Temperatures of dolomitizing fluids in the Feixianguan Formation from the Northeastern Sichuan Basin
Bibliographic record
Abstract
The discovery of natural gas reservoirs from the Triassic Feixianguan Formation in the Northeastern Sichuan Basin is an important breakthrough in the field of marine carbonate rocks for Chinese oil and gas exploration in recent years.Because of the dolomite-hosted reservoirs in the Feixianguan Formation,these dolomites and their formation mechanisms have been a research focus for sedimentary geologists and petroleum geologists.Based on the homogenization temperatures of fluid inclusions,oxygen isotopic composition and their calculated temperatures,and the burial and thermal history of the typical well,it is considered that the majority of dolomites are formed by low-temperature dolomitizing fluids in the Triassic Feixianguan Formation,Northeastern Sichuan Basin.Only a minority of dolomites are formed by high-temperature dolomitizing fluids.The ending depth interval of low-temperature dolomitizing fluids was about 1000-2500 m,of which the correspondingly ending timing interval was approximately from early-middle Middle Triassic to early-middle Late Triassic.The main depth interval of high-temperature dolomitizing fluids was about 3200-4500 m,of which the correspondingly main timing interval was approximately early-middle Middle Jurassic.The low-temperature and high-temperature dolomitizing fluids have different meanings to the formation and evolution of the pore volumes of dolomite reservoirs in the Feixianguan Formation,Northeastern Sichuan Basin.
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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 | 0.001 |
| 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".