Evaluation of organic matter abundance of source rocks of biogenic gas: a case from the Quaternary Qigequan Formation Shale, Sanhu Depression, Qaidam Basin
Bibliographic record
Abstract
A correct understanding of organic matter abundance is key to understanding the conditions necessary for generating biogenic gas, seeking favorable exploration intervals and fields and evaluating resources correctly. The Qigequan Formation shale of the Quaternary in the Sanhu Depression of the Qaidam Basin is taken as the research object. The abundance of dissolved organic matter was determined through total carbon, pyrolysis and other experiments. The evaluation criteria were established and applied. The resource quality is calculated. The results are as follows. (1) Dissolved organic matter is the basis for biogenic gas generation and should be emphasized in the evaluation. (2) The shale has a relatively high dissolved organic carbon (DOC) content, with an average of 2.48 times that of insoluble organic carbon. (3) The DOC of the good source rock is more than 0.60%, that of the medium is 0.25~0.60%, and that of the poor is less than 0.25%. (4) The distribution of good source rocks is influenced by the position and depth of the water column and the paleoclimate. Favorable intervals are mainly in the upper sections of K10, K9 and K8 and the middle section of K7. The favorable areas are mainly the Tainan, Sebei and Sedong areas.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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 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".