Formation Heat Treatment to Release the Trapped Gas from Stagnant Pores of Deep Coalbed Methane Reservoirs
Bibliographic record
Abstract
A large portion of gas in deep coalbed methane (CBM) reservoirs is trapped in stagnant matrix pores and cannot be effectively produced by pressure drawdown alone. In this study, the mechanisms of releasing trapped gas from the matrix by formation heat treatment (FHT) are investigated. First, the origins and classifications of the trapped gas in the deep CBM reservoirs are analyzed based on geological diagenesis and engineering operations. Then, FHT experiments are conducted to evaluate its effects on coal permeability, pore structure, and composition. The results indicate that the coal permeability increases significantly with the temperature, rising 36.45 times after treatment at 200 °C, though thermal fragmentation occurs at 300 °C. At 200 °C, the coal samples show a mass loss of 19.99%, with moisture, volatile matter, and fixed carbon decreasing by 25%, 39.45%, and 3.22%, respectively, while the ash content increases by 42.86%. The internal mineral framework of coal undergoes structural degradation due to thermal decomposition of organic matter, accompanied by a reduction in mechanical strength. Therefore, FHT promotes the development of primary and secondary fractures, forming effective flow channels to release trapped gas from stagnant pores. Finally, a reservoir stimulation method that combines FHT and hydraulic fracturing is proposed to efficiently develop the deep CBM. This study sheds light on the mechanisms of gas trapping and its thermal release, thereby promoting the development of stimulation technologies for deep CBM reservoirs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".