Coupled Geomechanics and Fluid Flow Modeling in Naturally Fractured Reservoirs
Bibliographic record
Abstract
Abstract A parallel geomechanics model for describing naturally fractured rock deformation is developed and tightly coupled with a dual porosity/dual permeability black oil model. The geomechanics model is developed with capabilities of modeling both rock matrix and the fracture deformations, as well as their effects on reservoir properties. An advanced constitutive law with the fracture deformation mechanism is proposed. The multiphase flow model is modified by introducing geomechanical variables. The matrix porosity and fracture permeability are chosen as coupling parameters between geomechanics and fluid flow models. An iteratively coupling method is employed in order to fully capture interactions between solid and flow. Moreover, parallel computing is employed to handle large scale problems by benefiting from its features of distributed memory storage and efficient runtime reduction. Geomechanical effects on the reservoir pressure distribution are illustrated by a numerical experiment. In addition, for testing the scalability behavior, a large scale problem with millions of grid blocks is performed on multiple processors. The result shows an encouraging speedup which indicates the integrated model can be an efficient and useful tool for predicting and analyzing oil/gas production of naturally 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".