Coupling Mechanism of THMC Fields in Crushed Soft Coal with Low Permeability after CO<sub>2</sub> Injection and Its Application in CO<sub>2</sub>-ECBM Technology
Bibliographic record
Abstract
During the CO 2 -ECBM process in crushed soft coal with low permeability (CSLP-Coal), the analysis of the fully coupled mechanism of the thermo-hydro-mechanical-chemical (THMC) fields is conducive to engineering promotion of CO 2 -ECBM technology. In this study, the CSLP-Coal in Huainan and Huaibei coalfields was taken as the research object; the fully coupled mathematical models of THMC fields were established; the effects of injection pressure, temperature, and initial permeability were studied; the evolution connotation of reservoir permeability was discussed; and the reaction mechanism of the chemical field was analyzed. The evaluation system of the CO 2 -ECBM project in CSLP-Coal was further established. The results show that the mathematical models of THMC fields are fully coupled during the CO 2 -ECBM process. Injection pressure, temperature, and initial permeability have great influence on the CO 2 -ECBM technology. The variation of reservoir permeability is mainly influenced by the effective stress effect and competitive adsorption effect of CH 4 /CO 2 . The formation of a geochemical reaction system with CH 4 /CO 2 -H 2 O-coal is conducive to the engineering popularization of the CO 2 -ECBM technology. Based on the three indexes, the evaluation system for the practical effectiveness of CO 2 -ECBM engineering in CSLP-Coal in Huainan and Huaibei coalfields can be constructed. This study has important theoretical and practical significance for improving the recovery efficiency of CH 4 and enhancing the ability of CO 2 storage in CSLP-Coal.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".