Analysis of the charging process of the lacustrine tight oil reservoir in the Triassic Chang 6 Member in the southwest Ordos Basin, China
Bibliographic record
Abstract
With the success of Bakken tight oil (tight sandstone oil and shale oil) and Eagle Ford tight oil in North America, tight oil has become a research focus in petroleum geology. In China, tight oil reservoirs are predominantly distributed in lacustrine basins. The Triassic Chang 6 Member is the main production layer of tight oil in the Ordos Basin, in which the episodes, timing, and drive of tight oil charging have been analyzed through the petrography, fluorescence microspectrometry, microthermometry, and trapping pressure simulations of fluid inclusions in the reservoir beds. Several conclusions have been reached in this paper. First, aqueous inclusions with five peaks of homogenization temperatures and oil inclusions with three peaks of homogenization temperatures occurred in the Chang 6 reservoir beds. The oil inclusions are mostly distributed in fractures that cut across and occur within the quartz grains, in the quartz overgrowth and calcite cements, and the fractures that occur within the feldspar grains, with blue–green, green, and yellow–green fluorescence colours. Second, the peak wavelength, Q650/500, and QF535 of the fluorescence microspectrometry indicate three charging episodes of tight oil with different oil maturities. The charging timings (141–136, 126–118, and 112–103 Ma) have been ascertained by projecting the homogenization temperatures of aqueous inclusions onto the geological time axis. Third, excess-pressure differences up to 10 MPa between the Chang 7 source rocks and the Chang 6 reservoir beds were the main driving mechanism supporting the process of nonbuoyancy migration.
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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 | 0.001 | 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".