The effects of shale composition and pore structure on gas adsorption potential in highly mature marine shales, Lower Paleozoic, central Yangtze, China
Bibliographic record
Abstract
The Ordovician Wufeng Formation and Silurian Longmaxi Formation are two of the most organic-rich and gas-prospective shale formations in the central Yangtze area, China. In this study, we investigate the controls exerted by shale composition and pore structure on methane sorption of these highly matured marine shales (Ro ranges from 2.0% to 4.0%). Samples were analyzed by SEM pore imaging of Ar-ion milled samples, high pressure methane adsorption, and low temperature nitrogen adsorption. In the high TOC Wufeng and lower Longmaxi formations, numerous organic matter pores are present. A positive correlation exists between TOC, BET surface area, and CH4 sorption capacity, indicating that porosity associated with organic matter is the key factor controlling methane sorption capacity of shale samples. In the organic-lean upper Longmaxi Formation, pores within clay particles and carbonate minerals are the major pore types. Organic-lean shale samples from the upper Longmaxi Formation have higher clay content, lower BET surface area, and lower adsorption capacity than organic-rich shales. Within several low TOC samples, a relatively strong correlation exists between illite content and methane sorption capacity, which is interpreted to result from clay mineral-hosted porosity.
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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 | 0.000 |
| 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".