Transient Pressure Analysis in Multi-Stage Fractured Horizontal Wells from Tight Gas Reservoirs with Weak Fluid Supply
Bibliographic record
Abstract
Abstract This paper develops a novel WFS model for transient pressure analysis in multi-stage fractured horizontal wells. In the WFS model, two concepts called WFS pressure and WFS index are introduced and an additional skin factor in the interface of inner and outer regions is applied based on a radial composite reservoir. Then, a novel multi-stage fractured horizontal well model is developed by considering the WFS, stress-sensitivity effects, and finite-conductivity fractures. The reservoir model is solved by the perturbation transformation, Laplace transform, and numerical inversion. While the fracture model is solved by fracture discretization and superposition principle. Finally, the bottom hole pressure is obtained. Following that, model verification and sensitivity study are performed. It is found that the flow regimes of the WFS model includes bilinear flow, linear flow, first radial flow, bi-radial flow, pseudo radial flow, and WFS flow. An interesting feature of "hump" caused by WFS flow exhibits in the pressure derivative curve. The results of sensitivity study show that the height of that "hump" increases as the WFS pressure increases, but is independent of WFS index. What’s more, WFS flow exhibits a closed boundary flow when the WFS index is equal to zero, while it appears as a constant pressure boundary flow when WFS pressure is very tiny. Through the WFS model, the fluid supply characteristics of tight gas reservoirs are fully understood.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".