Numerical upscaling of anisotropic failure criteria in heterogeneous reservoirs
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Bibliographic record
Abstract
With advances in characterizing the reservoir heterogeneities and modeling the complex reservoir-geomechanical behavior using modern geological modeling software and simulators, the impact of geological uncertainties on reservoir-geomechanical responses has drawn increasing attention for an improved engineering design and decision makings in subsurface developments. Robust and efficient upscaling techniques for heterogeneous reservoirs have emerged as the key to enable field-scale reservoir-geomechanical assessments while consider the impact of lithological heterogeneities like weak bedding planes . The proposed upscaling technique is based on local continuum geomechanical simulations with user-defined boundary conditions on each upscaled region, thus, it can reproduce the anisotropic stress-dependent failure criteria caused by sub-grid scale heterogeneities. This upscaling technique is applied in a reservoir-geomechanical simulation of a steam-assisted gravity drainage (SAGD) project and reduces the computational time by 94%. The complex thermal-hydro-mechanical (THM) interactions in SAGD, including temperature, pressure, saturation fields, surface heave, and plastic strain, are well reproduced by the upscaled model. The minimum factor of safety (FOS) of the caprock for potential shear failure in a field-scale SAGD case study with multilayer caprocks is also reasonably matched by the upscaled model. The improved computational efficiency and reasonable accuracy of the upscaled model can be a useful tool to investigate the impact of injection pressures on production performance and caprock integrity for decision making of SAGD. Moreover, this method addresses the enduring problem of finding anisotropic failure criteria for heterogeneous reservoirs, bridging the gap between computational efficiency and the desire to consider detailed geological features in geomechanical modeling of larger domains. The improved computational efficiency and reasonable accuracy of upscaled models enable reliability analysis and uncertainty quantification for geomechanical analyses that require numerous realizations with complex geology .
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it