Combined Effect of Non-Darcy Flow and Formation Damage on Gas Well Performance of Dual-Porosity and Dual-Permeability Reservoirs
Bibliographic record
Abstract
Abstract This paper addresses the combined effect of formation damage and non-Darcy flow in naturally fractured reservoirs using simplified analytical solutions and a two-dimensional numerical simulator. Pressure drawdown, buildup, and isochronal tests simulated in this work indicate that, despite high fracture permeability, skin damage may accentuate the non-Darcy flow effect and drastically influence pressure-transient characteristics of low-pressure, naturally fractured reservoirs. In high-pressure reservoirs, this effect is significant only at high rates. Non-Darcy flow does not usually mask the typical pressure-transient characteristics of dual-porosity and dual-permeability reservoirs, but the conventional interpretation of the early time data may lead to erroneous results. If the exponent, n, of the gas performance curve approaches 0.5 while the matrix permeability is low and flow rate is rather high, this indicates predominance of fracture flow. The practical motivations of this study and its extensions to other practical problems, such as condensate reservoirs where the condensate dropout in the wellbore region should increase non-Darcy flow, are also discussed.
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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 | 0.002 |
| 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 | 0.001 |
| 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".