Fracture Capillary Pressure Based on the Liquid Bridge Dynamic Stability Study
Bibliographic record
Abstract
Performance study of gas oil gravity drainage in stacks of overwhelmed blocks in a gas-invaded zone of naturally fractured reservoirs presents difficult challenges to petroleum engineers. It is believed that there exists some degree of block-to-block interaction that may lead to capillary continuity in fractured reservoirs. Effect of such continuity in gravity drainage is much more pronounced as it increases the height of the continuous fluid column in a reservoir and thereby the recovery of oil as height is a key parameter in gravity drainage mechanisms. It has been experimentally proven that liquid or solid bridges in horizontal fracture can contribute to wetting phase transfer across the horizontal fracture, but there is no mathematical model that predicts the probability of such continuity. In this article, a mathematical model developed by using 1-D Navier-Stock for the free surface flow equation and Young-Laplace of capillary for breakage of the stable liquid bridge held between two pairs of support while stretching. The model gives critical length of fracture aperture, which surely provides capillary continuity. Moreover, the developed model shows flow dependency of fracture capillary pressure and predicts a nonzero value for this parameter, while in the past many researchers used zero fracture capillary pressure for history matching of fractured reservoirs.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".