A New Criterion for the Estimate of Impact of Lean Zones on the Performance of SAGD/SA-SAGD/EBRT Processes
Bibliographic record
Abstract
Abstract This paper proposes a new criterion to estimate the impact of lean zones on thermal or thermal-solvent processes, such as SAGD, SA-SAGD, or EBRT (Imperial Oil's "Enhanced Bitumen Recovery Technology"). The interface stability of the steam/solvent chamber in the lean zone is related to the competition of heat transfer in either conductive or convective forms. This competition is described by a non-dimensional number, the Rayleigh number in porous media, which can be calculated by the parameters of the lean zone thickness, water mobility, thermal diffusivity, and steam chamber temperature. When a system's Rayleigh number is larger than a critical value, the primary heat transfer mechanism in the lean zone will be convection, in which the interface becomes unstable and may cause significant loss of steam or solvent. Analytical solution to obtain the critical Rayleigh number was given in literature (Philip, 1982). For long axis horizontal cross sections, the critical Rayleigh number is estimated between 0.1 and 1. A significant number of simulation cases have been analyzed in a sensitivity study with CMOST (Computer assisted Matching, Optimization, and Sensitivity analysis Tool, Computer Modeling Group) to validate the above hypothesis. Monte Carlo simulation results have shown a strong correlation between the solvent recovery and the product of water mobility and lean zone thickness. This product is the essential part of the formula of modified Rayleigh number. Further calculation indicated that the critical Rayleigh number for the simulation models is between 0.1 ∼ 1 for SA-SAGD or SAGD and about 0.17 ∼ 0.32 for EBRT. Both are within the range given by the analytical solution. The critical Rayleigh number is introduced to the lean zone analysis for the first time. This physics-based criterion is able to give an answer to the estimate of performance impact of the lean zone for thermal and thermal-solvent gravity drainage processes. The Monte Carlo simulation confirmed the consistency between the numerical studies and the analytical solution.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".