Diagenetic characteristics and microscopic pore evolution of deep shale gas reservoirs in Longmaxi Formation, Southeastern Sichuan basin, China
Bibliographic record
Abstract
The Lower Silurian Longmaxi Formation is the favorable target area for deep shale gas exploration and development in southeastern Sichuan Basin . Based on whole-rock X-ray diffraction analysis, scanning electron microscope, reservoir evolution thermal simulation experiment and nitrogen adsorption experiment, the diagenetic characteristics of deep shale reservoir in Longmaxi Formation were analyzed, and the reservoir pore evolution law was clarified. The results show that: ①The diagenetic minerals of the deep shale in the Longmaxi Formation are mainly quartz and clay minerals, with a small amount of carbonate minerals and feldspar. The primary inorganic pores are mainly controlled by mechanical compaction and cementation (quartz, carbonate, clay, pyrite). The organic pores are mainly controlled by the thermal maturity of organic matter, dissolution and later compaction. ②In the process of thermal simulation experiment, the organic pores of shale show a process of change from scratch, from small to large and then from large to small. Later, the organic matter is affected by compaction and graphitization , and the volume of micropores and mesopores begins to decrease. ③The shale pores of Longmaxi Formation have undergone several evolutionary stages. In the early stage of diagenesis , compaction caused a large number of inorganic pores to disappear. In the middle stage of diagenesis, kerogen hydrocarbon generation occupied pores, dissolution and cementation transformed pores. In the late diagenetic period, liquid hydrocarbon cracking gas and pressurization promote the development of organic pores.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".