Contribution of Geomechanics in Evaluation of Heat Transfer Mechanisms at Mobile Zone of SAGD and ES-SAGD
Bibliographic record
Abstract
Abstract Efficient recovery of heavy oil and bitumen in western Canada has widely been applied with thermal-based processes. The well-known Steam-Assisted Gravity Drainage (SAGD) takes advantage of the strong dependency of bitumen viscosity on temperature ranging from 10 to 250 °C. The latent heat of injected steam is released as the steam chamber develops and causes the bitumen to mobilize and drain under the effect of gravity toward the production well. Co-injection of solvent with steam (ES-SAGD) may help to reduce the oleic phase viscosity adjacent to chamber edge by offsetting the temperature reduction effect. While many researchers are currently tackling the optimal operational conditions from a fluid property point of view (pressure, solvent fraction, etc.), less attention was paid to the impact of heat transfer due to incorporation of geomechanics into occurring physics. Such simplifications in analyzing the real processes physics would result in neglecting of the convection flow of heat along with conduction. Considering the dramatic changes in temperature at the chamber edge, the induced thermal geomechanical responses would lead to a faster fluid movement. The fluid mobility at the edge of chamber would even increase more, mainly because of temperature-dependant heat capacity of water, changes in absolute and relative permeabilities, and possible wettability alteration. If a multi-component solvent is used (ES-SAGD), the assessment of production performance would get more complicated due to the different condensation dynamics of light versus heavy components and the possible gas-blanket effect caused by the co-injected solvent. In this study, the geomechanical changes due to pressure and temperature effects were considered at the steam chamber, for both SAGD and ES-SAGD scenarios. The thermo-poro-elasticity concept, with elastic constitutive rock behaviour, was chosen for geomechanical study. The primary impacts of geomechanics on the physics of ES-SAGD were rock and fluid alterations, and changes in petrophysical properties (porosity and absolute permeability). Assuming a potential change in rock and fluid interaction due to geomechanics, the same analysis was conducted for a multi-component solvent with different condensation profiles. It was shown how the use of solvent will adversely affect the induced thermal geomechanics contribution. The findings of this paper can be used as a guideline for further experimental studies on the effect of geomechanics in thermal-based recovery processes.
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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 | 0.001 | 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".