MétaCan
Menu
Back to cohort
Record W4248193340 · doi:10.2523/75708-ms

Applied Reservoir Characterization for Maximizing Reserve Growth and Profitability in Tight Gas Sands: A Paradigm Shift in Development Strategies for Low-Permeability Gas Reservoirs

2002· article· en· W4248193340 on OpenAlexaboutno aff
P.D. McKinney, J. A. Rushing, L. Allen Sanders

Bibliographic record

VenueProceedings of SPE Gas Technology Symposium · 2002
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexTight gasCitationFossil fuelPetroleum engineeringComputer scienceMining engineeringGeologyBusinessEngineeringLibrary scienceHydraulic fracturing

Abstract

fetched live from OpenAlex

Applied Reservoir Characterization for Maximizing Reserve Growth and Profitability in Tight Gas Sands: A Paradigm Shift in Development Strategies for Low-Permeability Gas Reservoirs P.D. McKinney; P.D. McKinney Anadarko Canada Corp. Search for other works by this author on: This Site Google Scholar J.A. Rushing; J.A. Rushing Anadarko Petroleum Corp. Search for other works by this author on: This Site Google Scholar L.A. Sanders L.A. Sanders Anadarko Petroleum Corp. Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Gas Technology Symposium, Calgary, Alberta, Canada, April 2002. Paper Number: SPE-75708-MS https://doi.org/10.2118/75708-MS Published: April 30 2002 Connected Content Related to: Maximizing Reserves Growth and Profitability in Tight Gas Sands Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation McKinney, P.D., Rushing, J.A., and L.A. Sanders. "Applied Reservoir Characterization for Maximizing Reserve Growth and Profitability in Tight Gas Sands: A Paradigm Shift in Development Strategies for Low-Permeability Gas Reservoirs." Paper presented at the SPE Gas Technology Symposium, Calgary, Alberta, Canada, April 2002. doi: https://doi.org/10.2118/75708-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Unconventional Resources Conference / Gas Technology Symposium Search Advanced Search AbstractThis paper proposes an alternative tight gas sand reservoir development strategy that allows operators to maximize gas recovery and net present value while minimizing capital expenditures. Our approach employs a "parallel" development technique where many reservoir performance evaluation and field development activities are performed almost concurrently, thus allowing an operator to identify the optimum well spacing early in the field's life. Successful application of this "parallel" development approach requires a coordinated reservoir description and characterization plan, reservoir modeling, and reservoir monitoring and surveillance. We also illustrate the economic advantages of our strategy with examples from a hypothetical tight gas sand reservoir.IntroductionUnconventional gas resources - fractured gas shales, coalbed methane and tight gas sands - constitute a significant percentage of the U.S. natural gas resource and offer tremendous potential for future reserve growth and production. Of the total unconventional gas resource base, tight gas sands have the largest proven potential. According to a recent study by the Gas Technology Institute,1 tight gas sands in the U.S. comprise 69% of gas production from all unconventional gas resources and account for 19% of the total gas production from both conventional and unconventional sources. The same study1 estimates total producible tight gas sand resources exceed 600 tcf, while economically recoverable reserves are 185 tcf.Similar to conventional oil and gas systems, tight gas sands are often characterized by complex geological and petrophysical systems as well as heterogeneities at all scales. Unlike conventional reservoirs, however, tight gas sands often exhibit unique gas storage and producing characteristics requiring more dense well spacing. As a result, the key to effectively exploiting low-permeability gas reservoirs is to develop the field at a sufficiently dense well spacing to maximize gas recovery while avoiding drilling more wells than is necessary, i.e., develop the field at the optimum well spacing. Furthermore, capital expenditures are minimized while profits are maximized when that optimum well spacing is achieved early in the field's life. Unfortunately, development of most tight gas sand fields typically follows a "series" approach where the initial development activity is followed by lengthy periods of production performance evaluation and surveillance separated by periods of additional drilling and down spacing. Under these conditions, the optimum field spacing may not be achieved until late in the field life.An example of a tight gas sand reservoir developed using a "series" approach is the Carthage Field located in Panola County, Texas. The field produces from the low-permeability upper Cotton Valley sands at depths from 9,000 to 10,000 ft. Sand porosities in the pay intervals range from 4% to 12% while the effective gas permeability is generally less than 0.01 md. Discovered in 1966, the field was developed initially on 640-acre well spacing. Following evaluation of the production performance, subsequent reductions in well spacing to 320 and 160 acres per well were allowed in 1981 and 1987, respectively. Field rules changes allowing optional 80-acre well spacing were implemented in 1996. A reservoir characterization and simulation study conducted almost thirty years after discovery2 suggested optimum field spacing might be less than 80 acres in some areas. Yet some operators have only recently begun infill drilling to 80-acre spacing. The field production and well development history are summarized in Fig. 1. Keywords: production data, development strategy, reserve growth, evaluation, water saturation, modeling & simulation, upstream oil & gas, permeability, paradigm shift, profitability Subjects: Formation Evaluation & Management This content is only available via PDF. 2002. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.236
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPE Gas Technology SymposiumSame topicReservoir Engineering and Simulation MethodsFrench-language works237,207