A novel method for evaluating shale gas preservation conditions in an area on a regional scale
Bibliographic record
Abstract
The Youjiang Basin is the main area of the Middle Devonian shale gas resources in southern China, with complex geological conditions, diverse stratigraphic structures, low level of exploration and limited hydrocarbon geological data. In this study, a method is proposed for evaluating the regional shale gas preservation conditions, by which it is easy to obtain information (using available data from regional geological maps) and to process data (processed by computer software). This method was applied to the evaluation of the preservation conditions of the Middle Devonian shale gas in the Youjiang Basin. Information extracted from geologic maps includes exposed stratum, magmatic rock distribution, stratigraphic occurrence and surface fracture distribution. Evaluation criteria for three indexes (stratigraphy index, dip angle index and fracture index) were established to classify the preservation conditions into five types from good to bad. Based on the calculated values of comprehensive index (CI), the comprehensive evaluation each area: 11621.23 km 2 for CI of 0.7–1.0, 37162.67 km 2 for CI of 0.5–0.7, 57784.43 km 2 for CI of 0.3–0.5, 69303.77 km 2 for CI of 0.1–0.3, and 69303.77 km 2 for CI of 0.0–0.1, accounting for 3.19%, 10.19%, 15.84%, 18.99% and 51.80% of the whole area, respectively. These results are highly consistent with the actual exploration discoveries, showing that in the northern and central parts of the Guizhong Basin, the southern part of the Xidamingshan Uplift, and the northern part of the Qiannan Basin, there are large areas with good shale gas preservation conditions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".