Evaluation of Aqueous Phase Trapping in Shale Gas Reservoirs Based on Analytic Hierarchy Process
Bibliographic record
Abstract
A large amount of fracturing fluid retained in a shale gas reservoir that does not flow back after hydraulic fracturing could induce formation damage of aqueous phase trapping (APT). A shale gas reservoir generally has a multiscale pore and fracture structure, so both retained fracturing fluid distribution and gas transport have multiscale characteristics. In this work, a comprehensive evaluation method of shale APT damage based on the analytic hierarchy process in fuzzy mathematics is put forward considering the petrophysical properties and multiscale gas transport behavior in a shale reservoir. First, the critical indexes of shale APT damage evaluation are determined. Then the hierarchy structure for APT damage evaluation for a shale gas reservoir is constructed. Finally, the weights of the critical evaluation indexes of shale APT damage are calculated on the basis of the analytic hierarchy process. Taking Longmaxi shale reservoir as an example, the APT damage degrees for matrix and fractures are calculated to be 65% and 84%, respectively. The evaluation method for shale APT damage proposed in this work is beneficial to accurately predicting the productivity of a shale gas well and optimizing the hydraulic fracturing process to improve the stimulation effect.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".