Effects of Pressure Decline Rate on the Post-CHOPS Cyclic Solvent Injection Process
Bibliographic record
Abstract
Abstract Cyclic Solvent Injection (CSI) has been proposed as a follow-up process in post-CHOPS reservoirs. The oil recovery factor, which could reach over 50% in lab-scale, is mainly attributed to solution gas drive and foamy oil flow in CSI process. It has been suggested that pressure decline rate has impact on the behavior of solution gas drive and foamy oil flow in cold heavy oil production. However, the role of pressure decline rate in the post-CHOPS CSI process production has not been studied adequately. This work was intended to evaluate the effects of pressure decline rate in CSI process under post-CHOPS reservoirs' conditions. In this study, different pressure decline rate tests were conducted in a large cylindrical sand-pack model with a length of 30.48 and a diameter of 15.24. Single well was applied and connected with a mimic wormhole. In terms of oil recovery factor, the average recovery factor of each cycle increases with the increasing pressure decline rate. But considering the running time, the tests with smaller pressure decline rates showed better total recoveries compared with the tests with larger pressure decline rates. And the residual oil saturation pictures showed that the oil far away from the wellbore could be more easily recovered when a smaller pressure decline rate is applied. In terms of oil production rate, the CSI process production can be typically divided into two phases. In Phase 1, the production rate increases and reaches to the maximum value. In Phase 2, the production rate significantly declines. It was found that the test with a larger pressure decline rate had the higher production rate in Phase 1, while the test with the smaller pressure decline rate had the longest production time in Phase 1. The production rate hardly has dependence on the pressure decline rate in Phase 2. This indicated that for an optimized CSI process the pressure decline rate should be dynamically adjusted in order to have the best performance. The results also suggested that the minimum production pressure exists, below which no oil or marginal amount of oil was produced.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".