CHARACTERISTICS OF POOLING AND EXPLORATION AND DEVELOPMENT OF CBM IN LOW-RANK COALS
Bibliographic record
Abstract
CBM gas reservoirs in low-rank coals are featured by large thickness of coal seams,high permeability,low gas content,and high adsorption saturation.In recent years,the major CBM discoveries are concentrated in the low-rank areas in the Powder River Basin(the U.S.A) and the Alberta Basin(Canada).Exploration and development practices in these areas show that commercial gas flow can be obtained in CBM gas reservoirs in low-rank coals.After introducing CBM in low-rank coals exploration and development techniques,this paper preliminarily analyzes,assesses and forecasts the resource volume and exploration potential of CBM in low-rank coals in China.It is shown that CBM resources in Low-rank coals are rich in China.The Jurassic low-rank coal seams in Junggar,Turpan-Hami,Santanghu,Tianshan,Tarim and Ordos basins have a!total gas-bearing area of about 206 800 km2,and a CBM resource volume of 19.96 TCM accounting for 54% of the total in China,thus exploration and developmeot potentials are large here.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".