1. Reservoir Engineering Aspects and Forecasting
SPEE Presentation
02 May 2019 | Brookhaven College, Farmer's Branch, TX
Reservoir Engineering Aspects and Forecasting
of Well Performance in Unconventional Resources
Tom BLASINGAME
Petroleum Engineering
Texas A&M University
College Station, TX (USA) —
SPE GCS Reservoir Study Group
2017 Reservoir Technology Forum 1

2. Brief Biography — Tom Blasingame
Who am I?
Professor, Texas A&M U.
B.S., M.S., & Ph.D. from Texas A&M U.
Counts: (May 2019)
14 Ph.D. Graduates
67 M.S. (thesis)/34 M.Eng. (report) Graduates
Over 160 Technical Articles
Historical Technical Contributions:
(1990's) Material Balance DCA ("Rate Transient Analysis" (or RTA)) [global standard]
(1990's) Analysis of Water-Oil-Ratio (WOR) Behavior [theoretical approach]
(1990's) Direct Estimation of pavg from Pressure Buildup Tests [theoretical approach]
(2000's) Pressure Integral and "Beta" Derivative [led to PTA and RTA methodologies]
(2010's) Diagnostic Analysis of Time-Rate Data (i.e., the qDb-plot) [evolving standard]
(career) Correlations for Rock and Fluid Properties [rg & mg are global standards]
(career) Deconvolution Methods (approximate, direct, and numerical) [several methods]
Research Interests: (2019)
Time-Rate Analysis (Models & Diagnostics) [unconventional reservoirs]
Early-Time "Flowback" Analysis/Interpretation [unconventional reservoirs]
Interpretation/Analysis of Time-Rate-Pressure Performance [unconventional reservoirs]
Parametric/Non-Parametric Correlation of Well Performance Data [various applications]
Numerical Analysis/Interpretation Techniques for Data [various applications]
[2012]
[2019]
(visa photo)
[self image]
[how others
see me]

3. Reservoir Engineering Aspects and Forecasting
SPEE Presentation
02 May 2019 | Brookhaven College, Farmer's Branch, TX
Reservoir Engineering Aspects and Forecasting
of Well Performance in Unconventional Resources
Start-Up
Tom BLASINGAME
Petroleum Engineering
Texas A&M University
College Station, TX (USA) —
SPE GCS Reservoir Study Group
2017 Reservoir Technology Forum 3

4. Start-Up — "Progression Cycle" for Unconventional Resources (Gartner Hype Cycles)
< 2 years to 5 years to 10 years
Years to mainstream adoption:
Technology
Trigger
Peak of
Inflated
Expectations
Trough of
Disillusionment
Plateau of Productivity
Slope of Enlightenment
Time
Visibility
Sweet-Spot
Identification
(Statistical Plays)
High IP/
High EUR
"On Demand"
Multi-Well
Pad Development
Microseismic
Monitoring
Early
Completion
Optimization
(Fluid Types/
Stage Placement/
Proppant/etc.)
High Gas
Prices
Low Gas
Strong
Oil Prices
(Liquids-Rich
Systems)
Water Management
High
Acquisition
Costs
Joint
Venture
Funding
Seismic
Exploration
Stakeholder
Concerns
Multi-
Fracture
Horizontal
Wells
Proximity to
Domestic
Market
Decarbonization
Reservoir
Modeling
Acreage
Consolidation
(Acquisitions)
Sweet-Spotting
(Intensive
Well Targeting —
Vertically And Laterally)
Late
(Very Large
Treatments)
Creator: T.A. Blasingame
Created:
Last Revised:
Discussion:
"Progression Cycle" plots are often used to illustrate "product" development.
There is (almost) always a "hype" point for a new technology, then reality sets in.
The perception early on in unconventional development is that IP correlates with EUR.
Unconventional gas was the starting point, liquids-rich systems are the value multiplier.

5. Start-Up — Crowd-Sourcing Exercise for Unconventionals (08-09 Oct 2017)
Most Urgent Technical Challenges:
Completion optimization for enhanced hydrocarbon recovery.
Quantitative description of heterogeneity.
Should we care about the rock permeability?
Increasing water-production/WOR and increasing GOR with time.
Parent-child relationship — depletion impacts on the child well.
Most Important Technical Challenges:
Improving average EUR and productivity.
Multiphase flow at multiple scale of pores/fractures [or GOR(t)].
Placement of wells/clusters/stages for optimal EUR/recovery.
Oil sweet-spot characterization for infill drilling.
EOR technologies for tight oil reservoirs.
Impact/importance of artificial lift selection and operations.
Validity of EUR’s using 30/60/90-days of production data?
Relating the Present with the Past:
Can we/do we obtain consistent results from data analytics?
Improvements in rock characterization, fracturing, and production.
Microseismic needs more fundamental work (happening now?).
Economics, disruptive changes, etc. versus the "herd mentality."
Data/Information Needed and Will be Needed:
Distributed pressure and temperature measurements.
High accuracy bottomhole pressure measurements in every well.
Reservoir simulation as a reliable technology (for SEC).
Continuous and accurate well flowrate measurements.
Need an industry/academia data repository.
Detailed geochemical mapping of intervals to SRV.
Need more deployments of intelligent field technologies.
Well F = Parent Well
"Map View" — Well F is the parent well (C-D-E-F-G-H group).
Final history match of the stress field.
Xu, T., Lindsay, G., Baihly, J., Malpani, R., Ejofodomi, E., & Shan, D. (2017, July 24). Unique Multidisciplinary Approach to Model and Optimize Pad Refracturing in the Haynesville Shale Unconventional Resources Technology Conference.

6. Reservoir Engineering Aspects and Forecasting
SPEE Presentation
02 May 2019 | Brookhaven College, Farmer's Branch, TX
Reservoir Engineering Aspects and Forecasting
of Well Performance in Unconventional Resources
Historical Aspects
Tom BLASINGAME
Petroleum Engineering
Texas A&M University
College Station, TX (USA) —
SPE GCS Reservoir Study Group
2017 Reservoir Technology Forum 6

7. Loss Ratio: (D-parameter)
Historical Aspects — ANCIENT History (Jones)
Loss Ratio: (D-parameter)
Derivative of Loss Ratio: (b-factor)
Example:
Early Example — Johnson/Bollens (1928)
Johnson, R.H. and Bollens, A.L.: "The Loss Ratio Method of Extrapolating Oil Well Decline Curves," Trans. AIME (1927) 77, 771.
Historical Analysis: Johnson/Bollens (1928)
Johnson and Bollens proposed a plot of the loss ratio versus time.
A linear plot of loss ratio versus time implies that b(t) = constant (hyperbolic decline).
A constant loss ratio versus time implies that b(t) = 0 (exponential decline).

8. Historical Aspects — ANCIENT History (Jones)
Jones, P.J.: "Estimating Oil Reserves from Production-Decline Rates," Oil and Gas Jour. (Aug. 20, 1942) 43.
Power-law trend of D-parameter data
Constant b-parameter (hyperbolic)
Changing b-parameter (power-law exponential)
Power-Law Exponential: (2008)
Fig. 37 — Variable rate of decline.
Historical Analysis: Jones (1942)
Log[decline rate] versus log [time] validates the power-law exponential concept.
Jones saw that this function had relevance, but did not demonstrate the approach.
Interesting that this was 66 years before the PLE relation was observed.

9. Historical Aspects — Blasingame — Rate Transient Analysis
Fetkovich Decline Type Curve — Arps Stems.
Fetkovich Decline Type Curve — Analytical Stems.
Fetkovich Decline Type Curve — Composite Curve (original curve).
Fetkovich Decline Type Curve — Example (Well 13 — SPE ).

10. Historical Aspects — Blasingame — Rate Transient Analysis
a. "History Plot" — Gas rate and computed bottomhole pressures.
b. "Edit Plot" — Gas productivity Index and gas material balance pseudotime, edited data are shown as open symbols (circa 1998).
c. "WPA Plot" — (original RTA) Unfractured well model.
d. "WPA Plot" — (original RTA) Fractured well model (infinite conductivity case).
Creator: T.A. Blasingame
Created: ~
Discussion:
Barnett Shale example case (surface rates/computed bottomhole pressures, vertical well).
"Data Edit" plot is actually a diagnostic plot (note trends).
WPA (RTA) type curve matches for an unfractured well and a fractured well.
This was the starting point for "modern" unconventional oil and gas development.

11. Reservoir Engineering Aspects and Forecasting
SPEE Presentation
02 May 2019 | Brookhaven College, Farmer's Branch, TX
Reservoir Engineering Aspects and Forecasting
of Well Performance in Unconventional Resources
Linear Flow Analysis?
Tom BLASINGAME
Petroleum Engineering
Texas A&M University
College Station, TX (USA) —
SPE GCS Reservoir Study Group
2017 Reservoir Technology Forum 11

12. (Formation) Linear Flow — Theory (q/Dp form)
Solution for a Single Fracture: (transient linear flow)
Solving for flowrate divided by pressure drop, we have …
Note:
These solutions are only valid for transient linear flow [i.e., the case of non-interfering pressure distributions (due to the fractures)].
Additive Fractures: (transient linear flow) →

13. (Formation) Linear Flow — Dp/q versus SQRT[t ] Plot
Formation Linear Flow: (t = t or tmb (material balance time))
Log-log diagnostic plot: log[Dp/q] versus log[t ] (slope = -1:2)
"Traditional" plot: Dp/q versus SQRT[t ] (straight-line portion)
Extrapolation of rate using a linear flow model will over-predict EUR…
Governing Relation:
Log[Reciprocal Productivity Index]
Log[Material Balance Time]
Linear Flow Region
(1/2 slope)
Deviation from Linear Flow
Apparent 1/1 slope
(most likely liquid-loading) 2 1
Reciprocal Productivity Index
Square Root of Material Balance Time
Linear Flow
Region
Deviation from
Linear Flow Region
melf
a. (Log-log plot): Reciprocal productivity index versus material balance time, multiple wells.
b. (Square root plot): Reciprocal productivity index versus square root of material balance time, multiple wells.

14. (Formation) Linear Flow — Multi-Fractured Horizontal Wells
Transient Linear Flow Relation:
Use of Hyperbolic Flow Relation
to Represent Transient Linear Flow:
Creator: T.A. Blasingame
Created: ~2017
Discussion:
MFHW model is the "master" solution for unconventional wells.
Diagnostics can be obscured by clean-up and liquid-loading.
Very significant time involved for observing a particular flow regime (k = 50 nd).

15. Reservoir Engineering Aspects and Forecasting
SPEE Presentation
02 May 2019 | Brookhaven College, Farmer's Branch, TX
Reservoir Engineering Aspects and Forecasting
of Well Performance in Unconventional Resources
Time-Rate Thoughts
Tom BLASINGAME
Petroleum Engineering
Texas A&M University
College Station, TX (USA) —
SPE GCS Reservoir Study Group
2017 Reservoir Technology Forum 15

16. Time-Rate Analysis — Suite of Plots — Shale Gas Example
Slope = 1:1
b = 2
b = 1
qg versus t D-parameter versus time b-parameter versus time
Slope = 1:2
Slope = 1:2
Dp/qg versus Gp/qg qg/Dp versus Gp/qg Dp/qg versus SQRT(t)
Discussion:
Basic diagnostic suite of plots.
D(t) and b(t) plots are critical for understanding time-rate behavior.
SQRT(t) plots can be deceptive. (i.e., we see what we want to see)

17. Time-Rate Analysis — D(t) and b(t) Diagnostics — b(t) Play-by-Play
Creator: D. Ilk
Created: ~2017
b = 1
b = 2
b = 1
b = 2
Discussion:
A constant "b(t)" value is unlikely for more than just a few months.
Decline in "b(t)" in some/most cases, behavior can be considered "power-law."
Conceptually, this decline in "b(t)" can be used to predict EUR(t).

18. Discussion: Time-Rate Analysis — Continuous EUR
Creator: D. Ilk
Created: ~2017
"b(t) vs. time" — decline exponent versus time (note segments).
"b vs. time" — b-value constant for a given section.
"qo(t) vs. cumulative oil" — note the extrapolated trends.
"EUR vs. time" — EUR presented versus time for a given segment.
Discussion:
Illustration of changing EUR as a function of time due to changing decline exponent (b).
b(t) data are (relatively) well-behaved, selected constant b-values for a given segment.
Declining EUR with time is characteristic of the declining b(t) function with time.

19. Reservoir Engineering Aspects and Forecasting
SPEE Presentation
02 May 2019 | Brookhaven College, Farmer's Branch, TX
Reservoir Engineering Aspects and Forecasting
of Well Performance in Unconventional Resources
Time-Rate Models
Tom BLASINGAME
Petroleum Engineering
Texas A&M University
College Station, TX (USA) —
SPE GCS Reservoir Study Group
2017 Reservoir Technology Forum 19

20. Work Path — Analysis of Well Performance
Completions
Production
Reservoir Fluids
Geomodel
Time-
Rate
Rate-
Pressure
Reservoir
Model
Model: Time-Rate
Basis: Proxy model
Predictions
EUR
Correlations
Time: Minutes/well
Model: Time-Rate-Pressure
Basis: Analytical/Numerical
EUR/SRV
Estimate Properties
Time: ~1 hour/well
Time
Rates
Basis: Full Numerical
Flow Mechanisms
Time: Days to weeks/well
Creator: T.A. Blasingame
Created: 2015

21. Time-Rate Models — Modified-Hyperbolic Relation
Modified-Hyperbolic Rate Relation:
Slope = 1:2
Linear Flow
(b = 2)
b = 2

22. Time-Rate Models — Power-Law Exponential Relation
Power-Law Exponential Rate Relation:
Decline Function: D(t)
Hyperbolic Function: b(t)
Ilk, D., Rushing, J. A., Perego, A. D., and Blasingame, T. A. (2008) Exponential vs. Hyperbolic Decline in Tight Gas Sands: Understanding the Origin and Implications for Reserve Estimates Using Arps Decline Curves. Society of Petroleum Engineers. doi: / MS
Ilk, D., Perego, A. D., Rushing, J. A., and Blasingame, T. A. (2008) Integrating Multiple Production Analysis Techniques To Assess Tight Gas Sand Reserves: Defining a New Paradigm for Industry Best Practices. Society of Petroleum Engineers. doi: / MS x

23. Reservoir Engineering Aspects and Forecasting
SPEE Presentation
02 May 2019 | Brookhaven College, Farmer's Branch, TX
Reservoir Engineering Aspects and Forecasting
of Well Performance in Unconventional Resources
Other Thoughts on Reservoir Configurations
Tom BLASINGAME
Petroleum Engineering
Texas A&M University
College Station, TX (USA) —
SPE GCS Reservoir Study Group
2017 Reservoir Technology Forum 23

24. Other Thoughts on Reservoir Configurations — Olorode (SPE 152482)
Discussion:
Reduction from linear flow (half-slope) for CfD,SecFrac < 10.
Model trends are also observed in field data.
Secondary fracture concept may be useful in optimizing fracture design.

25. Other Thoughts on Reservoir Configurations — Mhiri (TAMU 2014)
Sample random-walk fracture pattern cases.
3-D
rendering.
Discussion:
After a random number steps, the fractures may bifurcate (split).
b-derivative of the mass flowrate is the diagnostic function.
b-derivative is 0.55 (mono-branch) and 0.70 (quad-branch) for the cases.

26. Discussion: SRV (Stimulated Reservoir Volume)
Other Thoughts on Reservoir Configurations — Stimulation
"You only produce from what you fracture …" Anonymous
Individual Fractures from Individual Perforation Clusters
Complex Fractures from Individual Perforation Clusters
Discussion:
SRV (Stimulated Reservoir Volume)
Build Complexity → Slickwater
Build Conductivity → Hybrid/Gel
Future Stimulation Challenges:
"Rubble-ize" the reservoir?
"Pulverize" the reservoir?
Do this with little or no water?
Project Rulison (1971) Stimulation using Atomic Weapons

27. Other Thoughts on Reservoir Configurations — Broussard (TAMU 2013)
Geometry: (radial composite system)
Composite, cylinder consists of two regions:
Inner region is stimulated (k = power-law function).
Outer region is unstimulated and homogeneous.
Horizontal well centered in a cylindrical volume.
Wellbore spans the entire length of the reservoir.
Radial flow only.
xf = rs = 50 ft, wkf = 10 md-ft xf = rs = 25 ft, wkf = 10 md-ft
Performance of radial composite system very similar
to that for a multi-fracture horizontal well solution.

28. Reservoir Engineering Aspects and Forecasting
SPEE Presentation
02 May 2019 | Brookhaven College, Farmer's Branch, TX
Reservoir Engineering Aspects and Forecasting
of Well Performance in Unconventional Resources
Reservoir Pressure
Tom BLASINGAME
Petroleum Engineering
Texas A&M University
College Station, TX (USA) —
SPE GCS Reservoir Study Group
2017 Reservoir Technology Forum 28

29. Reservoir Pressure — (pwf)meas vs
Reservoir Pressure — (pwf)meas vs. Time, Multi-Well Interference (Source: SPE )
Scott, K. D., Chu, W.-C., and Flumerfelt, R. W. (2015) Application of Real-Time Bottom-Hole Pressure to Improve Field Development Strategies in the Midland Basin Wolfcamp Shale. Unconventional Resources Technology Conference. doi: /URTEC

30. Reservoir Pressure — PTA Cases in Bakken (Oil Shale) [SPE 162473 (Kurtoglu)]
[1:3 slope]
[≈2:5 slope]
Kurtoglu, B., Torcuk, M.A., & Kazemi, H. (2012) Pressure Transient Analyses of Short and Long Duration Well Tests in Uncon-ventional Reservoirs. Society of Petroleum Engineers. doi: / MS.

31. Reservoir Pressure — Quantifying Pressure Interference [SPE 191407 (Chu)]
Concept: The higher the Dp/(2Dp') value, the higher the "connectivity" between wells.
Pressure response due to Well 3H
being "put-on-production" (or POP'd).
Chow Pressure Group (pressure derivative function)
For all for 4 wells due to Well 3H being "POP'd."
Pressure interference response in Well 4H. Pressure interference response in Well 6H. Pressure interference response in Well 5H.
(due to Well 3H POP) (due to Well 3H POP) (due to Well 3H POP)
Chu, W., Scott, K., Flumerfelt, R., & Chen, C.-C. (2018) A New Technique for Quanti-fying Pressure Interference in Fractured Horizontal Shale Wells. Society of Petro-leum Engineering doi: / MS

32. Reservoir Engineering Aspects and Forecasting
SPEE Presentation
02 May 2019 | Brookhaven College, Farmer's Branch, TX
Reservoir Engineering Aspects and Forecasting
of Well Performance in Unconventional Resources
Time-Rate Analysis — A Few Parting Thoughts...
Tom BLASINGAME
Petroleum Engineering
Texas A&M University
College Station, TX (USA) —
SPE GCS Reservoir Study Group
2017 Reservoir Technology Forum 32

33. Time-Rate Analysis — A Few Parting Thoughts... (1 of 5)
You are tasked with creating
your own time-rate model...
Conceptually,
where do you start?
Logarithm of Rate
Time

34. Time-Rate Analysis — A Few Parting Thoughts... (2 of 5)
You are tasked with creating
your own time-rate model...
Now What?
Logarithm of Rate
Time

35. Time-Rate Analysis — A Few Parting Thoughts... (3 of 5)
You are tasked with creating
your own time-rate model...
Logarithm of Rate
Grrrrhhh
Time

36. Time-Rate Analysis — A Few Parting Thoughts... (4 of 5)
You are tasked with creating
your own time-rate model...
Logarithm of Rate
Approximate by a sum of exponentials?
Time

37. Time-Rate Analysis — A Few Parting Thoughts... (5 of 5)
You are tasked with creating
your own time-rate model...
Logarithm of Rate
Approximate by a sum of exponentials?
Questions:
So what? (my favorite question)
What do D(t) and b(t) look like? (you can't just consider q(t)).
What are the physics behind (any) proposed model?
Comments:
You must be prepared to consider q(t), D(t), and b(t).
This is a simplistic example, but you must think about what (if any) theory exists...
What is the objective of any/all extrapolation models? (... consistency)
Time

38. Reservoir Engineering Aspects and Forecasting
SPEE Presentation
02 May 2019 | Brookhaven College, Farmer's Branch, TX
Reservoir Engineering Aspects and Forecasting
of Well Performance in Unconventional Resources
End of Presentation
Tom BLASINGAME
Petroleum Engineering
Texas A&M University
College Station, TX (USA) —
SPE GCS Reservoir Study Group
2017 Reservoir Technology Forum 38

39. Reservoir Engineering Aspects and Forecasting
SPEE Presentation
02 May 2019 | Brookhaven College, Farmer's Branch, TX
Reservoir Engineering Aspects and Forecasting
of Well Performance in Unconventional Resources
Something Extra
Tom BLASINGAME
Petroleum Engineering
Texas A&M University
College Station, TX (USA) —
SPE GCS Reservoir Study Group
2017 Reservoir Technology Forum 39

40. Personal Mementos — Tom Blasingame
Napkin Art (drawn on recent flights) Marriage Counseling (New Zealand) December in College Station My Favorite Place/My Best Friends
My Other Job (as a Potato Picker (NZ)) My Proudest Professional Achievement Family in "Hobbiton" View from Our NZ Home

41. Professional Biography — Tom Blasingame
Tom Blasingame is a Professor and is the holder of the Robert L. Whiting Professorship in the Department of Petroleum Engineering at Texas A&M University in College Station Texas. He holds B.S., M.S., and Ph.D. degrees from Texas A&M University — all in Petroleum Engineering. In teaching and research activities Blasingame focuses on petrophysics, reservoir engineering, analysis/interpretation of well performance, unconventional resources, and technical mathematics.
Blasingame's research efforts deal with topics in applied reservoir engineering, reservoir modeling, and production engineering. Blasingame has made numerous contributions to the petroleum literature in well test analysis, analysis of production data, reservoir management, evaluation of low/ultra-low permeability reservoirs, and general reservoir engineering (e.g., hydrocarbon phase behavior, natural gas engineering, inflow performance relations, material balance methods, and field studies). To date (May 2019), Blasingame has graduated 67 M.S. (thesis), 34 M.Eng. (report, non-thesis), and 14 Ph.D. students, and he has performed several major field studies involving geology, petrophysics, and engineering tasks.
Blasingame is a member of the Society of Petroleum Engineers (SPE), the Society for Exploration Geophysicists (SEG) and the American Association of Petroleum Geologists (AAPG). Blasingame is a Distinguished Member of the Society of Petroleum Engineers (2000) and he is a recipient of the SPE Distinguished Service Award (2005), the SPE Uren Award (for technology contributions before age 45) (2006), the SPE Lucas Medal (SPE's preeminent technical award) (2012), the SPE DeGolyer Distinguished Service Medal (2013), the SPE Distinguished Achievement Award for Petroleum Engineering Faculty (2014), and SPE Honorary Membership (2015). Blasingame has served as an SPE Distinguished Lecturer ( ) and was the SPE Technical Director for Reservoir ( ). Blasingame has prepared approximately 160 technical articles; and he has chaired numerous technical committees and technical meetings. Blasingame also served as Assistant Department Head (Graduate Programs) for the Department of Petroleum Engineering at Texas A&M from 1997 to 2003, and Blasingame has been recognized with several teaching and service awards from Texas A&M University.

42. Current Students — Tom Blasingame
M.S. Projects: (start-up/active/closure)
Anatraksakul Transformational Decomposition Model for MF Horizontal Wells (active)
Anno Project TBD (coursework)
Bryan Mechanistic Model Validation for DCA in Uncon. Reservoirs (active)
Chingulprasan Laplace Transform Data Methods (closure)
Fonseca Non-Parametric Correlation of Well Performance Data (active)
Fulford Deconvolution using Bayesian Graphical Models (active)
Gorditsa Mechanistic Model Validation for DCA in Unconventional Reservoirs (active)
Jin Rate Transient Analysis in Unconventional Tight-Oil Reservoirs (active)
Nguyen Pressure Transient Analysis in Shales (start-up)
Pradhan Well Spacing Optimization using Production & Pressure Data (start-up)
Ph.D. Projects: (start-up/active/closure)
Garcia Mechanistic Behavior for GOR in Unconventional Reservoirs (active)
Kou Dynamic Modeling of Proppant Transport in Fractures (active)
Moridis Reserves, A&D, and Assessment of Unconventional Reservoirs (active)
Perez-Valdez Fractured Horizontal Wells in Fractal Reservoirs (closed)
M.Eng. Students: (those actively engaged and/or working on projects)
Newberry Regional Evaluation of Delaware Basin (Wolfcamp) (closure)
Pinmentel Extraction of Elemental Lithium from Produced Waters (active)
White Completion Aspects of Well Performance (Delaware Basin) (2019)