Geochemical characteristics, genetic types, and sources of gas accumulations in the northern Jizhong subbasin, Bohai Bay Basin, eastern China
Bibliographic record
Abstract
ABSTRACT Gas source and genetic type identification are important for gas system analysis and successful exploration. However, such crucial information is generally lacking or highly controversial in the northern Jizhong subbasin, Bohai Bay Basin, hindering further gas exploration. In this study, multiple genetic types of gases are identified in the northern Jizhong subbasin, including biogenic gas, coal-derived gas, and oil-associated gas. In particular, gases in the shallow Paleogene reservoirs are composed mainly of oil-associated gases derived from sapropelic organic matter in the Paleogene third member of the Shahejie Formation (Es3) and dark shales in the fourth member of the Shahejie and Kongdian Formations (Es4 + Ek). Gases in the deeply buried Ordovician and Carboniferous–Permian reservoirs are mainly derived from coal, with some contributions from oil-associated gases. The deep gases are mainly derived from the Carboniferous–Permian coal-bearing humic source rocks, with contributions from mixed organic matter in the Es4 + Ek source rocks. Biogenic gases, mainly present in the Paleogene Es3 reservoirs, are dominated by secondary microbially generated gas via CO2 reduction. Microbially generated gases are probably derived from sapropelic organic matter in the Es3 source rock. Based on the findings, it is concluded that shallow Paleogene rocks may be a favorable reservoir zone for primary (kerogen) cracking gases generated from type II1 kerogen. Dry gases derived from type III kerogen and secondary cracking gases from type II1 kerogen in the deep and ultradeep Ordovician and Precambrian–Cambrian reservoirs can be other potential exploration targets in the northern Jizhong subbasin.
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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 | 0.002 |
| 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) | 0.001 | 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".