5
e
P
(CMG, 2013)
Bitumen viscosity correlation (Mehrotra and Svrcek, 1986)
ln ln µ (cP) = A+B ln T(K)
97
11.5
5
kv1= 5.45x105 kPa
kv4= 879.84C
kv5 = 265.99C
A=22.8515
B = -3.5784
4.4 Model Initialization and Well Constraints
The initial temperature of the formation for all submodels is initially set equal to 10°C. At the
top of the formation (depth equal to 282 m), the initial pressure is set equal to 2,300 kPa. For
injection wells, during SAGD operation, two constraints are prescribed: 1. maximum steam
injection pressure equal to 3,500 kPa and 2. maximum steam injection rate equal to 400 m3/day
(expressed as cold water equivalent, CWE). The saturation temperature corresponding to the
injection pressure is equal to 242.6°C. The injected steam quality is set equal to 90%. For
production wells, during SAGD operation, steam trap control is applied via a maximum steam
production constraint equal to 1 m3(CWE)/day.
Prior to SAGD operation, steam circulation was modeled for four months by using temporary
heaters placed in the locations of the injection and production wells (heat delivery rate equivalent
to 90% 3,500 kPa steam at 200 m3(CWE)/day). In addition, temporary production wells were
placed in the locations of the injection wells (all production wells set with bottom hole pressure
equal to the initial reservoir pressure at the well depths) to deal with pressure buildup associated
with thermal expansion of the fluids near the well bore (Gates et al., 2007). After the steam
circulation period was completed, SAGD mode was started: the temporary heaters were turned
off, the temporary production wells in the location of the injection wells were removed, and
steam was injected into the upper injection wells and fluid was produced from the lower
production wells.
98
4.5 Results and Discussion
Figures 4.22 and 4.23 display profiles of the cumulative oil produced and cumulative steam-tooil ratio (cSOR) versus time for Submodels 1 to 4, respectively. The cSOR profiles include the
steam injected during the steam circulation period. The results reveal that the most productive
wellpair is the one in Submodel 4 whereas the least productive wellpair is the one in Submodel 2.
The wellpair in Submodel 4 intersects mainly high permeability reservoir and thus it has large
capability for injecting steam and producing bitumen. Also, the wellpair cuts across the shale
layers and thus the layers do not act as barriers to steam flow and oil drainage. The second most
productive wellpair is the Submodel 1 wellpair.
This wellpair cuts across a few high
permeability blocks but also intersects a relatively large block of relatively low permeability
reservoir.
As a result, steam is readily injected into and oil is produced from the high
permeability zones along the wellpair but the low permeability contributes little towards
production (discussed below and shown in Figure 4.24). The lowest cumulative oil produced is
realized from the Submodel 2 wellpair. This wellpair does not intersect a large fraction of high
permeability zones within the reservoir and thus its oil production is low. A similar result occurs
for the Submodel 3 wellpair. In the Submodels 2 and 3, the wellpairs are oriented nearly parallel
to the shale layers which hinder steam flow and oil drainage from the reservoir (shown in Figures
4.25 and 4.26).
99
Figure 4.22 Cumulative oil volumes produced from SAGD in each of the Submodels.
Figure 4.23. Cumulative Steam-to-Oil Ratio (cSOR) profiles for each of the Submodels.
100
The results show that the lowest cSOR profile is obtained in Submodel 1 with a minimum value
equal to about 5 m3/m3 which rises to about 6 m3/m3 after six years of operation. In this
submodel the wellpair intersects both high permeability and low permeability reservoir and it is
oriented nearly orthogonal to the IHS; in the high permeability zones, steam has the ability to
rise up through the inclined layers and oil can drain downwards to the production well. The low
cSOR implies that the steam is well utilized – steam moves into the reservoir, mobilizes bitumen,
which then drains effectively to the production well in these regions. However, since a large
fraction of the wellpair is in low permeability reservoir, its cumulative oil produced is lower than
that of the Submodel 4 wellpair. The Submodel 4 wellpair has the second best performance
among the Submodel wellpairs with respect to cSOR with a minimum value equal to 6 m3/m3
rising to about 7 m3/m3 after six years of operation. The next best relative cSOR is found in the
Submodel 3 wellpair but its value is above 10 m3/m3 and would not be considered a viable option
for development (given economic cSOR cut-off equal to about 7 m3/m3 associated with current
oil and natural gas prices). The highest cSOR is obtained from the wellpair in Submodel 2 – it
remains above 30 m3/m3 over the first six years of operation.
Figure 4.24 displays cross-sectional views of the permeability, fluid saturations (depicted in a
ternary plot distribution indicating relative amounts of oil, gas, and water saturation), and
temperature distributions in the plane containing the SAGD wellpair for Submodel 1. The
results demonstrate that early in the process the temperature distributions evolve along the
wellpair between the shale layers. Since the wellpair cuts across all of the shale layers, all of
them are contacted by injected steam. After about 4 years of steam injection, the entire zone
above the wellpair has been heated to steam temperature. The distributions of the oil, gas
101
(largely containing steam), and water reveals that steam conformance (marked by the purple
zone within the reservoir) along the wellpair is reasonably good with the steam zone reaching
about three-quarters of the well by Year 6. After 1 year of operation, the fluid phase saturation
distributions reveal that steam is rising into the formation parallel to the shale layers within the
formation. Since the permeability is relatively high near the heel of the wellpair (the right side of
the images), steam conformance there is excellent. In the region near the toe of the wellpair, the
steam has limited penetration into the reservoir despite the temperature distribution which
reveals that this zone is hot. By Year 6, most of the zone that has not been penetrated with steam
is occupied by oil and water. This later corresponds to a zone of a high density of shale layers.
Figure 4.24 Permeability, oil saturation, and temperature distributions versus time in the
plane of the SAGD wellpair in Submodel 1. S refers to the fluid phase saturations (gas,
water, and oil) whereas T refers to temperature.
102
Figure 4.25 displays cross-sectional distributions of the fluid phase saturations and temperature
in the plane of the SAGD wellpair for Submodel 2. The results reveal that even though heat
transfer to the system occurs via steam injection as measured by the temperature distribution, the
steam zone does not grow significantly within the formation (marked by the purple zone above
the wellpair). Steam conformance in this submodel is not as large in extent as that in Submodel
1 and as a result, the overall performance of the wellpair is poor. Given that the shale layers are
not intersected by the wellpairs but are nearly parallel to them, oil drainage back to the wellpairs
is not as effective as that in Submodel 1 and thus, with reduced drainage, the steam chamber
have trouble establishing itself.
Figure 4.25 Permeability, oil saturation, and temperature distributions versus time in the
plane of the SAGD wellpair in Submodel 2. S refers to the fluid phase saturations (gas,
water, and oil) whereas T refers to temperature.
103
Figure 4.26 shows cross-sectional views of the distributions of fluid saturations and temperature
for Submodel 3. In this case, the wellpair is oriented nearly parallel to the shale layers. The
results reveal that the steam chamber grows at multiple disconnected zones along the length of
the wellpair. The temperature distributions show that heat transfer is occurring through “holes”
in the shale layers, in other words, the shale layers in the Submodel 3 are acting as baffles with
breaches in the shale layers rather than barriers that prevent steam transfer. Steam conformance
is poor along the Submodel 3 wellpair with multiple “cold” spots along the wellpair.
Figure 4.26 Permeability, oil saturation, and temperature distributions versus time in the
plane of the SAGD wellpair in Submodel 3. S refers to the fluid phase saturations (gas,
water, and oil) whereas T refers to temperature.
104
Figure 4.27 displays the distributions of the fluid saturations and temperature for Submodel 4. In
this submodel, the wellpair cuts across the shale layers in the domain similar to that in Submodel
1. The steam saturation and temperature distributions demonstrate that steam conformance
achieved along the wellpair is superior relative to that achieved in the other submodels. The
evolving steam saturation distributions reveal that the steam is rising along the bottom of the
shale layers into the formation. As a result, oil drains along the inclined sand layers to the
production well. The high density of shale layers located roughly 40% of the way down the
wellpair from the heel (at the left side of the image) results in very limited steam injectivity into
the formation leading to a persistent cold spot at that location.
Figure 4.27. Permeability, oil saturation, and temperature distributions versus time in the
plane of the SAGD wellpair in Submodel 4. S refers to the fluid phase saturations (gas,
water, and oil) whereas T refers to temperature.
105
The results demonstrate that the performance of the SAGD wellpair depends significantly on its
orientation in the point bar system. The wellpairs in Submodels 1 and 4 cut across shale layers
and strata with low permeability layers which allow injection of steam into the formation and oil
drainage from the formation. Since the steam chambers extend in the cross-well direction, steam
flow into and oil drainage from the reservoir, the steam chamber extends laterally from the
wellpairs. The wellpairs in Submodels 2 and 3 do not cut across the shale layers and are parallel
or nearly parallel to the drapes. As a result, with extensive IHS, steam cannot spread vertically
or laterally as far as is the case in the wellpairs in Submodels 1 and 4 and thus they are not as
productive as those wellpairs. The results demonstrate that the wellpairs positioned so that it
cuts through the shale layers performs significantly better than the wellpair oriented parallel to
the shale layers. This implies that for design of SAGD wellpair placement within point bar
systems within the Athabasca oil sands deposit that the point bar itself has to be carefully
mapped to understand the orientation of the point bar and the shale layers. In typical practice,
the wellpairs are oriented either East-West or North-South within the deposit with no regard for
the orientation of the point bar. The results indicate that wellpairs that radiate from a central pad
that cut across the shale layers may have potentially better performance than wellpairs arranged
in fixed East-West or North-South orientations.
106
4.6 Final Remarks
This research is a first start to understand how the structure of a point bar impacts SAGD
performance. Given the water use and emissions of carbon dioxide from SAGD operations, it is
imperative that SAGD wellpairs are optimally positioned to reduce the steam injected per unit oil
volume produced to surface. The results show that SAGD orientation within the point bar is
impacted by the structure and heterogeneity of the point bar. Specifically, the wellpairs oriented
perpendicular to the inclined shale layers within the point bar performed significantly better than
wellpairs oriented parallel to the shale layers. When positioned perpendicular to the inclined
shale layers, the wellpairs cut across the shale layers allowing steam injectivity into the sand
intervals between the shale layers and oil drainage under gravity to the lower production well.
This implies that Athabasca oil sands point bar deposits must be carefully mapped so as to
understand the orientation of the point bar itself to determine the best orientation for SAGD
wellpairs for new development of the resource. Given the importance of oil sands environmental
emissions, the differences in performance, especially cSOR, due to wellpair orientation within
the point bar architecture must be taken into account. At this point, it remains unclear how to
arrange a pad of wells within the point bar to optimize oil recovery and steam-to-oil ratio. This
is examined in the next Chapter.
107
CHAPTER 5:
ORIENTATION OF A PAD OF SAGD WELL PAIRS IN AN
ATHABASCA POINT BAR DEPOSIT AFFECTS PERFORMANCE
5.1 Introduction
This chapter is related to the peer-reviewed publication: 2. Su, Y., Wang, J., and Gates, I.D.
Orientation of a Pad of SAGD Well Pairs in an Athabasca Point Bar Deposit Affects
Performance. Marine and Petroleum Geology 54:37-46, 2014
This study focuses on the a pad operation of Steam-Assisted Gravity Drainage (SAGD) well
pairs in the Lower Cretaceous McMurray Formation in Alberta, one of the largest oil sands
accumulations in the world. The in situ viscosity of the oil within this formation is typically in
the range from 1 to 7 million cP. The key property that enables production is that the viscosity
of the oil phase drops to less than about 10 cP when it is heated to over 200 ºC. During SAGD
operation, steam injected into the oil sands formation through a horizontal well transfers its heat
to oil sand (Gates et al., 2007; Peacock, 2009; Hubbard et al., 2011; Gates, 2011). As the
process evolves, the steam chamber grows both vertically and laterally within the reservoir. As a
result, the viscosity of the bitumen drops and the mobilized oil flows, under the action of gravity,
to the production well positioned below the injection well (Gates et al., 2007). In typical practice,
the separation between injection and production wells is equal to ~5 m and the length of the
injection/production wellpair is typically between 500 and 1,000 m (Gates et al., 2007; Peacock,
2009).
108
The basic depositional unit of the Middle McMurray Formation is the point bar which consists of
inclined heterolithic strata (IHS) of sandwiched sand-shale/siltstone sequences and abandoned
mud channels (Strobl et al., 1997; Fustic, 2007; Fustic et al., 2012; Hubbard et al., 2011;
Labrecque et al., 2011; Musial et al., 2011, Su et al. 2013). Due to the presence of those
shale/siltstone interbeds, many SAGD operations in the McMurray Formation suffer in
performance due to extensive vertical barriers which prevent vertical steam rise and oil drainage.
5.2 Geological Data
Nardin et al. (2013) have shown, from extensive examination of closely spaced core data and
light detection and ranging (LIDAR) images from a McMurray oil sands mine face that IHS mud
layers can explend as far as a few hundred meters in extent. Nardin et al. found that in
moderately to highly bioturbated mudstones, layers are generally greater than 100 m in extent
which implies that lateral growth of steam chambers will be affected by these mud layers.
However, erosion of mud layers creates breaches in the layers that enable steam rise and oil
drainage. They also found that beds associated with clast-associated IHS rock types were on the
order of ten meters in extent and could interfere with steam chamber growth. However, these
smaller in extent layers could serve to help thermal dispersion at a larger length scale that
enhances overall heat transfer into the reservoir (Gotawala and Gates, 2010).
SAGD is the ideal process to develop for a homogeneous reservoir; however, it is widely known
that oil sands are heterogeneous and that the recovery process is adversely impacted by this
lithological heterogeneity (Yang and Butler, 1992; Chen et al., 2008; Gotawala and Gates, 2010).
109
Thus, the specific impact of point bar architecture on steam chamber development can be
pronounced which explains why steam chambers, in some cases, take years to reach the top of
the oil column with large lateral growth (ConocoPhillips, 2012).
Su et al. (2013) demonstrated that the placement and orientation of a single SAGD well pair
affects its performance both in respect to thermal efficiency as measured by the steam-to-oil ratio
(SOR) and its oil production rate. However, it is not yet known how the orientation and
placement of a pad of SAGD well pairs within an oil sand point bar deposit affects individual
well pair and overall pad scale performance. In many instances, oil sands operators have drilled
their well pairs with either East-West or North-South orientation yet this orientation of the well
pairs may have nothing to do with the underlying point bar structure. Here, we have used an
ultra-defined point bar reservoir model consisting of about 85 million cells conditioned to
geological (fluid compositional, logs, core, and seismic) data from an oil sands formation to
examine pad scale SAGD performance. More specifically, we have evaluated the impact of the
placement of a pad of parallel SAGD well pairs within the point bar on overall pad performance.
5.3 Geological Setting
The Lower Cretaceous McMurray Formation is found in the distal part of the Alberta foreland
basin in Northeast Alberta, Canada (Leckie and Smith, 1992; Smith et al., 2009). The research
area of this study is the McMurray Formation in the Long Lake area. As a continuing study, the
model is modified based on a point bar model originally created by Patruyo (2010) and reworked and modified by Su et al. (2013). Because of long time exposure and erosion of
110
underlying Paleozoic carbonates, a regional north to south trending unconformity now exists
under the McMurray Formation as shown in Figure 5.1 (Leckie and Smith, 1992). Oil sands
accumulated during the second stage of foreland basin subsidence in the McMurray Formation of
the Lower Mannville Group (Hubbard et al., 1999). During this period, the sedimentary record
suggests a long-term sea level rise and stratigraphy reveals a transition from fluvial to marine
deposits (Peacock, 2009; Musial et al., 2011; Labrecque et al., 2011) with channels largely
following a paleo-valley that flowed to the north-northwest (Fustic, 2007; Patruyo, 2010; Fustic
et al., 2012). The most significant depositional elements are tidally-influenced fluvial channel
belts and estuarine deposits, including vast point bar deposits (Hubbard et al., 2011; Musial et al.,
2011). Analysis of cyclicity of oil sand logs reveals that oil sand point bar deposits exhibit an
overall upward-fining trend (Labrecque et al., 2011).
Figure 5.1 Generalized stratigraphic column of the Western Canada Sedimentary Basin.
111
The point bar geological model used in this study was developed by Su et al. (2013). For the
construction of the point bar model, 375 vertical wells were used from across 154 km2 in the
Long Lake area of Northeast Alberta. Specifically, core data from 44 wells across the area, logs
from 375 wells including gamma radiation and neutron-density, and interpretations from threedimensional (3D) seismic reflection data were used.
Figure 5.2 Examples of the four facies: A – cross-stratified sands, B – breccia lag – light
material is siltstone in bitumen saturated sand, C – massive to cross stratified very fine to
fine grained sands, and D – massive to bioturbated siltstone with sand interbeds used to
model the point bar (modified from Petruyo, 2010). Core boxes are 75 cm long. E and F
show potential baffles to steam rise and oil drainage – these intervals can be up to several
meters thick.
112
The point bar constructed here consisted of two main units: 1. channel lag and 2. inclined
heterolithic strata (IHS). The argillaceous sands above the point bar deposit were not included in
the point bar model. The lithology observed is divided into four facies (A, B, C, and D), shown
in Figure 5.2. Major elements are Facies C and D, which represent the inclined heterolithic strata
unit. Facies A consists mainly of breccia-dominated sandstone with subangular to subrounded
clasts of diameter ranging from ~3 to 4 mm and it is commonly located in the channel lag.
Bioturbation is insignificant in this rock type and mudstone clasts occupy about 30% of the
facies. The permeability of Facies A lies between about 0.5 and 4 D. Facies B mainly consists
of mudstone clasts with angular to sub-rounded mud rip-up clasts in a matrix of fine to mediumgrained bitumen-saturated sand with up to 0.5% coarser grained sands. The permeability of the
sand in this facies ranges from 0.25 to 1 D. Facies C is largely made up of medium-grained
sandstone and coarse grains with ripple cross-stratified sands and planar laminated sands evident
with low-angle cross stratification also present near the top of the IHS. In this facies, bitumen
saturates most of the sand although some gas-containing sands are found at the top of the IHS
unit capped by the upper McMurray Formation argillaceous sands. Bioturbation is rare, and in
general, the porosity in this facies reduces upsection. The permeability of the sand in this facies
is between 4 and 10 D. Facies D comprises interbedded fine-grained sandstone and siltstone
with bitumen-saturated sands. Massive to planar laminated siltstone intervals are also found in
this facies with many siltstone intervals which are extensively bioturbated. This facies also hosts
local occurrences of soft sediment deformation and mud rip-up clasts. Bioturbation in this facies
increases upsection being more prevalent in siltstones interbedded with sand laminae which
tends to be bitumen stained. The permeability of Facies D tends to be between 3.5 and 8 D. For
completeness of the work described here, the porosity-permeability transforms for the facies.
113
The geological model was built in a geomodeling package (Schlumberger, 2011) – the details of
the geostatistical description are described in previous chapter 4. For the geological model, the
cells are 5 m by 5 m in the horizontal directions and 1.5 m in the vertical direction. In total, there
are 546 cells in the east to west direction, 649 cells in the north to south direction and 238 cells
in vertical direction. Therefore, the total cell count of the geological model is equal to
84,336,252. Figure 5.3 shows the distribution of all four facies in the geological point bar model.
Figure 5.3 Facies distribution in the geological model with mud-filled channel lines (scale
in vertical direction has been exaggerated 5 times). Given the scale of the model (roughly
2.73 km by 3.245 km), shale and breccia lag facies are not visible. The inset pink square
indicates the location of extracted model (dimensions are 1 km by 1 km).
114
5.4 Reservoir Simulation Models
After the geological model was complete, it was imported and converted into a thermal reservoir
simulation model. No upscaling was done to ensure no loss of the resolution of the geological
model. Next, a 1,000 m by 1,000 m model, displayed in Figure 5.3, was extracted from the full
geological model. This domain was chosen since it is large enough to hold 7 to 10 well pairs
each 750 m long. The dimensions of the grid blocks for the extracted model is the same as that of
the geological model, that is, 5 m by 5 m by 1.5 m in the vertical direction. The total number of
gridblocks in the reservoir simulation model is equal to 9,615,438. The porosity, permeability
and water saturation distributions of the extracted model are shown in Figures 5.4, 5.5 and 5.6,
respectively.
Figure 5.4 Porosity distribution of the extracted model (scale in vertical direction has been
exaggerated 2 times).
115
Figure 5.5 Permeability distribution of the extracted model (scale in vertical direction has
been exaggerated 2 times).
Figure 5.6 Water Saturation distribution of the extracted model (scale in vertical direction
has been exaggerated 2 times).
116
To test the effect of pad orientation within the point bar, three separate submodels were
constructed with different well pad orientations within the extracted model from the full
geological model. Each submodel has the following orientations:
Submodel 1
A pad consisting of 9 SAGD well pairs (roughly 100 m apart) oriented in East-to-West direction.
The well pad orientation is orthogonal to the IHS and thus all of 9 wellpairs cross nearly all of
the high permeability regions in the extracted model domain. A view of this submodel is shown
in Figure 5.7.
Figure 5.7 Map view of locations of SAGD well pairs in Submodel 1. Colors indicate
horizontal permeability (in mD) distribution (scale in vertical direction has been
exaggerated 2 times).
117
Submodel 2
A pad of 9 SAGD well pairs (roughly 100 m apart) lying in the North-to-South direction. In this
submodel, the pad orientation is parallel to the strike of the IHS mud drapes. A view of this
submodel is displayed in Figure 5.8.
Figure 5.8 Map view of locations of SAGD well pairs in Submodel 2. Colors indicate
horizontal permeability (in mD) distribution (scale in vertical direction has been
exaggerated 2 times).
Submodel 3
A pad of 7 SAGD well pairs (roughly 100 m apart) positioned so that they lie roughly aligned in
the Northwest-Southeast direction. In this submodel, only 7 well pairs were included due to the
118
size of extracted reservoir simulation model. The well pairs are roughly perpendicular to the
paleo-flow and parallel to the strike of the IHS at the downstream end of the point bar. A view of
this submodel is presented in Figure 5.9.
Figure 5.9 Map view of locations of SAGD well pairs in Submodel 3. Colors indicate
horizontal permeability (in mD) distribution (scale in vertical direction has been
exaggerated 2 times).
Since breccia-dominated sandstone is located at the base of the submodel, the thickness of this
point bar deposit is between about 30 and 40 m. The production wells in each submodel are
located 2 m above the boundary between the basal layer and the IHS and the injection wells are
positioned 5 m above the production wells.
119
Table 5.1 summarizes the fluid, rock/fluid properties, and other properties used in the reservoir
models. The bitumen viscosity, oil/water relative permeability curve endpoints, K-values, and
other reservoir properties are typical of that used for Athabasca oil sands deposits.
Table 5.1 Reservoir simulation model input parameters.
Item
Value
Well length, m
Separation between injector and producer, m
Reservoir thickness, m
Initial Reservoir Temperature, C
Initial Reservoir Pressure at top of model, kPa
Depth of top of model, m
Sorw
Swc for Facies A
Swc for Facies B
Swc for Facies C
Swc for Facies D
Sorg
Sgc
krwro
krocw
krogc
krg(Sorg)
Three phase relative permeability model (CMG, 2010)
Rock and overburden/understrata heat capacity, kJ/m3C
(Butler, 1997)
Rock, overburden, understrata thermal conductivity, kJ/m
dayC (Butler, 1997)
Bitumen thermal conductivity, kJ/m dayC (Butler, 1997)
Solution Gas to Oil Ratio, m3/m3
kv 4
kv1 T  k v 5
e
P
Methane K-value correlation, K-value =
(CMG,
2011)
Bitumen viscosity correlation (Mehrotra and Svrcek, 1986)
ln ln µ (cP) = A+B ln T(K)
120
750
5
~30
10
2,300
282
0.25
0.3
0.5
0.2
0.4
0.005
0.005
0.1
0.992
0.834
1
Stone Model 2
2,600
660
11.5
5
kv1= 5.45x105 kPa
kv4= 879.84C
kv5 = 265.99C
A=22.8515
B = -3.5784
5.5 Results and Discussion
Figure 5.10 to 5.12 displays cumulative steam-to-oil ratio (cSOR, steam expressed as cold water
equivalent, CWE), daily oil production rate, steam injection rate (CWE) and cumulative oil
production profiles for all of the well pairs in the three submodels. The results reveal that there
is significant variability of well pair performance in each of the submodels. The cSORs for
Submodel 1 (well pairs oriented West-East in the extracted model) tend to range between 6 and
12 m3/m3 over the majority of the operation. For Submodel 2 (well pairs directed North-South
the extracted model), the cSORs range higher than 20 m3/m3 although several of the well pairs
achieve relatively low and nearly uniform cSORs near 5 m3/m3. Submodel 3, with the exception
of a single well pair, achieve similar cSOR profiles to that of Submodel 1. Although the
performance of the well pairs with respect to cSOR are relatively poor compared to overall
industry performance (average for SAGD in Alberta Canada in the McMurray Formation tends
to be equal to about 3.6 m3/m3), the key here is to interpret the results as indices of performance
that depend on the orientation of the pad model. The results suggest, from a cSOR standpoint,
that the horizontal wells oriented strike-parallel in IHS packages (Submodel 2) yield the poorest
results compared to the other two well pair arrangements. These results are similar to the
findings reported by Su et al. (2013) which showed that a single well pair aligned strike-parallel
with the IHS performed worse than single wellpairs that were positioned orthogonal to the IHS
shale layers.
121
Figure 5.10. Production profiles for each the well pairs in Submodel 1. For top two plots,
left to right, cumulative steam-to-oil ratio (cSOR) and daily oil production rates. For
bottom two plots, left to right, steam injection rate (CWE) and cumulative oil production.
Figure 5.11. Production profiles for each the well pairs in Submodel 2. For top two plots,
left to right, cumulative steam-to-oil ratio (cSOR) and daily oil production rates. For
bottom two plots, left to right, steam injection rate (CWE) and cumulative oil production.
122
Figure 5.12. Production profiles for each the well pairs in Submodel 3. For top two plots,
left to right, cumulative steam-to-oil ratio (cSOR) and daily oil production rates. For
bottom two plots, left to right, steam injection rate (CWE) and cumulative oil production.
The oil production rates displayed in Figure 5.10 to 5.12 reveal that there is significant
variability, especially in Submodel 2, among the well pairs within each submodel. In Submodel
2, the oil production rates range from about 10 to 120 m3/day. The variability of the oil
production rates for Submodels 1 and 3 are lower than that of Submodel 2 being between 30 to
90 m3/day and 20 to 100 m3/day, respectively.
Figure 5.13a and b displays the cSOR and the cumulative volume of oil produced, normalized to
an individual well pair, of the submodels, respectively. The results show that the overall cSOR
of the pad well pair arrangements are similar despite the variability displayed in Figure 5.10-5.12.
123
In general, with respect to pad-scale cSOR, Submodels 1 and 2 outperform Submodel 3.
However, Figure 5.13b shows that the pad with the largest volume of oil produced is Submodel 3.
Submodels 1 and 2 exhibit very similar total volumes of oil produced despite the variability of
the oil rates presented in Figure 5.10 and 5.12.
(a) Submodel cSOR profiles versus time
(b) Submodel average cumulative oil produced normalized per well pair
Figure 5.13 (a) Average cumulative steam-to-oil ratio and (b) average cumulative volume
of oil produced for each submodel normalized to a single well pair (Submodels 1 and 2
consist of 9 well pairs whereas Submodel 3 has 7 well pairs).
124
Given the small difference of the cSOR profiles, the results suggest that the well pair
configuration that performs the best is that of Submodel 3 since it produced roughly 20,000 m 3
more oil per well pair over the 6 years of operation. All of the well pairs in Submodel 3 are
roughly orthogonal to the IHS shale layers and thus, similar to the findings reported by Su et al.
(2013), the orientations that cut across the shale layers perform the best.
Figures 5.14, 5.15, and 5.16 display three-dimensional views of the evolution of the steam
chambers, as indicated by the 200C temperature isosurface, in Submodels 1, 2, and 3,
respectively, after 1, 2, 4, and 6 years of operation. Because Submodel 1 has well pairs that cut
across the IHS shale layers, steam readily spreads in the cross-well pair directions. However, for
Submodel 2, steam spreads faster along the length of the wells rather in the cross-well pair
direction.
Figure 5.14 Temperature isosurface (at 200C) for well pairs in Submodel 1 at 1, 2, 4, and
6 years. Colors on domain are oil saturation.
125
Figure 5.15 Temperature isosurface (at 200C) for well pairs in Submodel 2 at 1, 2, 4, and
6 years. Colors on domain are oil saturation.
Figure 5.16 Temperature isosurface (at 200C) for well pairs in Submodel 3 at 1, 2, 4, and
6 years. Colors on domain are oil saturation.
126
The results suggest that the steam chambers over the first 2 years operation are better connected
between most of wellpairs in Submodel 1 over that of Submodel 2. Submodel 3’s steam
conformance, in early years, is similar to that of Submodel 1. This is because the well pairs in
Submodel 3 also cut across the IHS shale layers. Beyond 4 years, the steam chambers in all of
the well pair configurations are well connected. The results reveal that the heterogeneity of the
steam chambers is directly linked to the heterogeneity of the reservoir and that the growth of the
steam chambers, especially at the early stages of the recovery process, are aligned along the IHS
shale layers.
The early results of the steam chambers are similar to the extents of steam
chambers determined from interpretations of 4D seismic data of existing SAGD operations
(ConocoPhillips, 2012); the ones from the simulations have “cold” spots along the well pairs and
the steam chambers exhibit heterogeneity with respect to their shape.
5.6 Final Remarks
The effect of the orientation of a pad of Steam-Assisted Gravity Drainage (SAGD) well pairs in
an oil sands point bar on their performance has been evaluated by using a detailed reservoir
simulation model of a McMurray Formation oil sands reservoir conditioned to core, log, and
seismic data from Su et al., (2014). The conclusions are as follows:
1. The results reveal that the performance of the pad depends on well pair orientation and
that horizontal well pairs that are arranged to cut across the inclined heterolithic stratified
shale layers of the point bar perform better than well pairs aligned along the strike
direction of the shale layers.
127
2. The heterogeneity of steam chambers surrounding the SAGD well pairs is directly linked
to the heterogeneity of the point bar.
3. There is large variability of the performance of the well pairs within the pad itself. Thus,
it is not possible to use a single well pair to gauge the performance of the process within
an oil sands point bar deposit. That is, pad scale models are required for recovery process
design.
128
CHAPTER 6: SAGD PAD PERFORMANCE ON POINT BAR DEPOSIT WITH A
THICK SANDY BASE
6.1 Introduction
Su et al. (2013) demonstrated that the placement and orientation of a single SAGD well pair in a
point bar affects its performance both respect to thermal efficiency as measured by the steam-tooil ratio and its oil production rate. Later, Su et al. (2014) described the performance of a SAGD
pad of well pairs within a point bar deposit. However, oil sand reservoirs are complex and
exhibit point bars as well as blocky sandy zones. Here we combined a single point bar model
with a relatively clean sand deposit below and placed a SAGD pad of wellpairs in the blocky
sandy zone to understand how the orientation and placement of a pad of SAGD well pairs affect
individual well pair and overall pad scale performance. In many instances, oil sands operators
have drilled their well pairs with either East-West or North-South orientation yet this orientation
of the well pairs may have nothing to do with the overlying point bar structure. Here, we have
used an ultra-defined point bar plus sandy base interval reservoir model consisting of about ~96
million cells conditioned to geological (fluid compositional, logs, core, and seismic) data from an
oil sands formation to examine pad scale SAGD performance. More specifically, we have
evaluated the impact of the placement of a pad of parallel SAGD well pairs within the
combination of point bar and clean sand reservoir on overall pad performance.
SAGD is the ideal process for the ideal reservoir; however, it is widely known that oil sands are
heterogeneous and that the recovery process is adversely impacted by this lithological
129
heterogeneity (Yang and Butler, 1992; Chen et al., 2008; Gotawala and Gates, 2010). Thus, the
specific impact of point bar architecture on steam chamber development can be pronounced
which explains why steam chambers, in some cases, take years to reach the top of the oil column
with large lateral growth (ConocoPhillips, 2012).
6.2 Methodology
The Lower Cretaceous McMurray Formation is found in the distal part of the Alberta foreland
basin in Northeast Alberta, Canada (Leckie and Smith, 1992; Smith et al., 2009). As an ongoing
study, the model is modified based on a point bar model originally created by Patruyo (2010) and
re-worked and modified by Su et al. (2013). The most significant depositional elements that
resulted from combined marine and non-marine deposits are tidally-influenced fluvial channel
belts and estuarine deposits in the form of point bar deposits (Hubbard et al., 2011; Musial et al.,
2011). Analysis of cyclicity of oil sand logs reveals that point bar deposits exhibit an overall
upward-fining trend (Labrecque et al. 2011).
The point bar geological model used in this study was developed by Su et al. (2013). To be more
specific, core data from 44 wells across the area, logs from 375 wells with gamma radiation and
neutron and density log measurements, and interpretations from three-dimensional (3D) seismic
reflection data were used. The geological model was built in a commercial geological modeling
package (Schlumberger, 2011) – the details of the geostatistical description are presented in
chapter 4 and will not be repeated here. The lithology observed is divided into four facies (A, B,
C, and D). For the geological model, the cells are 5 m by 5 m in the horizontal directions and 1.5
m in the vertical direction.
130
The clean sand geological model was constructed by adding a 20 m thick unit based on typical
Athabasca reservoir properties, such as porosity, permeability and oil saturation (Carrigy, 1966).
The clean sand body is positioned directly under the point bar model to form, in its union, a
geological model consisting of a upper point bar deposit sitting atop a clean sandy zone. In the
clean sand zone, the cells are remaining 5 m by 5 m in horizontal directions and 1.5 m in vertical
direction. In total, there are about 96 million cells in the geological model.
The Firebag pilot project, operated by Suncor Energy, located at Northeast Alberta consists of
several pads of SAGD wellpairs producing from the McMurray oil sand formation. Core sample
#26 correlated with type well log confirmed the presence of point bar deposits underlying
massive fluvial channel sands as shown in Figure 6.1 within which the SAGD well pairs are
located. The average reservoir properties of this project are as follows: continuous pay zone
about 38.9 m thick, porosity 32.1%, oil saturation 85%, and effective horizontal permeability
about 3 to 4 Darcy (Suncor, 2015). Figure 6.2 displays a high quality 4D seismic survey which
has been interpreted to indicate the steam chamber thickness. The results show that the steam
chamber has ascended by up to 54 m after 9 years of SAGD operation in Pad 102N. In total, 18
SAGD well pairs are currently on production, including infill wells, with a cumulative SOR
value equal to 3.18 m3/m3 with 36% recovery factor. A mud layer running across the north part
of Pad 102 leads the steam conformance to be varied and causes performance issues. Infills
located in between the producers shows different level of interference effect within the pad and
in general have improved the recovery performance and lowered the overall cSOR. With infill
wells started in 2011, the oil rate now increased ~40% of the original oil production rate at the
end of 2011 and the instantaneous SOR value has reached as low as 2.7 m3/m3.
131
Figure 6.1 Middle McMurray Estuarine Channels and Associated Point Bars at Firebag
pilot (Suncor, 2015). Core sample #26 from 304.35 m to 310.20 m.
Figure 6.2 4D seismic survey for Pad 102 from Suncor Firebag pilot (Suncor, 2015)
132
6.3 Reservoir Simulation Models
The geological model was imported and converted into a thermal reservoir simulation model.
No upscaling was done to ensure no loss of the resolution of the geological model. Next, a 1,000
m by 1,000 m submodel, displayed in Figure 6.3, was extracted from the full geological model.
This domain was chosen since it is large enough to hold 8 to 10 well pairs each 750 m long. The
dimensions of the grid blocks for the extracted model is the same as that of the geological model,
that is, 5 m by 5 m by 1.5 m in the vertical direction. The total number of gridblocks in the
reservoir simulation model is equal to 10,383,057. The porosity, permeability and water
saturation distributions of the new combination model are shown in Figures 6.4, 6.5, and 6.6,
respectively.
Figure 6.3. Facies distribution in the geological model with mud-filled channel lines (scale
in vertical direction has been exaggerated 5 times). Given the scale of the model (roughly
2.73 km by 3.245 km), shale and breccia lag facies are not visible. The pink square
indicates the location of extracted model (dimensions are 1 km by 1 km).
133
Figure 6.4 Porosity distribution of the extracted model (scale in vertical direction has been
exaggerated 5 times). The bottom 30 m is the basal sand zone (shown in top image) and the
upper 20 m are the IHS interval.
134
Figure 6.5 Permeability distribution of the extracted model (scale in vertical direction has
been exaggerated 5 times). The bottom 30 m is the basal sand zone (shown in top image)
and the upper 20 m are the IHS interval.
135
Figure 6.6 Water Saturation distribution of the extracted model (scale in vertical direction
has been exaggerated 5 times). The bottom 30 m is the basal sand zone (shown in top
image) and the upper 20 m are the IHS interval.
136
To test the effect of pad orientation within the point bar, four separate submodels were
constructed with different well pad orientations within the combination model. Each submodel
has the following orientations:
Submodel 1: A pad consisting of 9 SAGD well pairs oriented in East-to-West direction. The
well pad orientation is orthogonal to the IHS and thus all of 9 wellpairs cross
nearly all of the high permeability regions in the based extracted model domain. A
view of this submodel is shown in Figure 6.7.
Figure 6.7 Locations of SAGD well pairs in Submodel 1. Colors indicate the horizontal
permeability (in mD) distribution
137
Submodel 2: A pad of 9 SAGD well pairs lying in the North-to-South direction. In this
submodel, the pad orientation is parallel to the direction to the IHS mud drapes. A
view of this submodel is displayed in Figure 6.8.
Figure 6.8 Locations of SAGD well pairs in Submodel 2. Colors indicate the horizontal
permeability (in mD) distribution.
Submodel 3: A pad of 7 SAGD well pairs (roughly 100 m apart) aligned in the NorthwestSoutheast direction. In this submodel, only 7 well pairs were included due to the
size of extracted reservoir simulation model.
The well pairs are roughly
perpendicular to the paleo-flow and parallel to the strike of the IHS at the
138
downstream end of the point bar. A view of this submodel is presented in Figure
6.9.
Figure 6.9 Locations of SAGD well pairs in Submodel 3. Colors indicate the horizontal
permeability (in mD) distribution.
Submodel 4: A pad of 7 SAGD well pairs positioned in the Northeast-Southwest direction. Like
Submodel 3, only 7 well pairs were included due to the size of extracted reservoir
simulation model. The well pairs are roughly parallel to the paleo-flow. A view of
this submodel is presented in Figure 6.10.
139
Figure 6.10 Locations of SAGD well pairs in Submodel 4. Colors indicate the horizontal
permeability (in mD) distribution.
Since the clean sand base is added under the point bar model, the total thickness of the system is
about 50 m. The production wells for each wellpair in each submodel are located 2 m above the
base of oil column and the injection wells are positioned 5 m above the production wells. Table
6.1 listed the average reservoir properties of each geological body in this combination model.
Table 6.1 Reservoir simulation model properties for each geological body.
Item
Point Bar
Sandy Base
Reservoir thickness, m
Porosity, %
Permeability, mD
Oil Saturation
Original Oil In Place (OOIP), sm3
30
0.3
4800
0.5
5,280,000
20
0.35
5530
0.65
4,840,000
140
6.3.1 Well Constraints and Model Initialization
During SAGD operation, the operating constraint prescribed for the injection wells is the
maximum steam injection pressure which is set equal to 3,500 kPa with 90% steam quality. For
the production wells, the steam rate (expressed at surface conditions, cold water equivalent) is
constrained equal to 1 m3/day during SAGD operation. This constraint mimics steam trap
control.
Prior to SAGD operation, four months steam circulation was modeled by using
temporary heater wells positioned in the locations of both injection and production wells. To
deal with pressure buildup associated with thermal expansion of the fluids near the well bore,
temporary production wells were also placed in the locations of the injection wells in this time
period with bottom hole pressure is constrained equal to the initial reservoir pressure at the well
depths. (Gates et al., 2007). After the steam circulation period, the temporary heaters were
turned off and the temporary production wells in the location of the injection wells were
removed. Thereafter, the pad entered SAGD operation: steam was injected into the injection
wells and fluid was produced from the production wells.
Table 6.2 summarizes the fluid, rock/fluid properties, and other properties used in the reservoir
models. The bitumen viscosity, oil/water relative permeability curve endpoints, K-values, and
other reservoir properties are typical of that used for Athabasca oil sands deposits.
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Table 6.2 Reservoir simulation model input parameters.
Item
Value
Well length, m
Separation between injector and producer, m
Reservoir thickness, m
Initial Reservoir Temperature, C
Initial Reservoir Pressure at top of model, kPa
Depth of top of model, m
Sorw
Swc for Facies A
Swc for Facies B
Swc for Facies C
Swc for Facies D
Sorg
Sgc
krwro
krocw
krogc
krg(Sorg)
Three phase relative permeability model (CMG, 2010)
750
5
~50
10
2,300
282
0.25
0.3
0.5
0.2
0.4
0.005
0.005
0.1
0.992
0.834
1
Stone Model 2
Rock and overburden/understrata heat capacity, kJ/m3C
(Butler, 1997)
2,600
Rock, overburden, understrata thermal conductivity, kJ/m
dayC (Butler, 1997)
660
Bitumen thermal conductivity, kJ/m dayC (Butler, 1997)
Solution Gas to Oil Ratio, m3/m3
kv 4
Methane K-value correlation, K-value =
(CMG, 2011)
kv1 T  k v 5
e
P
Bitumen viscosity correlation (Mehrotra and Svrcek, 1986)
ln ln µ (cP) = A+B ln T(K)
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11.5
5
kv1= 5.45x105 kPa
kv4= 879.84C
kv5 = 265.99C
A=22.8515
B = -3.5784
6.4 Results and Discussion
Figure 6.11 displays the cumulative steam-to-oil ratio (cSOR, steam expressed as cold water
equivalent) for all of the well pairs in the four submodels. The results reveal that there is
significant variability among the well pairs in each of the submodels. The cSORs for Submodel
1 (well pairs oriented in the horizontal direction in the extracted model) tend to range between
4.5 and 5.5 m3/m3 over the majority of the operation and are the least variable of the submodel
results. For Submodel 2 (well pairs directed in the vertical direction in the extracted model), the
cSORs range from just under 4 to slightly above 7 m3/m3 although several of the well pairs
achieve nearly uniform cSORs near 4 m3/m3. The cSORs of the well pairs in Submodel 3 are
between 3.5 and 6 m3/m3. Similar to Submodel 2, the cSOR values for the well pairs in
Submodel 4 have large variability ranging from about 3 to nearly 8 m3/m3. This submodel
exhibits the greatest variability of the cSORs. An examination of the results reveal that the well
pairs in Submodel 2 are the nearest to aligning with the IHS of the point bar after 2 years SAGD
operation. These results for each well pair are similar to the findings reported by Su et al. (2013)
which showed that a single well pair aligned with the IHS performed worse than single wellpairs
that were positioned orthogonal to the IHS shale layers. Although the performance of the well
pairs with respect to cSOR are close to overall industry performance (average for SAGD in
Alberta Canada in the McMurray Formation tends to be equal to about 3.6 m3/m3), the key here
is to interpret the results as indexers of performance that depend on the orientation of the pad
model. According the previous study (Su et al., 2014) on pad performance when the well pairs
are placed in the IHS interval, the best SAGD performance is achieved with well orientation the
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same as Submodel 1. The results show that despite having a basal sand zone that has much less
heterogeneity relative to the IHS interval, the performances of the well pairs are highly variable.
Figure 6.11 Cumulative steam-to-oil ratio for each SAGD well pair in each submodel.
Figure 6.12 displays the cumulative produced water-to-steam (CWE) injected ratio (cWSR).
Most of the well pairs exhibit a similar overall trend where the cWSR is below 1 m 3/m3 for the
early part of the operation and then exceeds 1 m3/m3 towards the later part of the operation.
When the cWSR is lower than 1, this means that the amount of produced water is smaller than
the CWE steam injected into the formation. The results show that in the early parts of the
operation, most well pairs are producing significantly less water than is injected into the
144
formation. By the end of the operation, nearly all of the well pairs have produced more water
than was injected into the formation. The most variable cWSRs was obtained in Submodel 2
followed by Submodel 3. Submodels 1 and 4 obtained the least variable cWSRs.
Figure 6.12 Cumulative produced water to injected steam (as CWE) ratio for each SAGD
well pair in each submodel.
Figure 6.13 shows the steam injection rate profiles for the well pairs in each submodel. The
results show that the steam injection rates are variable mostly over the last few years of the
operations. All show a general trend where the injection rates are relatively low at the start of
the process and then rise and peak at between 1,500 and 2,000 days for most of the well pairs.
The oil rates for the well pairs for all of the submodels are presented in Figure 6.14.
145
Figure 6.13 Steam (CWE) injection rates for each SAGD well pair in each submodel.
Figure 6.14 Cumulative produced oil rates for each SAGD well pair in each submodel.
146
For most of the well pairs, the rates are not uniform but exhibit growth for most of the operating
period with a plateau towards the final year simulated. The early growth of the oil production
rate arises from the growth of the chamber through the basal sand zone and the plateau reflects
the continuous drainage that occurs from the IHS interval above basal sand zone. The results
also reveal that over the first few years that for some orientations, e.g. Submodels 1 and 3, the
variability of the oil rates are relatively low whereas in Submodels 2 and 4, the variability is
larger. This suggests that despite the lower heterogeneity of the basal sand zone, well pair
orientation has some impact in this zone as well. After 5 years of SAGD operation, the oil
production rates range from about 100 to 250 m3/day in Submodel 2, from 100 to 320 m3/day for
Submodel 4, and between 200 and 260 m3/day for Submodels 1 and 3. The water production
rates are plotted in Figure 6.15. The results show variability of the water production rates
although the variability of the water rates is smaller than that of the steam injection rates.
Figure 6.15 Cumulative produced water rates for each SAGD well pair in each submodel.
147
Figure 6.16 (a) presents the total volumes of steam (as CWE) injected into the reservoir. The
results show that Submodels 3 and 4 injected less steam compare to Submodels 1 and 2 – this is
due to the lower number of well pairs in these models. Figure 6.16(b) shows that Submodel 1
produced more oil compared to that of Submodel 2.
Since the major contribution to oil
production is from the basal sand zone where the geology is relatively clean, the difference of oil
production is due to the point bar part which is significantly affected by well pair orientation. In
Figure 6.16(b), Submodels 1 and 2 have similar total volumes of oil produced whereas
Submodels 3 and 4 exhibit similar total volumes of oil produced despite the variability of the oil
rates presented in Figure 6.14. All of the well pairs in Submodel 1 and 3 are roughly orthogonal
to the IHS shale layers and thus, similar to the findings reported by Su et al. (2013), the
orientations that cut across the shale layers perform the best. Figure 6.16(c) displays the padscale cSORs. The results show that two trends emerge from the results – Submodels 1 and 2
have a relatively high cSOR profile whereas Submodels 3 and 4 have a relatively low cSOR
profile.
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(a) Submodel average cumulative steam injected
(b) Submodel average cumulative oil produced
149
(c) Submodel cSOR profiles versus time
Figure 6.16 (a) Cumulative volume of steam injected (CWE), (b) average cumulative
volume of oil produced, and (c) average cumulative steam-to-oil ratio for each submodel
(Submodels 1 and 2 consist of 9 well pairs; Submodels 3 and 4 consist of 7 well pairs).
Figure 6.17 displays a cross-section along the fourth well pair in Submodel 1. A comparison of
the permeability distribution and the steam chambers reveal that the after the chamber has
reached the top of the basal sand zone, it ‘fingers’ into the IHS interval above and is limited in
vertical growth for shale layers that are extensive. For shale layers with breaches in them, the
steam chamber rises through the IHS although this can lead to steam ‘chimneys’. After Year 4,
the majority of the IHS is now occupied by steam with a few ‘cold’ spots persisting.
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Figure 6.17 Temperature profile for well pairs 6 in Submodel 1 at 1, 2, 4, and 6 years (scale
in vertical direction has been exaggerated 3 times).
Figures 6.18 to 6.21 display a 3D visualization of the steam chambers marked by a 200C
temperature isosurface. The top two images show the steam chambers at Years 1 and 2 with the
IHS interval removed from the view. The images reveal that even in the basal sand zone, the
steam chambers grow heterogeneously within the formation.
With more time, the steam
chambers eventually penetrate the IHS although ‘cold’ spots arise within the IHS interval leading
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to heterogeneous chambers within the reservoir. As shown in Figure 6.18 for Submodel 1, the
steam chamber conformance along the well pairs after 4 years of operation are much more
improved with steam chambers along most of length of the well pairs. After six years of
operation, the chambers extend over much of the pad area, however, there remain parts of the
reservoir where the steam chambers have not reached.
Figure 6.18 Temperature isosurface (at 200C) for well pairs in Submodel 1 at 1, 2, 4, and
6 years. Colours on domain are oil saturation (scale in vertical direction has been
exaggerated 2 times).
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Figure 6.19 shows the evolution of the steam chambers in Submodel 2. The results show that the
chambers through the basal sand zone achieve better steam conformance than that observed in
Submodel 1. However, when the steam chamber penetrates the IHS interval, the heterogeneity
of the chambers is more evident.
Figure 6.19 Temperature isosurface (at 200C) for well pairs in Submodel 2 at 1, 2, 4, and
6 years. Colours on domain are oil saturation (scale in vertical direction has been
exaggerated 2 times).
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The evolution of the steam chambers for Submodels 3 and 4, displayed in Figures 6.20 and 6.21,
exhibit similar results to those of the other models. However, steam conformance in Model 3
appears to be the best of the four submodels after Year 2 within the basal sand zone but the
impact of the IHS interval on chamber growth is evident.
Figure 6.20 Temperature isosurface (at 200C) for well pairs in Submodel 3 at 1, 2, 4, and
6 years. Colours on domain are oil saturation (scale in vertical direction has been
exaggerated 2 times).
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Figure 6.21 Temperature isosurface (at 200C) for well pairs in Submodel 4 at 1, 2, 4, and
6 years. Colours on domain are oil saturation (scale in vertical direction has been
exaggerate
Since Submodels 1 and 3 have well pairs that cut across the IHS shale layers, the results show
that steam readily spreads in the cross-well pair directions. However, for Submodels 2 and 4, the
steam spreads faster along the length of the wells rather in the cross-well pair direction. The
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results reveal that the heterogeneity of the steam chambers is directly linked to the heterogeneity
of the reservoir and that the growth of the steam chambers, especially at the early stages of the
recovery process, are aligned along the IHS shale layers.
The early results of the steam
chambers are similar to the extents of steam chambers determined from interpretations of 4D
seismic data of existing SAGD operations (ConocoPhillips, 2012); the ones from the simulations
have cold spots along the well pairs and the steam chambers exhibit heterogeneity.
According to the Underground Test Facility (UTF) project Phase B pilot started in 1993
(O’Rourke et al., 1997), three Phase B well pairs produced 2,400,000 barrels of bitumen and
recovery was equal to about 55% of the original bitumen in place (OBIP) by March 1997. From
sedimentological and reservoir perspectives, the Phase B reservoir is classified into three major
flow units: 1. cross-bedded sand at the bottom of reservoir; 2. transition zone in the middle; and
3. IHS at the top of reservoir. The large number of observation wells over the Phase B plant
provided temperature observations within these reservoir units. The results show that the steam
rise rate could be as much as 8 cm/day in the bottom high permeability cross-bedded sand zone
and considerably lower in the top relatively low permeability IHS zone. Strobl (2011) also
indicated that the mudstone-dominated IHS zone can negatively affect SAGD operation.
Temperature data from the observation wells confirms that a 70 cm thick IHS bed acted as a
barrier to steam rise over the 9 year SAGD operation life. The results of the thermocouple data
also show that as the injector penetrated and cut across the IHS bed (near a vertical observation
well so that the temperature distribution could be observed), the steam chamber was able to raise
an additional 4 m to a similar IHS zone (Strobl, 2013).
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6.5 Final Remarks
The effect of the orientation of a pad of Steam-Assisted Gravity Drainage (SAGD) well pairs in
an oil sands reservoir comprising a 30 m thick basal sand zone and a 20 m thick inclined
heterolithic strata interval directly above the sand zone has been evaluated by using a detailed
reservoir simulation model of a McMurray Formation oil sands reservoir. The reservoir model
was based on a detailed geological model conditioned to core, log, and seismic data. The results
reveal that the performance of the pad depends on well pair orientation and that well pairs that
are arranged to cut across the inclined heterolithic stratified shale layers of the point bar perform
better than well pairs aligned with the shale layers. There is less effect of well pair orientation
on the performance in the clean sand base model.
The heterogeneity of steam chambers
surrounding the SAGD well pairs is directly linked to the heterogeneity of the point bar. The
results also show that there is large variability of the performance of the well pairs within the pad
itself after the steam chamber reaches the overlying point bar part. Thus, it is not possible to use
a single well pair to gauge the performance of the process within an oil sands reservoir. That is,
pad scale models are required for recovery process design and forecasting.
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CHAPTER 7: IMPACT OF FLOW CONTROL DEVICES ON SAGD PERFORMANCE
FROM LESS HETEROGENEOUS TO STRONGLY HETEROGENEOUS RESERVOIRS
7.1 Introduction
SAGD is the ideal process for the ideal reservoir. However, it is widely known that oil sands are
strongly heterogeneous and that the recovery process is adversely impacted by this lithological
heterogeneity (Yang and Butler, 1992; Chen et al., 2008; Gotawala and Gates, 2010; Su et al.
2013; Su et al. 2014). In this Chapter, an examination of well completion designs is made to
improve steam conformance and the steam-to-oil ratio of the process.
For many years, SAGD operators in Alberta, Canada have attempted to improve steam
conformance along well pairs by altering the completion design. The thought behind these
efforts is that by altering the points at which steam is injected into the reservoir, this would help
to prevent the formation of ‘cold’ spots along well pairs. At this point, it remains unclear on how
to design these completions and where to place in-well devices to help target regions of the
reservoir that remain ‘cold’ during steam injection. Typically, given the length of SAGD well
pairs, as shown in earlier Chapters, the well pair will intersect regions of the reservoir that have
high permeability and oil saturation and regions with low permeability and potentially relatively
low oil saturation. Steam, with its low viscosity, typically of the order of micropoise, has
relatively high mobility compared to the other phases in the reservoir can readily flow through
most of the sand-filled regions but will be prevented from flowing into the reservoir by shale and
mud layers. Also, since the growth of the steam chamber is controlled by oil drainage, if no oil
can drain from a region, even if heated, then the steam chamber does not occupy the region. The
158
option to control where steam is injected into and where fluids are produced from the formation
permits greater capability to improve the conformance of steam within the reservoir but it is not
clear whether these injection or production points should be positioned at either the high
permeability intervals or the low permeability intervals along the well pair. At this point,
industry has been trying two main methods for controlled point injection and production along
well pairs but no one at this point has determined where it is optimal to place these points along
the well pair. This is the subject of this Chapter.
7.2 SAGD Completion Designs
The Athabasca oil sands deposit consists mainly of unconsolidated sands that with sand grains
between 20 and 200 microns (Bennion et al. 2008). There are also clay particles that have sizes
of order of a few microns (Bennion et al. 2008). In early days of production from SAGD
reservoirs, it became clear that sand production was an issue that led to sanding of wells (filling
of the wells with sand to the point the well production rates were too low to be economic),
erosion of wells and surface facilities, and excess production of sand to surface (Tronvoll et al.
2004; Forsyth et. al. 2008). Thus, well completion designs were altered to prevent sand
production. This led to the use of slotted liners; an example is shown in Figure 7.1.
Slotted liners are simply pipes with slots, typically between 50 microns to a few millimeters in
width and several inches long, cut into them parallel to the longitudinal axis of the pipe. Since
the open area of the slots relative to the external area of the well is small, slotted liners are
159
structurally strong and they have become the preferred completion design for SAGD operations
(Bennion et al. 2008). The geometry of the slot can be altered after it is cut into the well by
rolling the outer surface of the pipe. This slightly closes the outer part of the slot (referred to as a
keystone slot) which has been shown to help prevent sand production.
Figure 7.1 Slotted liner configuration (RGL 2014).
In typical practice, both the injection and production wells consist of slotted liners from the heel
to the toe of the wells and steam is injected into the heel of the injection well and fluids are
produced from the heel of the production well (the pump is landed at the heel of the well). The
literature reveals that despite the use of slotted liners within the SAGD industry, there is nearly
no research on how liner size, slot shape design, and slot spacing affects SAGD performance.
160
One thing that is clear, however, is that ideal steam conformance does not occur with slotted
liners. This is because of the heterogeneity of the formation – uniform openings along the well
in the form of slots coupled with geological heterogeneity along the wells leads to non-uniform
flows both from the injection well and into the production well.
Two general approaches for controlling steam injection points have been adopted by industry to
deal with in and out-flow non-uniformities along the wells. The first is that of multiple tubing
strings, in most cases, two tubing strings, within slotted liners. The second is via the use of
passive flow control devices that are positioned along the well pairs with the remainder of the
wellbeing blanked off (closed pipe).
Dual-tubing string designs have been tested in both injection and production wells (Li et al.,
2011; Stalder, 2012; ConocoPhillips, 2013). In these systems, tubing strings deliver steam to the
point at which the tubing string is terminated within the well. For example, if the tubing string is
place with its end at the toe of the well, then steam is injected at that point into the well. Figure
7.2 presents an example of dual-tubing design used by Husky at Tucker Lake (Husky, 2010). In
some cases, concentric arrangements are used where a larger tubing string ends at the heel of the
well and the inner smaller tubing string continues along the well and ends at the toe of the well
(Suncor, 2010).
161
Figure 7.2 Dual-tubing string design used by Husky (2010): top image is injection well
whereas bottom one is the production well.
162
In the Devon Jackfish project, Li et al. (2011) described a SAGD operation with lift-gas return
from the injector with continuous injection back down to either the long tubing, short tubing or
the annulus of the well. The results of the field trial showed that it achieved 180 m3/day oil
production after 8 days which rapidly increased to 200 m3/day with less steam injected. This
field trial demonstrated that multiple tubing strings could improve the oil production rate.
Passive flow control devices (FCDs) consist of nozzles or chokes that are placed in the well pipe
to control flow at specific points along the well. Although the first FCD for steam-based
recovery processes in oil sands reservoirs was in the early 1990s, the adoption of these devices in
SAGD wells has only been occurring since about 2012 (designs were tested in cyclic steam
stimulation wells in 2000). Between the FCDs, the wells are closed off and thus the only points
at which the wells interact with the reservoir are at the FCDs. For some designs, the FCDs are
simply chokes – that is, holes within the well design. Some of these design rely on achieving
sonic flow conditions during steam injection (Bacon et al. 2000). In this case, if the steam flows
at sonic conditions, in theory, the flow rate through the choke depends only on the upstream
pressure. This implies that the reservoir pressure does not factor in the flow rate of steam into
the reservoir and thus if the pressure in the well is nearly uniform along its length, then the flow
rate into the reservoir is uniform at each choke. In other designs, specially designed nozzles are
used within the well (Stalder, 2013). Table 8.1 displays several example designs for passive
flow control devices. In some cases, the flow control devices are used together with sand control
technology such as Bacon et al.’s (2000) use of chokes together with wire-wrapped screens.
163
Table 7.1
processes.
Several designs of passive flow control devices for steam-based recovery
US Patent 5,141,054 (Alameddine et al., 1992)
In this design, tubing string
inside the liner supplies
steam. The tubing string
has
a
number
of
perforations
along
its
length of controlled size
that act as chokes.
US Patent 5,826,655 (Snow and O’Connell 1998)
In this design, a limited
number of steam injection
points along a tubing string
act as chokes. Each steam
injection point has a
sacrificial strap opposite
each perforation to prevent
the steam from directly
impinging the production
liner.
164
US Patent 6,158,510 (Bacon et al. 2000)
In this design, a limited
number of spaced apart
holes are made in the base
pipe. Opposite the holes is
a collar that deflects the
steam flow through the
holes into a annular gap
between the base pipe and
a wire-wrap screen that
extends several meters in
length away from the
collar. Steam flows from
within the base pipe
through the holes and
impacts the collars. The
flow is deflected away
from the collars and flows
into the reservoir through
the wire-wrap screens. On
production, the reservoir
fluids will flow through the
wire-wrap screens, and
then converge and flow
through the holes in the
base pipe into the wellbore
to be produced to the
surface.
In this design, the ICD's
resistance to flow depends
on the dimensions of the
installed nozzles (orifice)
or
channels.
This
difference of the flow
resistance can be used to
make the flow more
uniform along the well
pair.
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ConocoPhillips (2013) evaluated the performance of FCDs in both the injection and production
wells of a SAGD well pair at the 102-06 SAGD well pair – this was the first known field
installation of FCDs in both producer and injector of a SAGD wellpair. According to Stalder
(2013), the FCDs enabled a low subcool over most of the completion length for extended periods
of the time. The liners were designed to permit a pressure drop of about 340 kPa in the injection
well with injection rate equal to 550 m3/day (CWE) and pressure drop about 28 kPa in the
production well with an emulsion flow rate of 750 m3/day and 75% water cut. In addition, the
steam-to-oil ratio after 2 years SAGD operation with FCD deployed reached as low as 2.4 m 3/m3
with an increase of the oil production rate by up to 33%. From the observations of the field
operation, he concluded that a FCD-deployed single tubing completion achieved similar or better
steam conformance compared to the standard toe/heel dual tubing injection. In addition, the FCD
completion significantly reduced the tubing size which in turn reduced the size of slotted liner,
intermediate casing, and surface casing. The smaller wellbore size increases the flexibility of
directional drilling and reduces drag making it easier to drill the wells with reduced cost.
Furthermore, it remains unclear where to place the FCDs.
Youngs et al. (2009) performed a reservoir simulation study on inflow control devices (ICDs,
FCDs used in production wells). They looked at the segment configuration to model various
type of ICDs in a multisegment well model. They presented a section on flow scaling in order to
properly model the pressure drop across these parallel flow paths when it was impractical to
model multiple. Guo et al. (2014) evaluated the use of uniformly spaced ICDs in a reservoir
model based on ConocoPhillips Surmont SAGD operation. The results showed that the main
166
function of the ICDs was to lower the amount of steam directly produced from the reservoir (the
goal is to not have steam short circuiting from the injection well to the production well but rather
have it deliver its heat to the edge of the depletion chamber). Thus, the main impact of the ICD
was on limiting steam production and thus improving steam trap control.
With respect to placement of FCDs along the length of the well pair, there are very few studies in
the public literature. Medina (2013), in a reservoir simulation study on a relatively simple oil
sands geological model, suggested that the steam injection rate should be proportional to the pay
zone thickness and this should guide the placement of FCDs in the injection well. In many cases,
the oil column thickness does not significantly vary along the well pairs and thus, this guide does
not provide a meaningful method to place FCDs along the injection wells. Furthermore, this
criterion does not reflect reservoir heterogeneity. Kyanpour and Chen (2013), in a reservoir
simulation study in a simple oil sands model, proposed the use of the oil production potential – a
measure of the relative amount of oil along the well pair – to place FCDs along the injection well.
This is similar to the use of the oil column thickness and does not address the heterogeneity of
the reservoir. None of these two studies took depositional setting into account. Tran et al. (2010)
discussed the use of ICDs in horizontal wells in a South China Sea project. They applied ICD
nozzles in the downhole completion enabling inflow balancing to delay water breakthrough and
reduce water cut later in the production cycle. As the result, the fluid inflow became more
uniform along the production interval of the horizontal wells due to the redistribution of the
downhole pressure caused by the ICDs. Das et al. (2012) examined nozzle based ICDs within a
“smart, level-4” multi-lateral well in the Burgan reservoir, Minagish Field, West Kuwait. They
167
found that the ICDs improved the premature water breakthrough problem and helped to sustain
oil production. Although the studies of ICD from Tran et al (2010) and Das et al. (2012) are not
associated with heavy oil production, the benefit of deploying ICDs was demonstrated.
The literature makes it clear that there is a gap on understanding the role of FCDs in geologically
heterogeneous oil sands reservoirs such as point bar deposits. In this study, we first briefly
review the construction of the refined point bar geological model used here. A submodel was
extracted from the geological point bar model to evaluate the impact of FCDs, placed in either
the injection or production wells or both, on SAGD operation. To compare, a model with
relatively low heterogeneity was also constructed to determine how the degree of heterogeneity
impacted results.
7.3 Reservoir Simulation Model
7.3.1 Geological Setting
The point bar geological model used in this study was developed by Su et al. (2013). Briefly, for
the construction of the point bar model, just over 375 vertical wells were used within an area of
about 154 km2 in the Long Lake area of Northeast Alberta as shown in Figure 7.3. Specifically,
core data from 44 wells across the area, logs from 375 wells with gamma radiation and neutron
and density log measurements, and interpretations from 3D seismic reflection data were used.
168
The core data was analyzed with focus on stratigraphic lithology and structure. The geological
model was built in a commercial geological modeling package (Schlumberger, 2011) – the
details of the geostatistical description are described in Su et al. (2013). For the geological
model, the cells are 5 m by 5 m in the horizontal directions and 1.5m in the vertical direction. In
total, there are 546 cells in the east to west direction, 649 cells in the north to south direction and
238 cells in vertical direction. Therefore, the total cell count of this geological model is
84,336,252.
Figure 7.3 (a) Illustration of wells used for input data for point bar model, (b) plan view
with location of wells used to create the conceptual North-South stratigraphic cross section
A-B-C displayed in (c). The cross-section illustrates channel lag and inclined heterolithic
strata geometries based on well logs.
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7.3.2 Reservoir Simulation Model
The geological model was imported and converted into a thermal reservoir simulation model. No
upscaling was done to ensure no loss of the resolution of the geological models. The 1,000 m by
100 m extracted model was extracted from the full geological model, displayed in Figure 7.4.
Figure 7.4 Facies distribution in the geological model with mud-filled channel lines (scale
in vertical direction has been exaggerated 5 times). Given the scale of the model (roughly
2.73 km by 3.245 km), shale and breccia lag facies are not visible. The red square indicates
the location of extracted model (dimensions are 1000 m by 100 m).
170
The dimensions of the grid blocks for the extracted model is the same as that of the geological
model, that is, 5 m by 5 m by 1.5 m in the vertical direction and the total number of grid blocks
in the model is equal to 958,167. To evaluate the impact of degree of heterogeneity on FCD
performance, a clean sand model was also constructed with the identical grid as that of the
heterogeneous point bar model. The geological models are described as follows:

Point Bar IHS model: This model was extracted directly from the full point bar geological
model. The average water saturation is 0.3 and porosity and permeability correlations were
used for each facies in this model, listed in Table 7.2. A view of this model is shown in
Figure 7.5(b).

Clean Sand Model: This model contains 100% sand representing a low heterogeneity
reservoir. It was constructed by homogenizing the Point Bar IHS model so that the range of
permeability is from 4570 to 7428 mD. The average properties are porosity 0.31,
permeability 6,621 mD, and water saturation 0.3. A view of this model is shown in Figure
7.5(a).
The porosity, permeability and water saturation distributions of the reservoir simulation models
are shown in Figures 7.6 to 7.8. Table 7.3 summarizes the fluid, rock/fluid properties, and other
properties used in the reservoir models. The bitumen viscosity, oil/water relative permeability
curve endpoints, K-values, and other reservoir properties are typical of that used for Athabasca
oil sands deposits.
171
Table 7.2 Porosity versus horizontal permeability (in mD) correlations for each facies.

A (Brecciadominated
sandstone)
B (Mudstone
clasts)
C (Crossstratified sands)
D (Interbedded
sand and
siltstone)
0.05
10.8
17.3
17.5
5.1
0.075
36.2
61
63
24
0.1
85.5
149.2
156.5
71.9
0.125
166.5
298.6
317.1
168.3
0.15
286.9
526.5
564.7
337.4
0.175
454.6
850.4
919.7
607.6
0.2
688.2
1,288.3
1,403.3
1,011.1
0.225
962.5
1,858.4
2,037.1
1,584.7
0.25
1,318.2
2,579.1
2,843.3
2,368.6
0.275
1,752.0
3,469.1
3,844.2
3,407.2
0.3
2,271.5
4,547.3
5,062.8
4,748.4
0.325
2,884.5
5,832.9
6,522.2
6,443.9
0.35
3,598.7
7,345.1
8,246.0
8,549.2
0.375
4,421.6
9,103.2
10,258
11,123
0.4
5,360.9
11,127
12,582
14,228
Figure 7.5 Facies distribution for clean sand model (scale in vertical direction has been
exaggerated 3 times). Gray represents interbeded shale, and color yellow represents sand.
172
Table 7.3 Reservoir simulation model input parameters.
Item
Value
Well length, m
Separation between injector and producer, m
Reservoir thickness, m
Initial Reservoir Temperature, C
Initial Reservoir Pressure of model, kPa
Reference Depth of model, m
Sorw
Swc for Facies A
Swc for Facies B
Swc for Facies C
Swc for Facies D
Sorg
Sgc
krwro
krocw
krogc
krg(Sorg)
750
5
~30
10
2,300
250
0.2
0.3
0.5
0.15
0.4
0.005
0.005
0.1
0.992
0.834
1
Three phase relative permeability model (CMG, 2010)
Stone Model 2
Rock and overburden/understrata heat capacity, kJ/m3C
(Butler, 1997)
2,600
Rock, overburden, understrata thermal conductivity, kJ/m
dayC (Butler, 1997)
660
Bitumen thermal conductivity, kJ/m dayC (Butler, 1997)
11.5
Solution Gas to Oil Ratio, m3/m3
5
kv 4
Methane K-value correlation, K-value =
kv1 T  k v 5
e
P
kv1= 5.45x105 kPa
kv4= 879.84C
(CMG, 2011)
kv5 = 265.99C
Bitumen viscosity correlation (Mehrotra and Svrcek, 1986)
A=22.8515
B = -3.5784
ln ln µ (cP) = A+B ln T(K)
173
Figure 7.6 Porosity distribution of the extracted model (scale in vertical direction has been
exaggerated 3 times).
Figure 7.7 Permeability distribution of the extracted model (scale in vertical direction has
been exaggerated 3 times).
Figure 7.8 Water Saturation distribution of the extracted model (scale in vertical direction
has been exaggerated 3 times).
174
7.4 Well Completions and Model Initialization
The production wells in each simulation models are located 1 m above the base of each model
and the injection wells are positioned 5 m above the production wells. Well pairs are 750 m long
with 8-5/8” casing diameter. The FCD is deployed with 5-1/2” outer diameter matched tubing
size, 0.0005 m2 channel cross-section area for injector, and 0.00005 m2 channel cross-section
area for producer. To test the effect of different well completions with different heterogeneous
level, three general classes of well completion designs are used.
The first well completion strategy is referred to as the base case (BC). In this case, a dual-tubing
design was applied for the injection well and single long tubing string was applied for the
production well. To apply the dual-tubing injector completion, a short tubing string was located
at heel of the well and long tubing string was landed at the toe of the well. The injection
proportions for the short and long tubing strings were set 75% and 25% of the total well injection
rate, respectively.
The second well completion design has FCDs on the injection well only. The production well
uses a single long tubing string. Five or ten FCD nozzles were located at the middle of
uniformly-spaced intervals separated by packers. These cases are referred to as Cases I5 or I10
depending on whether five or ten FCD nozzles are used.
The third well completion strategy is designed to have FCDs on the production well only. The
injection well has the dual-tubing injection design as that in the base case. Five or ten FCD
175
nozzles were positioned at the mid-points of uniformly-spaced intervals separated by packers
along the well. These cases are referred to as Cases P5 or P10 depending on whether five or ten
FCD nozzles are used.
As follow up, three FCD combination designs are applied within the Point Bar IHS model to
evaluate SAGD performance:
1. Five or ten FCDs installed in both injection and production wells with uniformly spaced
intervals. These cases are referred to as I5P10 or I10P5.
These cases have been
summarized in Table 7.4.
2. Five FCDs installed in injection or production wells either in the five lowest permeability
locations or highest permeability locations, shown in Figures 7.9 and 7.10, respectively.
These cases are denoted I5(LP)P5(LP) and I5(HP)P5(HP) and are listed in Table 7.3.
3. Similarly with above design, FCDs installed in both injection and production wells
combined those two different focus. These cases are listed in Table 7.3.
176
Figure 7.9 Well Completion design for 5 FCD nozzles installed focus on lower properties
zone. Reference properties are Permeability, Porosity and Water Saturation. NICD is
another name for FCD.
177
Figure 7.10 Well Completion design for 5 FCD nozzles installed focus on higher properties
zone. Reference properties are Permeability, Porosity and Water Saturation. NICD is
another name for FCD.
178
Table 7.4 Summary of simulation cases. All cases were done for the point bar IHS model
whereas only the first five (BC, I5, I10, P5, P10) were done for the clean sand model.
Case Name
Well Completion
FCD Locations
BC
Dual-tubing in Injector
Single tubing in Producer
-
I5
5 FCDs in Injector
Single tubing in Producer
Uniform
-
I10
10 FCDs in Injector
Single tubing in Producer
Uniform
-
P5
Dual-tubing in Injector
5 FCDs in Producer
Uniform
P10
Dual-tubing in Injector
5 FCDs in Producer
Uniform
I5P10
5 FCDs in Injector
10 FCDs in Producer
Uniform
Uniform
I10P5
10 FCDs in Injector
5 FCDs in Producer
Uniform
Uniform
I5(LP)
5 FCDs in Injector
Single tubing in Producer
Five lowest permeability locations
-
I5(HP)
5 FCDs in Injector
Single tubing in Producer
Five highest permeability locations
-
P5(LP)
Dual-tubing in Injector
5 FCDs in Producer
Five lowest permeability locations
P5(HP)
Dual-tubing in Injector
5 FCDs in Producer
Five highest permeability locations
I5(LP)P5(LP)
5 FCDs in Injector
5 FCDs in Producer
Five lowest permeability locations
Five lowest permeability locations
I5(HP)P5(HP)
5 FCDs in Injector
5 FCDs in Producer
Five highest permeability locations
Five highest permeability locations
I5(LP)P5(HP)
5 FCDs in Injector
5 FCDs in Producer
Five lowest permeability locations
Five highest permeability locations
I5(HP)P5(LP)
5 FCDs in Injector
5 FCDs in Producer
Five highest permeability locations
Five lowest permeability locations
179
For each case, the Eclipse thermal reservoir simulator was used (Schlumberger, 2014). This
simulator is a parallel finite volume reservoir simulator where the reservoir domain is divided
into grid blocks over which mass and energy balances together with phase behaviour in the
context of Darcy flow of each phase governed by gas-liquid and oil-water relative permeability
curves are solved (Schlumberger, 2014). The phase behaviour calculations are equilibrium based
(meaning that at each time step, equilibrium is enforced and are based on K-value flash
calculation (Schlumberger, 2014). For the wells, multiphase flow is modelled by using a driftflux model (Schlumberger, 2014) where the momentum and energy balances are taken into
account together with phase behaviour (again modelled by a K-value based flash calculation).
For the FCD design, the length of each well segment was taken to be the length of a single joint
multiplied by the open flow area per joint (Stone et al. 2013). According to Youngs et al. (2009),
multiple nozzles are represented by a single equivalent nozzle. Then the flow rates through the
nozzles should be scaled to correctly simulate the pressure drop across the single equivalent
devices. To accomplish this, the effective nozzle diameter (cross-sectional area) of a single
nozzle was increased by the number of joints that could fit into each of the 100 m segments. For
flow through the nozzles, it obeys Bernoulli’s law of pressure drop versus flow rate (Stone et al.,
2013). The multisegment well model supports down hole device modeling within the reservoir
(Schlumberger 2014; Youngs et al., 2009; Neylon et al., 2009).
Birchenko (2010) defined the ICD’s resistance, referred to as ICD’s “strength”, to flow
depending on the dimensions of the installed nozzle orifices or channels. He mentioned a high
ICD strength may be required to achieve a high level of inflow uniformity, reducing the well’s
180
productivity or injectivity. From his work, the total pressure difference between the reservoir and
the tubing, ΔP, can be divided into the pressure drop in the reservoir, ΔPr, and the pressure drop
in the ICD, ΔPICD. Following Bernoulli’s law, the pressure drop generated by an ICD is
proportional to the second power of the flow rate through ICD (Schlumberger, 2009). In terms of
specific inflow:
∆𝑃𝐼𝐶𝐷 = 𝑎𝑈 2 (𝑙)
7.1
Where
1/4 𝜌
𝜌
For channel ICDs
𝑎 = (𝜌𝜇𝑐𝑎𝑙 )
For nozzle or orifice ICDs
𝑎=
𝑐𝑎𝑙
𝑙 2 𝐵2 𝑎𝐼𝐶𝐷
𝜌𝑐𝑎𝑙 𝐼𝐶𝐷
2
𝐶𝑢 𝜌𝑙𝐼𝐶𝐷
𝐵2
𝐶𝑑2 𝑑4
7.2
7.3
where U is inflow per unit length of completion; l is distance between particular wellbore point
and the toe; 𝜌𝑐𝑎𝑙 is density of calibration fluid (water); ρ is density of produced or injected fluid;
𝑙𝐼𝐶𝐷 is length of the ICD joint (typically 12 m or 40 ft); B is formation volume factor; 𝑎𝐼𝐶𝐷 is
channel ICD strength; Cu is unit conversion factor; Cd is discharge coefficient of nozzle or
orifice; d is the effective diameter of nozzles or orifices in ICD joint of length 𝑙𝐼𝐶𝐷 .
During SAGD operation, the operating constraint prescribed for the injection well is the
maximum steam injection rate which is set equal to 600 m3/day (cold water equivalent, CWE),
with 90% steam quality. For the production well, the minimum production pressure is
constrained equal to 2,700 kPa during SAGD operation. Prior to SAGD operation, four months
of steam circulation was modeled by using temporary heater wells positioned in the locations of
181
both injection and production wells. To mitigate pressure buildup that arises from thermal
expansion of the fluids near the well bore during circulation, both injection and production wells
are operated as production wells in this time period with bottom hole pressure constrained equal
to the initial reservoir pressure at the well depths (Gates et al., 2007). After the steam circulation
period, the temporary heaters are turned off and the upper well switched back to an injection
well. From then on, the wellpairs are in SAGD operation: steam is injected into the upper
injection wells and fluid is produced from the bottom production wells. Each of the cases is
simulated for six years of operation.
7.5 Results
7.5.1 FCDs in Clean Sand Model
Five simulation cases (BC, I5, I10, P5, and P10) were completed in this section as listed in Table
7.3. All FCD nozzles are uniformly assigned in these cases. Figure 7.11 displays oil production
profiles for base case and FCD cases. For clean sand model, the base case achieves oil rates
starting about 100 m3/day which rise with time as the chamber grows within the reservoir up to a
peak of 350 m3/day. The other cases exhibit similarly shaped profiles. The highest initial oil
rate that occurs over the first four years of the operation is found in the I5 case (5 FCDs in
Injector). Beyond this point, the oil rate for this case drops and becomes the lowest among the
cases. In Cases I10 and P10, the oil rate profiles are similar to that of the base case. It appears
10 FCDs in the injection or production wells does not help the performance of the wellpairs with
182
respect to oil rate. In the P5 case, the oil rate is greater than that of the base case over the first
three years of the operation. Beyond this point, the oil rate is lower than that of the base case.
Figure 7.11 Oil production profiles for clean sand cases with uniform distribution of FCDs
along the well pair. .
Figure 7.12 shows the cumulative steam-to-oil ratios (cSORs) for each case. The results show
that after six years of operation, all five well completion design cases achieve similar values
equal to about 2.7 m3/m3. However, Cases I5 and P5 achieved significantly better cSOR profiles
compared to the other cases – their cSORs over the first three years is roughly one-third lower
than that of the other cases. This implies that its steam requirement per unit oil and carbon
183
dioxide emissions intensity is significantly lower over the first three years of the operation
compared to the other cases.
Figure 7.12 Cumulative steam-to-oil ratio profiles for clean sand cases with uniform
distribution of FCDs along the well pair.
Figure 7.13 presents the steam production profiles for the clean sand models. For the clean sand
model, in general, FCDs in the production well provided better steam production control than
that of the cases with FCDs in the injection well. For the I5 and P5 cases, significant live steam
production occurs for a significant portion of the early and late operation yet these cases
achieved the highest early oil rates and best cSORs over the first few years. This suggests that
FCDs for control of steam production is not the only feature that these well devices provide to
the system.
184
Figure 7.13 Steam production profiles for clean sand cases with uniform distribution of
FCDs along the well pair. .
Based on the performance plots, cross-section views of the process, viewed in the plane of the
SAGD well pair, are displayed for the base case, P10 (poorer case), and I10 (better case),
displayed in Figures 7.14, 7.15, and 7.16, respectively. The top image in these figures is the
permeability distribution (recall here that in the clean sand models, the permeability has a small
range from 4570 to 7428 D). The remaining images show the temperature distribution, oil
saturation distribution, and ternary phase distribution for Years 1, 2, 4, and 6. The ternary phase
diagrams provides an indication of the presence of gas (indicated by red), water (indicated by
blue), and oil indicated by green) phases. In the base case, the results show that despite the
relatively low heterogeneity of the reservoir, after one year of operation, there are a few ‘cold’
185
spots along the well pair – the largest is located roughly at the middle of the well pair. The
results show that the steam chamber, in the heated intervals, has ascended to the top of the
formation but that the zone that is mainly gas(steam)-filled is at the top of the reservoir.
Between the top gas (steam) zone and the well pair mobilized oil and steam condensate are
draining to the well pair but the chambers are not uniform but appear as ‘plumes’ along the well
pair. By year 4, largest ‘plumes’ of draining oil evolve into dominant main ‘hot’ spots along the
well pair where most of the drainage is occurring into the production well. As the oil intervals
between the hot spots are heated further, the conformance along the well pair increases and by
Year 6, the steam chamber has evolved to occupy the full length of the well pair.
Case P10 performed the worst of the clean sand cases. The locations of the FCDs are displayed
in the permeability distribution. The visualization results shown in Figure 7.14 show that the
‘plumes’ of draining oil persist to Year 4 and that there are many more, smaller plumes than was
found in the base case. The locations of the plumes for some locations are correlated with the
position of the FCDs whereas in a few locations, it is not the case. By Year 6, the steam
chamber has descended to the well pair and a large continuous chamber exists along the well pair.
Figure 7.15 displays the results for the I5 case. The results show that the growth of the chamber
is larger when the FCDs are placed in the injection well compared to the P10 case.
186
Figure 7.14 Visualization of SAGD process for the base case in the clean sand model
(images are exaggerated 3 times in the vertical direction).
187
Figure 7.15 Visualization of SAGD process for Case P10 in the clean sand model (images
are exaggerated 3 times in the vertical direction).
188
Figure 7.16 Visualization of SAGD process for Case I10 in the clean sand model (images
are exaggerated 3 times in the vertical direction).
189
7.5.2 FCDs in Point Bar Model
7.5.2.1 Uniformly-Spaced FCDs Cases
The five cases examined here are the base case and the I5, I10, P5, and P10 cases for the point
bar model. The oil production rate profiles for these cases are displayed in Figure 7.17; they are
similar in shape to that of the clean sand profiles. For the base case, the results are very similar –
over the first three years, the oil rate is equal to about 110 m3/day and then it rises and peaks at
about 350 m3/day. For the point bar model, the best two cases are those of the I10 and P10 cases.
The cases with 5 FCDs perform roughly equal to that of the base case with the exception of the
I5 case which achieves a later period peak rate. Figure 7.18 shows the cumulative steam-to-oil
ratios (cSORs) for each case. The results show that after six years of operation, all five well
completion design cases achieve similar values in point bar models. However, better cSOR
profiles are obtained in the I10 and P10 cases. After three years of operation, they have achieved
cSORs that are roughly one-third that of the base case.
Figure 7.19 presents the steam production profiles for the point bar cases with uniform
distribution of FCDs along the well pair. Similar to the clean sand cases, FCDs in the production
tended to yield lower live steam production compared to FCDs in the injection well. Similar to
the clean sand cases, the cases where live steam production occurred tended to have the lower
cSORs which is not typically expected. The reason for this is because even though putting FCDs
in to control steam production rate is good, it also inhibits oil production.
190
Figure 7.17 Oil production profiles for point bar IHS cases with uniform distribution of
FCDs along the well pair.
Figure 7.18 Cumulative steam-to-oil ratio profiles for point bar IHS cases with uniform
distribution of FCDs along the well pair.
191
Figure 7.19 Steam production profile for point bar IHS cases with uniform distribution of
FCDs along the well pair.
Figures 7.20, 7.21, and 7.22 displays visualizations of the process evolution (temperature, oil
saturation, and ternary phase distributions) in the plane of the well pair for the base case and
Cases P5 and P10, respectively. Despite the similarity of the base case profiles of the clean sand
and point bar IHS models, as shown by Figures 7.14 and 7.20, the evolution of the depletion
chambers within the reservoirs are significantly different. The results show that the shale layers
provide a much greater control on the evolution of the chamber in the point bar model. This is
most evident by comparing the ternary phase distributions of Figures 7.14 and 7.20. In the point
bar model, the leftmost steam chamber evolves towards the right as the process continues with
chamber growth and drainage aligned with the shale layers.
192
Figure 7.20 Visualization of SAGD process for the base case in the point bar IHS model
(images are exaggerated 3 times in the vertical direction).
193
Figure 7.21 Visualization of SAGD process for Case P5 in the point bar IHS model (images
are exaggerated 3 times in the vertical direction).
194
Figure 7.22 Visualization of SAGD process for Case P10 in the point bar IHS model
(images are exaggerated 3 times in the vertical direction).
195
By Year 2, steam chamber conformance is less than one-third the length of the well pair. For
Case P5 displayed in Figure 7.21, comparing the gas (steam) phase distribution from the ternary
diagrams, the steam chamber has not grown in extent down the length of the well pair as is the
case in the base case. For Case P10 shown in Figure 7.22, the 10 FCDs have helped to drain
greater oil from the reservoir – most evident after Year 6.
7.5.2.2 Cases I5P10 and I10P5 in the Point Bar IHS Model
Figures 7.23, 7.24 and 7.25 present the oil production rates, cSOR, and steam production rate,
respectively, for the base case and I5P10 and I10P5 cases. The results show that the use of the
FCDs improves the oil production rate especially over the first three years of the operation. The
increase of the oil rate shifts from about 110 m3/day for the base case up to about 190 m3/day for
the I5P10 and I10P5 cases. As a consequence, the cSOR profiles are reduced significantly as
shown in Figure 7.23. Over the duration of the operation, the I5P10 cSOR profile is slightly
lower than that of the I10P5 case. Similar to other cases, the most live steam production is seen
in the FCD cases.
The visualization of the evolution of the process in the plane of the SAGD well pair is displayed
in Figure 7.26. The results suggest that the FCDs improve steam conformance within the
reservoir and with the greater number of FCDs in the production well, oil production is not
constrained from the system as would be the case with lower number of FCDs.
196
Figure 7.23 Oil production profiles of Cases I5P10 and I10P5 in the point bar IHS model.
Figure 7.24 Cumulative steam-to-oil ratio profile of Cases I5P10 and I10P5 in the point
bar IHS model.
197
Figure 7.25 Steam production profile of Cases I5P10 and I10P5 in the point bar IHS model.
198
Figure 7.26 Visualization of SAGD process for Case I5P10 in the point bar IHS model
(images are exaggerated 3 times in the vertical direction).
199
7.5.2.3 Non-Uniform FCD spacing in the Point Bar Model
The results for Cases I5(LP), I5(HP), P5(LP), and P5(HP) are shown in Figures 7.27 to 7.29.
The results show that the placement of the FCDs, whether in the low permeability or high
permeability zones, does not significantly impact the performance of the process. In general,
there is a slight increase of the oil production rates and slight reduction of the cSOR profiles
when the FCDs are placed in the high permeability zones along the well pairs versus the lowest
permeability zones in the well pair.
The best case, indicated by the lowest cSOR profile, is the I5(HP) case where the FCDs are
placed in the injection well in the high permeability zones. Figure 7.30 displays the evolution of
the process for the I5(HP) case. The results show that the conformance of the steam chamber
along the well pair, best seen at Year 4 in the ternary phase distribution, is greater for the I5(HP)
case than that of the base and I5 cases. Since the permeability is high in these zones, steam
injectivity is greater and so to the oil drainage. Thus, the chamber grows fastest and yields the
best cSOR profiles.
200
Figure 7.27 Oil production profiles of base case and Cases I5(LP), I5(HP), P5(LP), and
P5(HP) in the point bar IHS model.
Figure 7.28 Cumulative steam-to-oil ratio profiles of base case and Cases I5(LP), I5(HP),
P5(LP), and P5(HP) in the point bar IHS model.
201
Figure 7.29 Steam production profiles of base case and Cases I5(LP), I5(HP), P5(LP), and
P5(HP) in the point bar IHS model.
202
Figure 7.30 Visualization of SAGD process for Case I5(HP) in the point bar IHS model
(images are exaggerated 3 times in the vertical direction).
203
7.5.2.4 FCDs in Both Wells with Non-Uniform Spacing
The results for Cases I5(LP)P5(LP), I5(HP)P5(HP), I5(LP)P5(HP), and I5(HP)P5(LP) are
displayed in Figures 7.31 to 7.33. The results show that the differences between the results are
not significant although the placement of the FCDs for both the injection and production wells
in the high permeability zones. The steam production rates reach as high as 50 m 3/day steam
(CWE) production rate which is lower than other FCD cases. Figure 7.34 displays the evolution
of the steam chamber for Case I5(HP)P5(HP). The results show that there appears to be greater
drainage within the reservoir as the process evolves when compared to the base case and other
FCD cases.
Figure 7.31 Oil production profiles of base case and Cases I5(LP)P5(LP), I5(HP)P5(HP),
I5(LP)P5(HP), and I5(HP)P5(LP) in the point bar IHS model.
204
Figure 7.32 Cumulative steam-to-oil ratio profiles of base case and Cases I5(LP)P5(LP),
I5(HP)P5(HP), I5(LP)P5(HP), and I5(HP)P5(LP) in the point bar IHS model.
Figure 7.33 Steam production profiles of base case and Cases I5(LP)P5(LP), I5(HP)P5(HP),
I5(LP)P5(HP), and I5(HP)P5(LP) in the point bar IHS model.
205
Figure 7.34 Visualization of SAGD process for Case I5(HP)P5(HP) in the point bar IHS
model (images are exaggerated 3 times in the vertical direction).
206
7.6 Discussion of Results
The results show that FCDs installed in the injection and production wells improve the
performance of SAGD. The impact of heterogeneity on the growth of the steam chamber is very
evident from the visualizations of the chambers. Establishment of steam flow paths happens soon
after the wells are switched over from steam circulation to SAGD mode and after these paths are
established, these flow paths are difficult to break and may endure throughout the life of the
SAGD well pair which compounds production at later stages of operation. This leads to ‘cold’
spots along the well pairs that persist for significant periods of time.
When FCDs are placed in the production well, the devices not only can equalize the toe to heel
influx but also provide greater control of the subcool by limiting steam production. Although
this may be helpful for steam trap control, if too few FCDs are placed in the production well, this
can also limit oil production from the reservoir. When FCDs are placed in the injection well,
these devices can better equalize the outflow of steam from heel to toe regardless of variations in
oil, water, and steam mobility properties within the reservoir. Thus, it will lead to a more stable
steam chamber and help mobilize a larger volume of heavy oil.
A comparison of the early year results, cumulative oil recovered and cSOR, is listed in Table 7.5.
For the clean sand cases, the results show that for most of the cases, the addition of FCDs help
the performance of the recovery process after 3 years of operation. The exception is the P10 case
where the cSOR and cumulative oil produced is worse than that of the base case. There appears
to be a significant drop of the cSOR and improvement of the oil recovered for the I5 and P5
207
cases in the clean sand model. Doubling the FCDs to 10 in either the injection or the production
wells does not help the process.
For the point bar IHS model, the results show that the I5(HP) case achieves the lowest cSOR.
The results also show that the greatest impacts on using FCDs appears to be when they are used
in the injection well. A comparison of the I5 and I10 cases in the point bar IHS model reveals
that the larger the number of the FCDs, the better the cSOR and the amount of oil recovered.
Similarly, for the point bar model, a comparison of the P5 and P10 shows that the larger the
number of the FCDs, the lower is the cSOR and the greater is the volume of oil recovered. This
is likely due to the greater hydraulic contact that the greater number of FCDs achieves. When
only 5 FCDs are used, the 5 used in the injection well alone achieve a better performance than
that of 5 FCDs in the production well alone. A comparison of Cases I5 and I5(HP) demonstrates
that placing the FCDs in the high permeability zones for the injection well improves the
performance of the process significantly. When the FCDs are placed in both wells in the high
permeability zones, the results are between the injection well placement only results and the
production well placement only results. For example, the I5(HP)P5(HP) results are between the
results of the I5(HP) and P5(HP) cases. Thus, it appears that FCDs placed in the injection well
have greater benefit over that of the production well.
208
Table 7.5 Summary of results of cases over the first three years of the operation.
Cumulative oil and cSOR are expressed in thousands of m3 and m3/m3, respectively.
Case Name
BC
(Clean Sand)
I5
(Clean Sand)
I10
(Clean Sand)
P5
(Clean Sand)
P10
(Clean Sand)
BC
(Point Bar IHS)
I5
(Point Bar IHS)
I10
(Point Bar IHS)
P5
(Point Bar IHS)
P10
(Point Bar IHS)
I5P10
(Point Bar IHS)
I10P5
(Point Bar IHS)
I5(LP)
(Point Bar IHS)
I5(HP)
(Point Bar IHS)
P5(LP)
(Point Bar IHS)
P5(HP)
(Point Bar IHS)
I5(LP)P5(LP)
(Point Bar IHS)
I5(HP)P5(HP)
(Point Bar IHS)
I5(LP)P5(HP)
(Point Bar IHS)
I5(HP)P5(LP)
(Point Bar IHS)
Cum. Oil, Cum. Oil, Cum. Oil,
Yr. 1
Yr. 2
Yr. 3
cSOR,
Yr. 1
cSOR,
Yr. 2
cSOR,
Yr. 3
24807
68737
125365
5.95
5.33
4.67
34654
112745
195735
4.25
3.25
2.99
23827
69584
134465
6.18
5.25
4.35
37026
102716
166369
3.99
3.57
3.52
23708
64033
117588
6.21
5.71
4.98
24661
68660
126087
6.00
5.33
4.64
24442
67765
133959
6.05
5.40
4.37
33681
108040
187825
4.37
3.38
3.11
23833
60316
102321
6.21
6.08
5.72
38989
108766
182589
3.77
3.36
3.20
39682
111720
189196
3.72
3.28
3.09
38239
104994
174581
3.86
3.49
3.35
30973
100428
179422
4.76
3.64
3.26
34566
113054
193161
4.26
3.24
3.02
34485
92527
153679
4.27
3.95
3.81
38357
102172
164920
3.83
3.58
3.55
35281
92365
157151
4.19
3.97
3.73
40967
106342
172610
3.61
3.45
3.39
38386
99794
166693
3.85
3.67
3.51
40253
102196
163173
3.68
3.58
3.58
209
The results suggest that the benefits of FCDs may be seen only in the first few years of the
operation and that due to conductive heating in the reservoir which eventually heats the entire
reservoir, long term benefits may diminish the longer the process operates. However, given the
time value of money and the significant reductions of the SOR early in the process (and
consequent decrease of the carbon dioxide intensity), FCDs should be used in the recovery
processes and new operating strategies should be considered, for example, step down pressure
operation, to continue the benefit from the FCDs.
7.7 Final Remarks
From the results described in this Chapter, the following conclusions are made:
1. Passive flow control devices (FCDs) tend to improve the oil rates and cSOR profiles of
SAGD in both clean sand and point bar IHS reservoirs.
2. The performances of flow control devices (FCDs) in injector or producer are largely related
to heterogeneity of geology of the oil sands formation.
3. FCDs impact the process performance to the greatest benefit when they are placed in the
injection well.
4. FCDs in the production well provide a means to control the steam production rate from the
reservoir but if too few FCDs are used, the oil production rate may be constrained as well.
5. Placement of the FCDs in the high permeability zones along the well pair appears to yield the
best performance.
210
CHAPTER 8: CONCLUSIONS AND RECOMMENDATION
8.1 Conclusions
This research is a first start to understand how the structure of a point bar impacts SAGD
performance. Given the water use and emissions of carbon dioxide from SAGD operations, it is
imperative that SAGD wellpairs are optimally positioned to reduce the steam injected per unit oil
volume produced to surface. The overall conclusions that arise from the research are as follows:
1.
The results show that SAGD orientation within the point bar is impacted by the structure
and heterogeneity of the point bar. Specifically, the wellpairs oriented perpendicular to the
inclined shale layers within the point bar performed significantly better than wellpairs
oriented parallel to the shale layers. When positioned perpendicular to the inclined shale
layers, the wellpairs cut across the shale layers allowing steam injectivity into the sand
intervals between the shale layers and oil drainage under gravity to the lower production
well.
2.
Given the importance of oil sands environmental emissions, the differences in performance,
especially cSOR, well pair orientation in the context of pad design within the point bar
architecture must be taken into account.
3.
The results reveal that the performance of the pad depends on well pair orientation and that
horizontal well pairs that are arranged to cut across the inclined heterolithic stratified shale
layers of the point bar perform better than well pairs aligned along the strike direction of the
211
shale layers. The heterogeneity of steam chambers surrounding the SAGD well pairs is
directly linked to the heterogeneity of the point bar.
4.
The effect of the orientation of a pad of Steam-Assisted Gravity Drainage (SAGD) well
pairs in an oil sands reservoir comprising a 30 m thick basal sand zone and a 20 m thick
inclined heterolithic strata interval directly above the sand zone has been evaluated. The
results reveal that the performance of the pad depends on well pair orientation and that well
pairs that are arranged to cut across the inclined heterolithic stratified shale layers of the
point bar perform better than well pairs aligned with the shale layers.
5.
There is less effect of well pair orientation on the performance in a point bar deposit with a
clean sand base. The heterogeneity of steam chambers surrounding the SAGD well pairs is
directly linked to the heterogeneity of the point bar although some heterogeneity of the
steam chambers is even evident in the sandy base.
6.
The results also show that there is large variability of the performance of the well pairs
within the pad itself after the steam chamber reaches the overlying point bar part. Thus, it is
not possible to use a single well pair to gauge the performance of the process within an oil
sands reservoir. That is, pad scale models are required for recovery process design and
forecasting.
7.
Passive flow control devices (FCDs) tend to improve the oil rates and cSOR profiles of
SAGD in both clean sand and point bar IHS reservoirs. The performances of flow control
devices (FCDs) in injector or producer are largely related to heterogeneity of geology of the
oil sands formation.
FCDs have large effect in clean sand reservoir especially when
installed on the injection well.
212
8.
FCDs in the production well provide a means to control the steam production rate from the
reservoir but if too few FCDs are used, the oil production rate may be constrained as well.
9.
Placement of the FCDs in the high permeability zones along the well pair appears to yield
the best performance.
8.2 Recommendations
The research documented in this thesis was on evolution, control, and improvement of steam
conformance along SAGD well pairs within heterogeneous point bar oil sands reservoirs. The
results of the research suggest the following recommendations:
1.
Examine how operating strategy and additives, for example, solvents and non-condensable
gas, could be used to improve the performance of SAGD in heterogeneous point bar
deposits.
2.
More research is needed on the use of flow control devices (FCDs) in SAGD well pairs to
determine optimal placement strategies and operating conditions.
3.
Explore how FCDs could be used in tubing strings in already mature SAGD operations to
extend their economic life.
4.
Use rigorous optimization to improve the placement of pads and well pairs within point bar
deposits together with their operating strategy.
213
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APPENDIX
Figure A.1 Porosity-Permeability transform for each Facies
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Figure A.2 Normalized Water Oil Relatively Permeability curve
Figure A.3 Normalized Gas Liquid Relatively Permeability curve
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