1. INSTRUCTOR © 2017, John R. Fanchi
All rights reserved. No part of this manual may be reproduced in any form without the express written permission of the author.
© 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

2. To the Instructor
The set of files here are designed to help you prepare lectures for your own course using the text Introduction to Petroleum Engineering, J.R. Fanchi and R.L. Christiansen (Wiley, 2017)
File format is kept simple so that you can customize the files with relative ease using your own style. You will need to supplement the files to complete the presentation topics.

3. RESERVOIR PERFORMANCE
© 2017, John R. Fanchi
All rights reserved. No part of this manual may be reproduced in any form without the express written permission of the author.
© 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

4. Outline Reservoir Flow Simulators Reservoir Flow Modeling Workflows
Performance of Conventional Oil and Gas Reservoirs
Performance of an Unconventional Reservoir
Performance of Geothermal Reservoirs
Homework: IPE Ch. 14

5. RESERVOIR FLOW SIMULATORS
© 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

6. Flow Model Reservoir Simulation Subsystems
Surface Model
Wellbore Model
Well Model
Reservoir Model

7. Reservoir Subdivisions
Subdivide reservoir into subregions
Require for each subregion:
mass entering – mass leaving = mass accumulation
Volume
Element
Unconformity

8. What is a flow unit*?
“a volume of rock subdivided according to geological and petrophysical properties that influence the flow of fluids through it.”
* W.J. Ebanks, Jr., 1987 AAPG Annual Meeting

9. What is a flow unit*?
A mappable portion of the total reservoir within which geological and petrophysical properties that affect the flow of fluids are consistent and predictably different from the properties of other reservoir rock volumes (after Ebanks, 1987)
* Ebanks, Scheihing and Atkinson (1993): AAPG Methods #10

10. Characteristics of a flow unit*
A specific volume of reservoir composed of
One or more reservoir quality lithologies
Any nonreservoir quality rock types
Fluids they contain
Correlative and mappable at the interwell scale
Flow unit zonation is recognizable on wireline logs
May be in communication with other flow units
* Ebanks, Scheihing and Atkinson (1993): AAPG Methods #10

11. Flow Units and Geostatistics
Flow units are “mostly deterministic”
Use geostatistics conditioned by well data
To distribute petrophysical properties
To create stochastic realizations
* Ebanks, Scheihing and Atkinson (1993): AAPG Methods #10

12. Extended Black Oil Simulator Flow Equations
Stock Tank Oil
Water plus Surfactant
Surfacant
Soluble Species
© 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

13. Discretize time into time steps
Finite Differences
Formulate fluid flow equations, e.g.
Approximate derivatives with finite differences
Discretize region into grid blocks
Discretize time into time steps
Numerically solve set of linear algebraic equations

14. Finite Difference Representation
Production Wells
Injection Wells
Distributions
S = S(x,y,z,t)
P = P(x,y,z,t)
Spatial Discretization
Time Discretization
Aspect Ratio of Block
Width / length
Eg. y / x for areal grid
No Flow Nodes

15. Digitize Mapped Properties

16. Numerical Dispersion Arises from time and space discretizations
Leads to smeared spatial gradients
saturation, concentrations
Depends on grid-block size and time-step size

17. Well Models
Vertical
Deviated
Horizontal
Multilateral

18. RESERVOIR FLOW MODELING WORKFLOWS
© 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

19. Traditional Brown Field Flow Modeling Workflow
Illustrative Deterministic History Matching Workflow (after Williams, et al., 1998)

20. Green Fields and Brown Fields
Data requirements depend on field history
Green Field
Essentially an undeveloped field
Minimal production – injection history
Brown Field
Essentially a developed field
Significant production – injection history

21. Green Field Flow Modeling Workflow
Step
Task G1
Gather Data G2
Identify Key Parameters and Associated Uncertainties G3
Generate Forecast of Field Performance Results G4
Generate Distribution of Field Performance Results
(Proxies facilitate statistical analysis)

22. Green Field Flow Modeling Workflow
(minimal history)
Identify parameters and uncertainties
Gather data
Generate recovery distribution
Generate prod-inj forecasts

23. How many trial runs should be made?
Experimental Design
Different ways to design experiment
Full factorial design
Select p input parameters
Vary each parameter using q values
3-Level Design uses q = 3 values
e.g. Min, Most Likely, Max
# of trial runs = pq
3-Level Full factorial design example
Let p = 3 and q = 3
# of trial runs = pq = 33 = 27

24. Illustrate q-Level Design Parameter Space
Select p = 3 input parameters (x1, x2, x3)
2-Level Design uses q = 2 values
e.g. Min, Max
3-Level Design uses q = 3 values
e.g. Min, Most Likely, Max
fills in parameter space
# of runs = 3q

25. Modern Brown Field Flow Modeling Workflow
Step
Task B1
Gather Data B2
Identify Input Parameters and Associated Uncertainties B3
Identify History Match Constraints and History Match Variables B4
Generate Forecast of Field Performance Results B5
Determine Quality of History Match
(Select subset of acceptable HM cases) B6
Generate Distribution of Field Performance Results
(Proxies facilitate statistical analysis) B7
Verify Workflow

26. Brown Field Flow Modeling Workflow
Identify input parameters and uncertainties
Brown field
(prod-inj history)
Gather data
Identify HM variables and constraints
Generate prod-inj forecasts
Variable
Constraints
Pressure
< 10%
Oil Rate
< 2%
Water Rate
Verify Workflow
Recovery Results from Subset
Determine Quality of HM (Select Subset)

27. PERFORMANCE OF CONVENTIONAL OIL AND GAS RESERVOIRS
© 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

28. Wilmington Field, California Immiscible Displacement by Water Flooding

29. Wilmington Field Fault Blocks and Stratigraphic Zones

30. Prudhoe Bay Field, Alaska Water Flood, Gas Cycling, and Miscible Gas Injection

31. Schematic Cross-Section of Prudhoe Bay Field, Alaska

32. PERFORMANCE OF AN UNCONVENTIONAL RESERVOIR
© 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

33. Barnett Shale, Texas Shale Gas Production

34. Barnett Shale, Texas Development Area

35. Barnett Shale, Texas Drilling Rig

36. Wellbore Trajectories Drilled from a Shale Development Well Pad

37. Surface Equipment at a Shale Gas Well Pad

38. Water Disposal Wells TX Railroad Commission must approve sites
Barnett Shale at 5000 to 7000 ft
Dispose in Ellenburger LS at 10,000 to 12,000 feet

39. Environmental Impact: Earthquakes
Several earthquakes in 2009
< 2.0 to 3.0 Richter quakes
Barnett is 5, ’ deep
Two disposal wells near quakes
Disposal wells are 10-12,000’ deep
Known faults in area
Faults originate >14,000’ deep
Tremors are from 14,000-15,000 ft
UT and SMU seismograph study
No direct relationship proven

40. Working with Communities
ANSI – API Bulletin 100-3: Community Engagement
Consequence of unconventional resource development
Prepare communities for exploration activities
Minimize disruption to communities
Manage resources
Source: J. Donnelly, “Community Engagement,” JPT, Sep. 14, pg. 18

41. Summary
Barnett Shale
A pioneer in unconventional shale drilling and production techniques
Deviated drilling
Hydraulic fracturing
Will continue to guide other unconventional shale plays in the United States and around the world.
Areas for improvement:
Extend field/well production life
Improve accuracy of reserve estimates
Develop improved recovery techniques

42. PERFORMANCE OF GEOTHERMAL RESERVOIRS
© 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

43. Puna Geothermal Venture (PGV), Hawaii

44. Communities and Well Locations ca. 2005
PGV = Puna Geothermal Venture
[formerly HGPA operation]

45. HGPA Geothermal Operations
Initial operator: State of Hawaii
HGPA: Hawaii Geothermal Project – Well A
Experimental Geothermal Station
Operated from
Power: 2.2 MW

46. Puna Geothermal Operations
Puna Geothermal Venture (PGV)
Commenced operation in 1993
Power: 38 MW (30 MW + 8 MW expansion)
PGV acquired by Ormat in June 2004
Customer: Hawaii Electric Light Output
Contract to deliver 25 – 30 MW continuously
~ 20% of Big Island consumption
Puna 8 MW Expansion
Source:
accessed

47. 2 air-cooled power plants: Closed cycle and Binary system
Puna Geothermal Power
Flash-Binary Power Plant
Well
~ 1 mi deep
Well
2 air-cooled power plants:
Closed cycle and Binary system

48. Environmental Concerns
Health effects of fluid emissions such as H2S
Need to reinject produced fluids
Well failures
e.g. corrosion of tubing and casing; pollute groundwater; encounter magma/lava
Possible catastrophic events
e.g. blowouts, volcanic eruption, earthquakes, tsunami
Venting
Source: accessed

49. What is in Puna geothermal fluid?
Water (liquid and steam) plus
Benzene
Hydrogen sulfide
Fatal at 700 ppm
PGV wells at 750 – 1100 ppm
Ammonia
Mercury vapor
Methane
Non-methane hydrocarbons
Carbon dioxide
Arsenic
Radon
Radionuclides (alpha and beta emissions)

50. Environmental Impact Environmentally friendly features
noise reduction enclosures
low-profile, small-footprint design
near-zero emissions
100% geothermal fluid reinjection
continuous monitoring

51. QUESTIONS?
© 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

52. SUPPLEMENT
© 2004 John R. Fanchi All rights reserved. Do not copy or distribute.