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Record W1993542321 · doi:10.2118/114778-pa

Predicting Sorption-Induced Strain and Permeability Increase With Depletion for Coalbed-Methane Reservoirs

2009· article· en· W1993542321 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSPE Journal · 2009
Typearticle
Languageen
FieldEngineering
TopicCoal Properties and Utilization
Canadian institutionsUniversity of Calgary
FundersCommonwealth Scientific and Industrial Research OrganisationZhejiang UniversityOklahoma State University
KeywordsCoalbed methaneSorptionPermeability (electromagnetism)MethanePetroleum engineeringShrinkageAdsorptionCoalMaterials scienceThermodynamicsGeotechnical engineeringChemistryGeologyCoal miningComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Summary It is well known that absolute permeability changes occur in coalbed methane (CBM) reservoirs during primary depletion or enhanced recovery/CO2 sequestration operations. Sorption-induced strain in CBM reservoirs, also known as matrix shrinkage or swelling, may dominate permeability changes at low pressures, as is the case for CBM wells undergoing primary depletion in the Fruitland coal fairway of the San Juan basin. Several analytical models have been developed to predict changes in coal permeability as a function of stress and sorption. Most models, however, utilize an empirical method for estimating sorption-induced strain. Recently, a theoretical model for sorption-induced strain was developed and applied to single-component adsorption/strain experimental data. The new model was developed from basic thermodynamic principles and is more predictive than the empirically based approaches. In this paper, the theoretical model is expanded to incorporate multicomponent adsorption models that are more rigorous, and sometimes more accurate, than the commonly applied extended Langmuir (EL) equation. This improves predictions of multicomponent gas sorption-induced strain, as demonstrated by comparison to experimental data. The new sorption-induced strain model is then used to calculate the sorptionstrain component of the popular Palmer and Mansoori (P&M) equation, which, in turn, can be used to model permeability changes during both primary (single- or multicomponent gas) and enhanced recovery operations. Finally, the coupled sorption-strain/permeability model, incorporated into an analytical simulator, is used to predict and match permeability growth in a producing CBM well in the Fruitland coal fairway, which has a binary (CH4 + CO2) sorbed/produced gas composition. Matches to field-derived permeability growth using the new model are accurate but nonunique because of the lack of available data, particularly rock mechanical properties. Given the availability of rock mechanics and adsorption isotherm data, the rigorous thermodynamic basis of the new model should allow for more accurate predictions of coalbed permeability changes, but further testing is required.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.643
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.230
Teacher spread0.214 · 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