A new pressure control scheme on steam‐assisted gravity drainage for heavy oil production
Bibliographic record
Abstract
Abstract As one the most important recovery mechanisms of steam‐assisted gravity drainage (SAGD), gravity drainage is largely dependent on the inclination angle of the steam chamber edge. The existence of solution‐gas causes an ellipsoid‐shaped chamber that has small inclination angle at the bottom, which leads to inefficient gravity drainage and slows down oil production. To address this problem, this study proposes a new scheme, variable‐pressure SAGD (VP‐SAGD). It is basically a SAGD process, at certain stages of which pressure surge is induced by controlling the operating conditions so that the shape of steam chamber can be altered. This leads to a larger slip angle in the steam chamber at the bottom and more efficient heat transport between hot steam and crude oil. Results show that VP‐SAGD is able to increase oil recovery by up to 20% and decrease cumulative steam–oil ratio (cSOR) by up to 7%. Its special oil extraction mechanisms include swabbing effect, enlarged inclination angle of steam chamber boundary at the bottom, and enhanced heat transfer. Particularly, the inclination angle is increased by up to 40%. In addition, a lower producer bottom‐hole pressure (BHP) during pressure drawdown leads to a better production incremental in later stages. The optimal timing for pressure surge is the middle stage of steam chamber growth. The lower the producer BHP decrease, the better the yield increase. Moreover, The VP‐SAGD strategy works better in heavy oil reservoirs with a permeability of k = 0.5–10 Darcy or solution gas content of greater than 2%.
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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 | 0.000 |
| 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) | 0.001 | 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".