Pore Structure Evolution’s Reaction to Late-Stage Tectonic Uplift in Organic-Rich Marine Shale Reservoirs
Bibliographic record
Abstract
An important scientific question in comprehending the dynamic adjustment and accumulation mechanisms of shale gas is the effect of late-stage tectonic uplift on the shale pore structure. It has a direct impact on how well shale gas exploration and development work in China’s structurally complicated Sichuan Basin. This study aims to reveal the rebound evolution patterns and characteristics of shale pores at different scales under the influence of the most recent tectonic uplift. To achieve this, we conducted triaxial creep experiments to investigate the compression recovery behavior of shale under varying confining pressures. Shale samples were subjected to low-pressure CO 2 /N 2 adsorption studies and high-pressure mercury intrusion both prior to and during creep testing. Combined with the fractal theory, these methods revealed the evolution patterns of shale pore structures across different scales. Key findings reveal a bimodal pore size distribution in the Longmaxi Formation shale. Micropores contribute 60.25% to 81.52% of the specific surface area, while mesopores account for 51.02% to 70.03% of the pore volume. Under deep burial, macropores and mesopores tend to transform into micropores, enhancing the adsorbed gas storage. Micropore evolution is jointly influenced by clay minerals and total organic carbon (TOC), whereas mesopores correlate strongly with the TOC and quartz. Macropore development is governed by brittle minerals, such as quartz and calcite. This study presents a conceptual model of multiscale pore rebound under a tectonic uplift, highlighting the complex interactions between the mineral composition and mechanical behavior.
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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 | 0.000 | 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) | 0.001 | 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".