Fluid Flow in a Fractured Reservoir Using a Geomechanically-Constrained Fault Zone Damage Model for Reservoir Simulation
Bibliographic record
Abstract
Abstract Secondary fractures and faults associated with larger, reservoir scale faults affect both permeability and permeability anisotropy and hence may play an important role in controlling the production behavior of a faulted reservoir. It is well known from geologic studies that there is a concentration of secondary fractures and faults in a damage zone adjacent to larger faults. Because there is usually inadequate data to incorporate damage zone fractures and faults into reservoir simulation models, in this study we utilize the principles of dynamic rupture propagation from earthquake seismology to predict the nature of fractured/damage zones associated with reservoir scale faults. We include geomechanical constraints in our reservoir model and propose a workflow to more routinely incorporate damage zones into reservoir simulation models. The model we propose calculates the extent of the damage zone along the fault plane by estimating the stress perturbation associated with dynamic rupture propagation. Fractures created by the stress pulse accompanying rupture propagation enhance permeability along reservoir scale faults in both the horizontal and vertical directions. We calibrate our modeling with observations from a number of studies and show that dynamic rupture propagation gives a reasonable first order approximation of damage zones in terms of permeability and permeability anisotropy in order to be incorporated into reservoir simulators.
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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 | 0.001 |
| Open science | 0.001 | 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".