Research on One Novel Logging Interpretation Method of CBM Reservoir
Bibliographic record
Abstract
Coalbed methane (CBM) is a kind of natural gas which is stored in the micropores and fractures of the “coal seam” and has not been transported out of the source rock. Conventional logging technology plays an important role in coalbed methane exploration and development. By analyzing the response characteristics of conventional logging of coalbed methane, coal bearing strata are accurately determined. Two methods of statistical model and volume model are established to analyze and calculate industrial components. Based on the study of adsorption isotherm and correlation between logging parameters and coal core gas content, the calculation method of coal seam gas content is determined In practices, the calculation accuracy of industrial components and gas content of coal seam has been significantly improved. Abstract: coalbed methane (CBM) is a kind of natural gas which is stored in the micropores and fractures of “coal seam” and has not been transported out of the source rock. Conventional logging technology plays an important role in coalbed methane exploration and development. By analyzing the response characteristics of conventional logging of coalbed methane, coal bearing strata are accurately determined. Two methods of statistical model and volume model are established to analyze and calculate industrial components. Based on the study of adsorption isotherm and correlation between logging parameters and coal core gas content, the calculation method of coal seam gas content is determined In practice, the calculation accuracy of industrial components and gas content of coal seam has been significantly improved.
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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".