Differential Thermal Evolution between Oil and Source Rocks in the Carboniferous Shale Reservoir of the Qaidam Basin, NW China
Bibliographic record
Abstract
Shale oil and source rock samples of the Carboniferous Keluke Formation from well Chaiye 2 in the Delingha Depression were analyzed by gas chromatography–mass spectrometry. Source rocks were highly mature at the gas generation stage with vitrinite reflectance (Ro) of 1.45–1.88%. However, the oil produced from the shale reservoir was characterized by abundant biomarkers but low abundance of diamondoid hydrocarbons with estimated Ro of ca. 0.78%, indicating hydrocarbons were still at a relatively low thermal maturity level. As the crude oil was generated and accumulated autochthonously, preliminary results indicate that crude oil and source rocks witnessed differential thermal evolution and significant disparity of the current thermal maturity in the shale reservoir due to rapid tectonic subsidence and clay mineral catalysts that accelerated the thermal maturation process. Although tectonic uplifts occurred afterwards, the vitrinite recorded the highest maturity that source rocks have ever reached, whereas the oil has not reached the same maturity level due to less impact from thermal alteration or mineral catalysis than source rocks in the shale reservoir. Such a discovery enlarges the hydrocarbon perseveration of maturity ranges in reservoirs, particularly for the unconventional tight formation, and benefits potential hydrocarbon exploration from highly mature sediments.
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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 | 0.001 | 0.001 |
| 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 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".