Apresentação de Victor Manuel Salazar Araque, da Computer Modelling Group, durante o evento promovido pelo Sistema FIEB, Fundamentos da Exploração e Produção de Não Convencionais: a Experiência Canadense.

1. Unconventional Reservoirs
Flow modelling challenges
Victor Salazar
victor.salazar@cmgl.ca
November, 2013

2. Agenda
1. CMG products
2. Unconventional Reservoir Modelling Physics
3. Using CMG’s Reservoir Simulation products
to Determine EUR from Limited Data
4. Using CMG’s Reservoir Simulation products
to Optimize Well Completion Design & Well
Spacing
5. SPE Unconventional Reservoir papers that
feature the use of CMG’s Reservoir
Simulation products

3. CMG Software Products
Superior physics
EOR advanced processes leader (+95%)
 Project Manager
LAUNCHER
 Reservoir Numerical Simulators
Black Oil/Condensate simulator
GEM
Equation of State Compositional
Simulator
STARS
 Pre & Post Processors
IMEX
K value compositional, thermal,
chemical, geomechanical simulator
BUILDER
RESULTS 3D
RESULTS GRAPH
RESULTS REPORT
 Converter
ECL 100 IMPORT ASSISTANT
 Assisted history match, Optimization,
Sensitivity and Uncertainty analysis
CMOST
 Phase behavior, PVT modelling
WINPROP

4. Unconventional reservoirs physics
Diffusion
Desorption
Fractured system
Non-Darcy effects
Low porosity/permeability
Typical Shale Adsorption Curve
Gas Adsorption (ft3/ton)





700
600
500
400
300
200
100
0
Shale
0
1000
2000
Pressure (psi)
3000
4000

5. CMG Simulator Physics
Physics
IMEX
GEM
PVT
BO, VO, GC, WG
EOS
Adsorbed Comp
Gas Comp
Any Comp
Diffusion
No
Any Comp
Natural Fracs
DP or DK
DP or DK
Non-Darcy (turbulent) Flow
Yes
Yes
Klinkenberg (slip) Flow
No
Yes
Krel/Pc by Rock Type
Yes
Yes
Propped Fracs
Explicit Grids
Explicit Grids
Press-dependent Compaction
Yes (& w/ time)
Yes (& w/ time)
Stress-dependent Compaction
No
Yes (w/ GEOMECH)
LS-LR-DK gridding
Yes (& w/ time)
Yes (& w/ time)

6. CMG Frac’d Well Modelling History

7. Microseismic Results
Possible trend visible
in blue stage
Possible interaction with
pre-existing fractures?
Trend visible in red stage
Shmax direction?
In-situ stress will
influence dominant
hydraulic fracture
orientations
Williams-Stroud, Microseismic, 2008

8. Propped Frac Gridding is EASY
BUILDER can create LS-LR-DK
(tartan) grids around fractures
automatically
Single Plane Geometry
Complex Geometry

9. Varying Propped Frac Properties & SRV
Size with CMOST is EASY
Propped Frac Properties
Half-length, Width, Perm, Spacing,
Height & Perm Gradient
Stimulated Natural Frac Properties:
Width, Perm
SRV Size & Shape
# MS events per gridblock
MS Moment Magnitude
MS Confidence Value
Etc.

10. Geomechanics
 Independent
geomechanic grid
 Hydraulic fracture closure
 New fractures opening
 Permeability vs Stress
kf
C
kfmax
D
kfmin
B
Crack occurs
Beginning
A
/
σ fn

11. 3 key Questions about
Unconventional Reservoirs
1. How can I determine the EUR with
limited data?
2. What is the Optimum Well
Completion Design?
3. What is the Optimum Well
Spacing?

12. Physics-based EUR Calculation
1. Choose CMG simulator
with required physics
Engineer builds base model, decides which parameters
to allow CMOST to vary, and CMOST does the rest
2. Build base model
3. Perform SA & AHM
4. Forecast EUR using
best HM models

13. Physics-based EUR Calculation
• 4000 ft Eagle Ford “Oil Window” well
•
41-stage frac job pumped
• 7 months of production (222 days)
•
Oil, gas & water rates, and flowing BHP
measured daily
• Task: Determine Oil & Gas EURs
• Solution: Match 7 months of history &
Forecast 30 years of future production

14. Physics-based EUR Calculation
Known Reservoir, Well & Fluid Properties
Property
Value
Unit
Depth at top of reservoir
Reservoir thickness
Initial Reservoir Pressure
Initial Reservoir Temperature
Oil Bubble Point Pressure
Oil Gravity
Initial Solution GOR
Lateral Length
Number of Frac Stages Pumped
10,800
150
8,100
270
3010
43
950
4000
10
feet
feet
psi
F
psi
API
scf/stb
feet

15. Physics-based EUR Calculation
Ranges for uncertain reservoir & frac properties
Property
Min
Value
Max
Value
Unit
Matrix Porosity
Matrix Permeability
Natural Fracture Effective Porosity
Natural Fracture Effective Permeability
Natural Fracture Areal Spacing
Propped Fracture Spacing
Propped Fracture Half-Length
Propped Fracture Permeability
Swi in Propped & Natural Fractures
0.04
10
0.0006
40
50
100
50
1
0.15
0.10
1000
0.0006
40
50
400
400
30
0.45
fraction
nD
fraction
nD
feet
feet
feet
D
fraction

16. Physics-based EUR Calculation
Krel, Pc & PV Compaction Assumptions
Property
Matrix Krel
Natural Fracture Krel
Propped Fracture Krel
Matrix Pc
Natural Fracture Pc
Propped Fracture Pc
Matrix PV Compaction
Natural Fracture PV Compaction
Propped Fracture PV Compaction
Assumptions
Corey Functions are sufficient
Straight Line behavior
Straight Line behavior
Can ignore during primary depletion
Zero
Zero
Constant Compressibility
Constant Compressibility
Changes with Pressure

17. Physics-based EUR Calculation
2D Areal View of Simulation Grid

18. Physics-based EUR Calculation
3D Perspective View of Simulation Grid

19. Physics-based EUR Calculation
 CMOST




Assisted HM
Optimization
Sensitivity and
Uncertainty analysis

20. Physics-based EUR Calculation
Discrete Values used in Sensitivity Analysis
Matrix
Perm
(md)
Nat
Matrix Frac
Por
Swi
(frac) (frac)
Rock
Comp
Table #
Prop’d
Frac
Xf
(ft)
Prop’d
Frac
Perm
(md)
Prop’d
Frac
Spacing
(ft)
Prop’d
Frac
Swi
(frac)
0.00001
0.04
0.15
ctype1.inc
50
1000
100
0.15
0.0001
0.06
0.25
ctype2.inc
150
10000
200
0.25
0.0005
0.08
0.35
ctype3.inc
250
20000
300
0.35
0.001
0.1
0.45
ctype4.inc
400
30000
400
0.55

21. Physics-based EUR Calculation
Propped Frac PV Compaction Curves
Permeability Multiplier
1
0.1
ctype1
0.01
ctype2
ctype3
ctype4
0.001
0.0001
0
1000
2000
3000
4000
5000
Pressure, psia
6000
7000
8000
9000

22. Physics-based EUR Calculation
Cumulative Oil Tornado Plot

23. Physics-based EUR Calculation
Cumulative Water Tornado Plot

24. Physics-based EUR Calculation
Discrete Values used in History-Match
Nat
Prop’d Prop’d Prop’d Prop’d
Matrix Matrix Frac
Rock
Frac
Frac
Frac
Frac
Perm
Por
Swi
Comp
Xf
Perm Spacing Swi
(md)
(frac) (frac)
Table #
(ft)
(md)
(ft)
(frac)
0.00001 0.04
0.15 ctype1.inc
50
1000
100
0.15
0.00005 0.05
0.16 ctype2.inc
100
5000
150
0.20
0.0001
0.06
0.17 ctype3.inc
150
10000
200
0.25
0.0002 Total Search Space: 6.22 million15000
0.07
0.18 ctype4.inc
200
250
combinations 0.30
0.35
0.0003
0.08
0.20
250
20000
300
0.09
25000
350
0.40
0.0004
0.25
300
0.10
400
30000
400
0.45
0.0005
0.30
0.0007
0.35
0.40
0.001

25. Physics-based EUR Calculation
History-Match Run Progress Plot
Engineer only has to monitor
History-Match progress….. so is
free to work on other projects!

26. Physics-based EUR Calculation
Oil Phase History-Match

27. Physics-based EUR Calculation
Gas Phase History-Match

28. Physics-based EUR Calculation
Water Phase History-Match

29. Physics-based EUR Calculation
Flowing BHP History-Match

30. Physics-based EUR Calculation
30-yr Oil EUR using 15 best HM models
Maximum
Minimum
Average
Median
Std Dev
Oil EUR (stb)
724,059
571,847
654,125
649,323
45,162

31. Physics-based EUR Calculation
30-yr Gas EUR using 15 best HM models
Maximum
Minimum
Average
Median
Std Dev
Gas EUR (MMscf)
981
851
926
922
44

32. Time to do Physics-based EUR
Task
ENGINEER’s time
100 CMOST SA runs*
446 CMOST AHM runs*
15 x 30-year forecast runs**
TOTAL COMPUTE Time
Time
(hr)
8
2.8
8.5
0.6
11.9
Time/Run
(min)
1.7
1.1
2.5
-
* 4 simultaneous 4-way parallel IMEX runs on a Dell Precision T5600
** Sequential 16-way parallel IMEX runs on a Dell Precision T5600

33. Physics-based Well Optimization
1. Choose CMG simulator
with required physics
Engineer builds base model, decides which parameters
to allow CMOST to vary, and CMOST does the rest
2. Build base model
3. Perform SA
4. OPT Completion Design
5. OPT Well Spacing

34. Physics-based Well Optimization
Assumed Reservoir, Well & Fluid Properties
Property
Natural Fracture Relative Permeability
Propped Fracture Relative Permeability
Matrix Capillary Pressure
Natural Fracture Capillary Pressure
Propped Fracture Capillary Pressure
Matrix Pore Volume Compaction
Natural Fracture PV Compaction
Propped Fracture PV Compaction
Data
Straight Line data from EUR calc.
Straight Line data from EUR calc.
Assumed to be zero
Assumed to be zero
Assumed to be zero
Constant
Constant
“ctype4.inc” from EUR calc.

35. Physics-based Well Optimization
Assumed Economic Parameters
Economic
Parameter
Oil Price
Gas Price
Well Drilling Cost
Frac Cost
Forecast Period
Value
100
3
3,000,000
250,000
30
Unit
$US/bbl
$US/Mscf
$US/well
$US/Stage
years

36. Physics-based Well Optimization
Proposed Well Completion/Spacing Options
Property
Proposed Well Spacing
Proposed Well Lateral Length
Min
Value
Max
Value
128
640
(5 wells) (1 well)
4000
4000
Unit
acres
feet
Proposed Propped Fracture Spacing
200
800
feet
Proposed Propped Fracture Half-Length
50
400
feet
Proposed Propped Fracture Permeability
1
20
D

37. Physics-based Well Optimization
Discrete Values used for
Completion Optimization
Propped Frac
Propped Frac
Propped Frac
Spacing
Permeability
Half-Length
(feet)
(Darcies)
(feet)
200
1
50
300
3
100
400
6
200
Total Search Space: 240 combinations
500
9
300
600
12
400
800
15
18
20

38. Physics-based Well Optimization
Optimization Run Progress Plot
Engineer only has to monitor
Optimization progress….. so is
free to work on other projects!

39. Physics-based Well Optimization
Optimum Parameter Histograms

40. Physics-based Well Optimization
Cum Oil after 30 years vs # of Wells
# of Wells
1
2
3
4
5
NPV
(MMUSD)
49
97
145
191
230

41. Physics-based Well Optimization
Matrix Pressure @ 30 years with 4 & 5 wells

42. Time to do Physics-based
Well Completion & Spacing
Optimization
Task
ENGINEER’s time
Time (hr)
8.0
Time/Run
(min)
-
55 CMOST OPT runs*
5 IMEX 30-year Forecast runs**
TOTAL COMPUTE Time
2.2
0.85
3.05
1.9
10.2
-
* 4 simultaneous 4-way parallel IMEX runs on a Dell Precision T5600
** 5 Sequential 16-way parallel IMEX runs on a Dell Precision T5600

43. SPE References
Used GEM to model DFITs and concluded:
• Greatly enhances our ability to efficiently design DFIT's for tight shale reservoirs
• Shows the validity of the Nolte analysis technique for tight rocks and provides guidelines for the shut-in
time duration required to generate a reasonable estimate of reservoir properties from DFIT pressure
response
• Shows that geomechanics-coupled reservoir flow simulation of DFITs can provide estimates of fracture
dimensions that compare reasonably with those from more traditional fracture design tools
• Demonstrate that geomechanics-coupled reservoir flow simulation provides an additiona advantage over
traditional fracture design tools in that is can numerically model the system response even after fracture
closure
• Shows significant fracture tip extension, both vertically and horizontally, for a significant period after the
end of the shut-in period

44. SPE References
SPE 166279
Estimation of Effective Fracture Volume Using Water
Flowback and Production Data for Shale Gas Wells
Ahmad Alhkough (TAMU), Steve McKetta (Southwestern Energy) and Robert
Wattenbarger (TAMU)
Used IMEX to model water flowback and long-term production, and
concluded:
• Used to simulate production of gas and water from a shale gas
well
• Water production analysis can provide effective fracture volume
estimates, which were confirmed by cumulative water produced,
which in turn can evaluate fracture-stimulation treatments.
• Water production analysis can show the pitfalls of ignoring
flowback data (i.e. in some cases the time-shift on diagnostic plots
changes the apparent flow regime indentification of the early gas
production data, as well as water production data, which leads to
different (incorrect) interpretation of the fracture/matrix system.

45. SPE References
URTeC 1575448
Marcellus Well Spacing Optimization – Pilot
Data Integration and Dynamic Modeling Study
Deniz Cakici, Chris Dick, Abhijit Mookerjee, Shell Exploration &
Production; Ben Stephenson, Shell Canada
Used GEM & CMOST to Match production history

46. 36 E&P Companies are using CMG for
Unconventional Reservoir Modelling
•
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Anadarko
Apache
BG Group
BHP Billiton
Birchcliff
Bonterra
BP
Chesapeake
Chevron
Devon
Encana
Enerplus
•
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•
•
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•
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•
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EOG
ExxonMobil
Harvest
Marathon
Matador
Nexen
Noble Energy
PennWest
Perpetual
Petrobakken
Reliance
Rosetta
Resources
•
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Samson
Sasol
Seven Generations
Shell
Sinopec Daylight
Southwestern Energy
Statoil
Talisman
Taqa North
Total
Vitruvian
XTO
“Physics-based”
EUR & Well Optimization
in hours
using CMG software

47. VISION:
To be the Leading Developer and Supplier of
Dynamic Reservoir Technologies in the World
info@cmgl.ca
www.cmgl.ca