Geomechanical and Thermal Reservoir Simulation Demonstrates SAGD Enhancement Due to Shear Dilation
Bibliographic record
Abstract
Abstract A novel numerical analysis is described, in which the steam-assisted gravity drainage (SAGD) recovery process in bituminous oil sand is studied. A geomechanical/reservoir simulator was modified to incorporate the absolute permeability increases resulting from the progressive shear dilation of oil sands. The objective was to obtain a realistic prediction of shear dilation, as the oil sands approached failure and beyond, and the concomitant increases in permeability. Changes in the in situ stresses that caused this dilation were due to the combined effects of reduced effective stress with high-pressure steam injection, and increased deviatoric stress with thermal expansion under lateral confinement. The resultant volumetric strains were used to modify the absolute permeability characteristics of the oil sands as the SAGD process progressed. The spatial and temporal growth of enhanced permeability zones resulted in an accelerated steam chamber growth. The relationship between volumetric strains and absolute permeability changes was obtained from existing laboratory data on quality specimens of non-bituminous Athabasca oil sands. The source sample was obtained from an outcropping of the McMurray Formation, thus avoiding most of the sample disturbance associated with unconsolidated core obtained conventionally. Under triaxial loading, the resultant volumetric strains increased absolute permeabilities by a factor of 4 to 6. The analysis is innovative in that the model used an effective stress approach, and used the volumetric strains to modify absolute permeabilities. Thus, the encroaching SAGD steam chamber was found to modify the stress regime, which in turn modified the permeabilities within the reservoir. Geomechanical enhancement of the SAGD process was found to be a significant beneficial effect, and would be increased by operating the SAGD process at higher injection pressures.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".