Relative Permeability of CBM Reservoirs: Controls on Curve Shape
Bibliographic record
Abstract
Abstract Relative permeability to gas and water for 2-phase flow coalbed methane (CBM) reservoirs has long been known to exhibit a strong control on (gas and water) production profile characteristics. Despite its important control on both primary and enhanced recovery of CBM for coal seams that have not been fully dewatered, relative permeability in coal has received little attention in the literature in the past decade. There are few published laboratory-derived curves; these studies and their resulting data represent a small subset of the commercial CBM reservoirs and do not allow for a systematic investigation of the physical controls on relative permeability curve shape. Other methods for estimation of relative permeability curves include derivation from simulation history-matching, and production data analysis. Both of these methods will yield pseudo relative permeability curves whose shapes could be affected by several dynamic CBM reservoir and operating characteristics. The purpose of the current work is to perform a systematic investigation of the controls on CBM relative permeability curve shape, including non-static fracture permeability and porosity, multi-layer effects and transient flow. To derive the relative permeability curves, effective permeability to gas and water are obtained from flow equations using a modified version of the approach described by Clarkson et al. (2007). Simulated cases are analyzed so that derived and input curves may be compared allowing for investigation of CBM reservoir properties on curve-shape. One set of relative permeability curves that were input into the simulator were derived from pore-scale modeling. Field cases from two basins are also examined and controls on derived relative permeability curve shape inferred. The results of this work should be useful for future CBM development and greenhouse gas sequestration studies, and it is hoped that it will spark additional research of this critical CBM flow property.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".