Re-Examination of Fingering in SAGD and ES-SAGD
Bibliographic record
Abstract
Abstract Steam-Assisted Gravity drainage (SAGD) is a popular approach for oil sands recovery, in which a steam chamber is developed inside reservoir with heated up bitumen flowing downwards along the edge of the steam chamber to production well by gravity. To improve the production performance of SAGD, solvent co-injection with steam (called ES-SAGD) is also proposed. In both SAGD and ES-SAGD, the penetration of low viscosity gas phase into viscous bitumen induces fingering at the steam chamber edge, resulting in non-uniform steam chamber. In this study, for the first time, the phenomenon of fingering is re-examined under the condition of mobile initial-water in oil sands through a newly designed reservoir simulation model. The effect of Solution Gas to Oil Ratio (GOR) on fingering in SAGD is also studied. In addition, the impact of solvent-water-bitumen phase behavior, which is critical to the amount of gas phase, on fingering is examined in ES-SAGD. The results reveal that fingering takes place at the oil zone on the top of steam chamber in SAGD, due to the ex-solution of solution gas under elevated temperature. The addition of solvent in ES-SAGD enhances the fingers by reducing the partial pressure of the solution gas and increasing the amount of solution gas at the top of steam chamber. It is found that the flow of the initial-water in oil sands mitigates the degree of fingering and helps stabilize steam chamber edge. This re-examination of fingering in SAGD and ES-SAGD demonstrates that the mobility of the initial water in oil sands has to be taken in account in the analysis of steam chamber instability.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".