A novel fluid–solid coupling model for the oil–water flow in the natural fractured reservoirs
Bibliographic record
Abstract
The mutual coupling effect between the fluid flow and the in situ stress fields cannot be ignored during the development of natural fractured reservoirs (NFRs), such as in the waterflooding process. In this study, a discrete fracture model is proposed to simulate the rock deformation and two-phase flow behaviors of oil and water in the NFR. The numerical solution of the model is achieved via the finite-element method and control-volume finite-element method. The numerical simulator is verified using commercial software, and a perfect agreement is obtained. Finally, sensitivity analysis is conducted on the key parameters in the model, such as fracture parameters, matrix permeability, and injection intensity. Results show that the fluid–solid coupling effect gradually weakens with production time. The degree of the fluid–solid coupling on cumulative oil production becomes smaller as the permeability of the matrix increases. Fracture connectivity controls the velocity and direction of the water flood front. Water injection intensity directly affects the natural fracture opening deformation and well productivity. The research and the numerical results obtained in this paper can provide theoretical guidance for the optimal design of water flooding operations in NFR.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".