The depositional evolution, reservoir characteristics, and controlling factors of microbial carbonates of Dengying Formation in upper Neoprotozoic, Sichuan Basin, Southwest China
Bibliographic record
Abstract
The Dengying Formation of Neoprotozoic age deposited in north Sichuan Basin, China, is dominated by dolomitic strata containing microbial carbonates. Thirteen cyanobacteria forms, one oncolite and two stromatolitic structures have been identified. Different microfacies may be related to different microbe forms or assemblages as well as depositional environments. Potential hydrocarbon reservoirs in microbial carbonates are of low porosity and permeability. Microbialites develop in the members Z 2 dn 1 , Z 2 dn 2 , and Z 2 dn 4 . The member Z 2 dn 1 and Z 2 dn 2 lying in the lower part, dominated by thrombolitic and spongiostromata dolostone, with three reservoir intervals of overall 190 m thick. Laminite and stromatolitic dolostone are the most important in member Z 2 dn 4 , with three reservoir intervals of 119 m thick. Microbial carbonate reservoirs in members Z 2 dn 1 and Z 2 dn 2 were effected by two stages of fresh water dissolution, three stages of burial dissolution, and one stage of hydrocarbon invasion. But one stage of fresh water dissolution, two stages of burial dissolution, and three stages of hydrocarbon invasion modified the reservoirs of member Z 2 dn 4 . The dominant factors for microbial reservoirs were microbial textures and development of Mianyang-Changning intracratonic sag.
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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) | 0.000 | 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".