Analytical Solution of Matrix Permeability of Organic-Rich Shale
Bibliographic record
Abstract
Abstract Apparent matrix permeability of organic-rich shale is complicated because of its unique pore structure, gas storage and transport mechanisms. In inorganic pores, free gas is the only phase considered. While in organic pores, adsorbed phase coexists with free gas. Surface diffusion is the transport mechanism of the adsorbed phase. However, transport mechanism of free gas varies during production and is distinguished by the Knudsen number. Slip flow, transition flow, Knudsen diffusion and surface diffusion are found in organic pores, whereas only slip flow and transition flow occur in inorganic pores. The effects of pore size, pressure and temperature on the transport mechanism are discussed. Pressure reduction causes a change in transport mechanisms during production. Stress dependency of inorganic pores is one of the factors that affect pore size, transport mechanism and permeability. The apparent permeability is derived by calculating the geometric average of permeability of different units with varying pore sizes and permeabilities. Sensitivity analysis shows that stress-dependency plays an important role in inorganic pores, which results in the positive correlation between permeability and pressure. Conversely, in inorganic pores, permeability increases as pressure decreases. As a result, permeability decreases and then increases with decreasing pressure.
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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".