Coupled Fluid Flow-Thermoplastic Deformation of Oil Sand and Shale in SAGD Process
Bibliographic record
Abstract
Abstract Steam-Assistant-Gravity-Drainage (SAGD) has become one of the most commonly used thermal recovery processes to extract heavy oil from oil sand reservoirs, especially in Northern Alberta, Canada. However, due to geological history, interbedded shales (IBS) in the reservoir act as barriers due to their low permeability and as such hinder the progression of the steam chamber. Cap-rock integrity also needs to be ensured to prevent steam breakthrough. Therefore, a comprehensive investigation of geomechanics is required in modeling SAGD processes to properly address the above issues. The numerical simulation of SAGD typically solves classic multiphase fluid flow equations, but with seemingly less detailed reservoir thermo-hydro-mechanical (THM) deformation calculations. However, the latter play a major role in SAGD responses in that the injection of steam significantly alters both the pore fluid pressure and temperature fields in the reservoir, which in turn impact on effective (skeleton) stresses. The latter inevitably leads to plastic deformations which eventually cause geomechanical failure inside and above the reservoir. Relevant to this issue is the dilatancy of geomaterials under shearing that increases the pore volume, and thus permeability. Hence, a proper treatment of such effects requires the coupling of multiphase flow with geomechanics. In this paper, the THM behavior of the reservoir was studied through a proper constitutive modeling of the porous media. Specifically, a generalized density-stress-fabric dependent elasto-plastic model with stress-dilatancy and plastic damage as main ingredients was implemented into COMSOL (2012), a commercial finite element programming environment, to model geomechanical behavior during SAGD process. The strength and deformation of oil sand and IBS were evaluated through the respective stress-strain relationships, including stress path analysis. As such, geomechnical effects would be highlighted in view of the global operation and performance of the SAGD process.
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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".