A Semianalytical Method for Modeling Two-Phase Flow in Coalbed-Methane Reservoirs With Complex Fracture Networks
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Bibliographic record
Abstract
Summary Coalbed-methane (CBM) reservoirs are naturally fractured formations with cleats surrounding the coal matrix. Analyzing and predicting CBM-production performance is challenging, especially for early-time production, because of the complex fracture networks and gas/water two-phase flow. In this study, we develop an efficient semianalytical model to predict gas and water production in CBM reservoirs with multiscale fracture networks. The activated large-scale or interconnected cleats and hydraulic fractures are modeled explicitly as discretized segments with connected nodes. The small-scale cleats and disconnected natural fractures are described implicitly as “enhanced matrix permeability.” We incorporate critical gas-flow mechanisms and stress sensitivity of the fracture network in the model. The two-phase-flow mechanism is considered by iteratively correcting the relative permeability to gas/water for each fracture segment and capillary pressure at each node with the reservoir depletion. We verified the model against a numerical reservoir simulator, field data, and an analytical solution. Subsequently, we apply the model to quantify the effects of fracture-network complexity/connectivity and stress sensitivity on gas/water-production behavior. This work presents an accurate and fast semianalytical model to perform two-phase flow of gas and water in CBM wells with complex fracture networks. The approach is easier to set up and less data-intensive than using a numerical reservoir simulator, and more flexible in handling the complex-fracture networks than full analytical models. This method provides a promising technique for better understanding the effect of the cleats and fracture networks present in CBM reservoirs on gas and water production.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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