A Model for Changes in Coalbed Permeability During Primary and Enhanced Methane Recovery
Bibliographic record
Abstract
Summary The natural fracture network of a dual-porosity coalbed reservoir is made up of two sets of orthogonal, and usually subvertically oriented, cleats. Coalbed permeability has been shown to vary exponentially with changes in the effective horizontal stress acting across the cleats through the cleat-volume compressibility, which is analogous to pore compressibility in porous rocks. A formulation for changes in the effective horizontal stress of coalbeds during primary methane recovery, which includes a Langmuir type curve shrinkage term, has been proposed previously. This paper presents a new version of the stress formulation by making a direct link between the volumetric matrix strain and the amount of gas desorbed. The resulting permeability model can be extended readily to account for adsorption-induced matrix swelling as well as matrix shrinkage during enhanced methane recovery involving the injection of an inert gas or gas mixture into the seams. The permeability model is validated against a recently published pressure-dependent permeability multiplier curve representative of the San Juan basin coalbeds at post-dewatering production stages. The extended permeability model is then applied successfully to history matching a micropilot test involving the injection of flue gas (consisting mainly of CO2 and N2) at the Fenn Big Valley, Alberta, Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".