Application of thermal methods to increase the efficiency of coalbed methane production
Bibliographic record
Abstract
In recent years, the expansion of the base of energy raw materials occurs through the involvement of new unconventional sources into operation. The development of new technologies made it possible to extract methane and its homologues from sedimentary formations that were not previously considered as sources of natural gas. One of these formations are coal-bearing strata. In some cases, the development of coal seams using traditional methods (quarry and mine) is impossible due to mining, geological, economic, technical and other reasons. The volume of industrial production of coalbed methane in foreign countries is beginning to have a significant impact on global gas markets. Industrial extraction of methane is conducted in the USA, China, Canada and other industrialized countries. It should be noted that the potential of unconventional resources of methane is huge - the resources of coal in the world reach 15 trillion tons. Coals are a promising source of coalbed methane. Gas output can be increased by thermal exposure to the coal seam. We have carried out studies of residual gas components from samples of fossil coal by the method of combined thermogravimetry (TG) and IR spectroscopy (IR). The method of thermogravimetry allows us to estimate the amount of gas sorbed in the coals, and IR spectroscopy to identify the composition of the emitted gases in each temperature range. Data on the composition of gas fractions in various temperature ranges was obtained.
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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".