Best Practices for Reserves Estimation in Unconventional ... · PDF fileBest Practices for Reserves Estimation in Unconventional Reservoirs ... Well performance will vary, ... Best

Best Practices for Reserves Estimation in Unconventional Reservoirs —

Present and Future Considerations

Tracy HECKMAN, Anadarko Petroleum CorporationGrant OLSEN, Pressler Petroleum Consultants

Kerry SCOTT, Pioneer Natural ResourcesBernard SEILLER, Total

Marcia SIMPSON, EXCO ResourcesTom BLASINGAME, Texas A&M University

Advancement of KnowledgeSlide 2

Estimating Reserves in Unconventional Reservoirs:●It’s early●It’s different●It’s good to learn from others●It’s good to have guidance●It’s good to have a vision

We advance our knowledge by application of mathematics and physical science, trial and error, and observation.

Heckman (novice philosopher)

(www.eia.gov/analysis/studies/usshalegas/pdf/usshaleplays.pdf)

"It's Early"(Use Caution)




Slide 4

It's Early — Horizontal Wells as the Enabler (1/2)

Slide 5

It's Early — Horizontal Wells as the Enabler (2/2)

Slide 6It's Early — Tight Oil Will Dominate in 10-15 Years (U.S.)

From the Authorities: Oil● Tight oil (shale and chalk)

production projected to rise sharply over next decade.

●U.S. Energy Information Administration (EIA) AEO 2013 Early Release Overview.

U.S. Energy Information Administration(AEO 2013 Early Release Overview)

U.S. domestic crude oil production by source, 1990-2040 (millions of barrels/day)

Slide 7

From the Authorities: Gas● Shale gas is projected to be

the most significant U.S. growth play over the next ~30 years.

●Considerable uncertainty in size and economics of shale gas resources.

●Most shale gas wells have been drilled in the last few years, leaving considerable uncertainty regarding long-term productivity.

●U.S. Energy Information Administration (EIA) AEO 2013 Early Release Overview.

It's Early — Lots of Room to Grow (U.S.)

U.S. Energy Information Administration(AEO 2013 Early Release Overview)

U.S. Dry natural gas production by source,1990-2040 (trillions of cubic feet per year)

For many unconventional reservoirs, (particularly shales) it's early in the…●Development life-cycle ●Production life-cycle●Learning life-cycle

We are in a period of significant uncertainty!●Production forecasts and ultimate recovery●Drilling and completion techniques●Optimum well spacing (interference)● Impact on company portfolio of opportunities●Project financing, investor confidence, regulatory harmony

It's Early — There's Uncertainty…Slide 8

"It's Different"(We May Not Know What We Don't Know…)




It's Different — DefinitionsSlide 10

Conventional Reservoirs Unconventional Reservoirs (Shale)● Localized structural trap ● "Continuous-type" deposit● External HC sourcing ● Self-sourced HC● Hydrodynamic influence ● Minimal hydrodynamic influence● Porosity important ● Porosity may not be important● Permeability > 0.1 md ● Permeability << 0.1 md● Permeability ≠ f(p) ● Permeability = f(p)● Traditional phase behavior (PVT) ● Complex (HP/HT) PVT● Minimal extraction effort ● Significant extraction effort● Significant production history ● Limited production history● Often late development life-cycle ● Early development life-cycle● Few wells for commerciality ● Many wells for commerciality● Base reserves on volumetrics ● Base reserves on analogs ● Assess entire prospect before drilling ● Prospect driven by drilling ● Boundary-dominated flow (months) ● No boundary-dominated flow

● Traditional reserves methods ● Traditional reserves methods

Slide 11

●Challenges:—No industry standard tech-

niques for assessing uncon-ventional exploration plays.

—Stimulation is the major challenge (cost/technology).

—Fractures (induced or natural) are critical producibility factors.

—Success is judged based on production results.

It's Different — Challenges and Methodology

●Methodology:—Expect the unexpected. Well

performance will vary, despite similar drilling/completion practices, well spacing, etc.

—Unconventional plays are "statistical," many wells must be drilled to assess potential.

—Drilling too few wells is likely to lead to a bad decision.

" It’s Good to Learn from Others "(Industry Survey: Development of "Most Likely"

Production Forecasts from Unconventional Reservoirs)




Industry SurveySlide 13

Objective of the Survey:●Collect and communicate industry "Best Practices:"— "Most Likely " forecast (expected technical outcome).— Reasonable " Low Side " forecast.

●Criteria:— Survey of individuals.— Anonymous.— Independent of regulatory classification systems.


Administration of the Survey:●Design:— Designed by project team.— Applicable to unconventional

reservoirs.— Vetted and previewed survey

with all participants.— Focused on current practices in

developed areas.— Intended participants selected

from all facets of E&P sector.●Structure:— Survey delivered by secure,

web-based system.— 13 core questions (rate-time

analysis/forecasting).— 17 optional questions

(confidence/risks/undeveloped reserves/probabilistics). "User name and password…"

"My opinion? Are you sure I'm supposed to have one?"


Participation:●Survey Particulars:— 39 surveys submitted.

●Survey responses:— [33 responses] Shale Gas (i.e., Eagle Ford, Marcellus, etc.).— [17 responses] Shale Oil (i.e., Bakken, etc.).— [17 responses] Tight Gas (i.e., Cotton Valley, etc.).— [12 responses] Tight Oil (i.e., Spraberry, etc.).

Slide 16

Primary Techniques for Forecasting Existing Shale Gas Wells:

Industry Survey

●Arps' Method:— Single most often used

method.— Often limited with a

maximum value of the Arps' b-factor.

●Combination:— Arps' method with

alternative cross-check.— Implementation varies,

but general practice is to constrain EUR.

●RTA:— Relatively uncommon,

need for higher quality data.

— Requires time-rate-pressure data.

Slide 17

Forecasting Undeveloped Shale Gas Wells:

Industry Survey

●Analog Type Curve:— Most popular approach.— Need a relevant analog.— Need a big database.

●Simulation:— Either basic or exhaustive

datasets can be used.— Tailor model to needs:

■ Basic model for screening studies.

■ Full "mechanistic" models for evaluating well completion, well spacing, PVT, etc.

Slide 18

Time-Rate Analysis:

Industry Survey

●Comment: (from survey)— Arps' DCA methodology can be

aggressive if unconstrained. "Work-around" is the "Modi-fied-Hyperbolic" (hyperbolic-exponential model),

— Other models mentioned:■ "Stretched-Exponential"■ "Duong" (early-time) model

●Suggestions: (from survey)— Double hyperbolic model (with

terminal exponential).— Attempt to represent physical

behavior of well-reservoir system (SRV + non-SRV).

● Last Words:— What we have works (when

constrained).— Some users want more models

and better diagnostics.

Slide 19

Best Practices:

Industry Survey

●New Wells:— Require 3-24 months of production performance.— Exception — maintain "shape" of type curve and fit to actual IP.

●EUR:— Cross-check estimates against various/alternate methodology(s).— Ensure "reasonableness" of results (confidence limits).

●Reserves Methodologies:— Time-Rate (DCA/Arps) — existing plays.— Time-Rate-Pressure (RTA) — existing plays.— Analogs — new plays.— Reservoir simulation (mechanistic) — existing and new plays.— Probabilistic (stochastic simulations) — existing and new plays.

"It’s Good to Have Guidance"(Statistical Analysis of Public Production Data —

Dry Horizontal Shale Gas Wells ONLY)[all data obtained from publicly available sources]




Statistical Analysis of Public Production DataSlide 21

Objectives of the Public Data Study:●Use Arps' "Modified Hyperbolic" relation:

●Establish analysis limits:— 0.5 < b < 2.0.— Dlim = 10 percent (terminal exponential).— Abandonment Rate = 50 MSCF/D.

●Regression Approach:— Automated data fitting using constraints given above.— All results quality-checked, outliers discarded.

●Provide guidance and limits with graphical results:— P50 rate vs. time with observations to generate confident EUR.— Comparison of P10/P50/P90 EURfinal-values.

)( ]exp[

)( )1()(

limexp,

/1hyp,

t*ttDq

t*ttbD

qtq

i

bi

i

[all data obtained from publicly available sources — Dry Horizontal Shale Gas Wells ONLY]

Slide 22

P50 Well Gas Rate Trends:

Comment:Left plot yields time required to estimate EUR (~12-32 months).The "hyperbolic" (or "constant b") flow regime is required to estimate EUR.

Statistical Analysis of Public Production Data[all data obtained from publicly available sources — Dry Horizontal Shale Gas Wells ONLY]

Slide 23

P90/P50/P10 EUR Comparisons: (Modified Hyperbolic Model with 30 year max life)

Comment: Results are “auto-fitted” and should be considered reasonably accurate. Results will vary when data are segregated by geological area, completion practices, spacing, etc. Analyses represent an attempt to quantify the RANGE of values.

Statistical Analysis of Public Production Data[all data obtained from publicly available sources — Dry Horizontal Shale Gas Wells ONLY]

"It’s Good to Have a Vision"(Vision for Reserves Estimation — The Next 10 Years)




Slide 25

Models for Production Forecasting:●Most likely scenarios:— Statistical models will remain an alternative to reservoir models.— Analytical and numerical models will focus on SRV/beyond SRV.— Numerical models will use more microseismic and geomechanics.

●Developed Reserves: Decline Curve Analysis (DCA)— (present) DCA models are useful to relate "SRV"-based reserves.— (future) Beyond the "SRV" will require a reservoir model.

●Developed Reserves: Probabilistic Methods— Probabilistic (non-deterministic) reserves can provide insight.— Probabilistic models will account for changes in completions.— Probabilistic approach will continue to evolve...

●Undeveloped Reserves:— Data mining methods will yield insight into EUR trends.— EUR = f(geomechanics, geology, and engineering data ).— Seismic can be/will be used to calibrate geostatistical models.— Geomechanical properties are/will be the weak link.

Vision — Models for Production Forecasting

Slide 26

Integration of the SRV: Fracture Models●Assessment of SRV Architecture:— [need] Modeling of SRV flow (block size + fracture conductivity).— [need] Improved modeling of hydraulic fracture growth models.— [challenge] Geomechanics and formation characterization.

Vision — Integration of the SRV (1/2)

Microseismic

Fracture DistributionModel

Simulation Model

Comment:■ We assume (Darcy) flow physics — and we

force performance to match "old" models.■ We assume we understand the nature of the

(natural and induced) fracture systems.

Slide 27

Integration of the SRV: Matrix Contribution●Matrix Contribution within the SRV:— [need] Storage, transport, PVT for unconventional systems.— [need] Physical experiments — porosity, adsorption, permeability.— [need] Numerical experiments — molecular simulation/up-scaling.

Vision — Integration of the SRV (2/2)

Geology

Nano-Scale BehaviorConcept Model

Comment:■ Need to redefine the fundamentals.■ Need more precise experiments.■ Can we model instead of measure?



Summary




Slide 29

Summary:This work provides orientation to industry reserves practices via acomprehensive survey — the major conclusion of which is thatindustry will continue to utilize traditional reserves methods (withtighter constraints) while continuing to develop methods/practiceswhich will provide a unique characterization of reserves for un-conventional reservoir systems.

This work also provides a statistical study derived from approxi-mately 25,000 shale gas wells. This work confirms the use of theArps' "modified hyperbolic" model and provides statistical results(EUR's and other DCA results) on a play-by-play basis.

Conclusions:● Industry Survey:— DCA will remain a primary reserves tool (and will evolve).— Definition of simulation models will likely rely more on analogs.

●Reserves Analysis:— DCA is not fully representative (and must be constrained).— Time-Rate-Pressure analyses will become common (e.g., RTA).

Summary and Conclusions



End of PresentationTracy HECKMAN, Anadarko Petroleum Corporation

Grant OLSEN, Pressler Petroleum ConsultantsKerry SCOTT, Pioneer Natural Resources

Bernard SEILLER, TotalMarcia SIMPSON, EXCO Resources

Tom BLASINGAME, Texas A&M University

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Best Practices for Reserves Estimation in Unconventional ... · PDF fileBest Practices for Reserves Estimation in Unconventional Reservoirs ... Well performance will vary, ... Best