Volumetric strain associated with methane desorption and its impact on coalbed gas production from deep coal seams
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The permeability of deep (>1000 m; >3300 ft) coal seams is commonly low. For deep coal seams, significant reservoir pressure drawdown is required to promote gas desorption because of the Langmuir-type isotherm that typifies coals. Hence, a large permeability decline may occur because of pressure drawdown and the resulting increase in effective stress, depending on coal properties and the stress field during production. However, the permeability decline can potentially be offset by the permeability enhancement caused by the matrix shrinkage associated with methane desorption. The predictability of varying permeability is critical for coalbed gas exploration and production-well management. We have investigated quantitatively the effects of reservoir pressure and sorption-induced volumetric strain on coal-seam permeability with constraints from the adsorption isotherm and associated volumetric strain measured on a Cretaceous Mesaverde Group coal (Piceance basin) and derived a stress-dependent permeability model. Our results suggest that the favorable coal properties that can result in less permeability reduction during earlier production and an earlier strong permeability rebound (increase in permeability caused by coal shrinkage) with methane desorption include (1) large bulk or Young's modulus; (2) large adsorption or Langmuir volume; (3) high Langmuir pressure; (4) high initial permeability and dense cleat spacing; and (5) low initial reservoir pressure and high in-situ gas content. Permeability variation with gas production is further dependent on the orientation of the coal seam, the reservoir stress field, and the cleat structure. Well completion with injection of N 2 and displacement of CH 4 only results in short-term enhancement of permeability and does not promote the overall gas production for the coal studied.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it