Multiscale coupled modeling of coalbed methane and water extraction from coal reservoirs with fractures and barriers
Bibliographic record
Abstract
This study introduces a fully coupled two-phase flow and geomechanics model to simulate the extraction of coalbed methane (CBM) and water from coal reservoirs with conductive fractures and blocking barriers, characterized by high and low permeability, respectively. These fractures and barriers are modeled as low-dimensional objects. The accuracy of the proposed model is first validated against a reference case using the open-source simulator DuMux. Following validation, the model is applied to a coal reservoir with a discrete fracture network to simulate CBM and water production. The simulation results reveal that gas and water extraction decrease both nonwetting phase saturation and pressure, with pressure decreasing more rapidly. This leads to permeability changes due to depressurization and shrinkage-induced strain. Fracture permeability near the well decreases, while it significantly increases in the far-field region. Sensitivity analysis indicates that higher initial permeability and lower entry pressure of fractures enhance CBM productivity. The relationship between fracture stiffness, matrix elasticity, and production exhibits non-monotonic behavior. As fracture stiffness increases and matrix elasticity decreases, production may initially decline but increase again. These results highlight the complex interaction between fracture and matrix properties, where fracture permeability plays a key role in determining both production rates and cumulative production. Fracture angles influence the connectivity of the network, significantly affecting fluid flow, pressure changes, and production rates, even with similar initial permeability and fracture density. Overall, this study offers valuable insights for more accurate predictions of CBM production.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".