Analytical and Experimental Investigations of Gas-Flow Regimes in Shales Considering the Influence of Mean Effective Stress
Bibliographic record
Abstract
Summary Flow conditions determine the flow regimes governing gas flow in porous media. Slip-flow regime commonly occurs in laboratory gas-permeability measurements, and one must consider the physics of that when finding the absolute permeability of a sample. Accurate permeability estimates are paramount for production forecasts, financial planning, and recovery estimation. Slip flow is present in low-permeability rocks, both in the laboratory environment and at reservoir conditions. Gas flow through the matrix lies under the slip-flow regime for the majority of low-permeability-reservoir production scenarios, and accurate prediction of pressure and production rate requires a good understanding of the flow regime. In this paper, an analytical study is conducted on the dominant flow regimes under typical shale-gas reservoir conditions. A flow-regime map is produced with respect to gas pressure and matrix permeability. Steady-state gas-permeability experiments are conducted on three shale samples. An analytical model is used to match the experimental results that could explain the order-of-magnitude difference between the permeabilities of gas and liquid in shales. Experimental results are combined with further tests available in the literature to inform a discussion of the model's parameters. The results improve the accuracy of gas-flow modeling and of absolute-permeability estimates from laboratory tests. Similar tests performed at various mean effective stresses investigate the influence of mean effective stress on flow regime and apparent permeability. The results indicate that flow regime is a function of mean effective stress, and that the apparent permeability of shale rocks is a function of both flow regime and mean effective stress.
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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 | 0.001 |
| 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 | 0.001 |
| 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".