The Major Controlling Factors and Different Oolitic Shoal Reservoir Characteristics of the Triassic Feixianguan Formation, Eastern Longgang Area, NE Sichuan Basin, SW China
Bibliographic record
Abstract
Abstract Based on comprehensive analyses of occurrence, petrological observation, pore structure and geochemistry, the different reservoir characteristics and reservoir evolutionary pathways between different oolitic shoal reservoir types of the Feixianguan Formation on the west side of the Kaijiang‐Liangping Trough have been studied. There exist three stages of high‐energy slope break belts in the Feixianguan period, the corresponding three stages of oolitic shoals gradually migrating in the direction of the trough. Three types of oolitic shoal reservoirs, namely, residual‐oolitic dolomite, mold‐oolitic dolomite and sparry oolitic limestone, were formed during sedimentary‐diagenetic evolution, the pore types being intergranular dissolved pore, mold pore (or intragranular dissolved pore) and residual intergranular pore, respectively. The petrology, physical properties and pore structure of the different types of oolitic shoal reservoirs are quite different. Residual‐oolitic dolomite reservoirs have the best quality, while sparry oolitic limestone reservoirs have the poorest. Combined with analyses of trace elements, rare earth elements and carbon‐oxygen isotopes, it is suggested that the formation of residual‐oolitic dolomite reservoirs is jointly controlled by penesaline seawater seepage‐reflux dolomitization and hydrothermal dolomitization. Mold‐pore oolitic dolomite reservoirs are controlled by penesaline seawater seepage‐reflux dolomitization and meteoric water solution. The burial dissolution of organic acid not only further improves the reservoir qualities of previously formed oolitic dolomite reservoirs, but also preserves residual intergranular pores in the sparry oolitic limestone reservoirs.
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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) | 0.001 | 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".