Pressure Pulsing Cyclic Solvent Injection (PP-CSI): A New Way to Enhance the Recovery of Heavy Oil through Solvent-Based Enhanced Oil Recovery Techniques
Bibliographic record
Abstract
Abstract Hydrocarbon solvent-based enhanced oil recovery (EOR) techniques, such as vapor extraction (VAPEX) and cyclic solvent injection (CSI), have shown a great potential to recover heavy oil reserves. Solvent dissolution into heavy oil and diluted oil flow are the two main processes of these techniques. VAPEX suffers a low production rate because of the slow mass transfer and inefficient gravity drainage. Although benefited from solution gas drive and foamy oil flow, CSI is bothered with the solvent gas release and viscosity re-increase during the production period, which might seriously slow down the oil production. In this study, it is found that foamy oil flow would generate a foamy oil zone which re-saturated part of the solvent chamber. On the basis of this a phenomenon, this paper proposes a new way to enhance the CSI performance through a three-step pressure control scheme during the production period: first, reduce the model pressure to induce foamy oil flow and foamy oil zone; second, re-increase the model pressure to a preset value; third, maintain a certain pressure difference between injector and producer for gas flooding. This three-step process is called one pressure pulse and it can be consecutively repeated several times during the production period. A series of laboratory experiments have been conducted with a visual rectangular sand-packed physical model. The sandpack permeability is ∼5 Darcy. Propane is used to recover a heavy oil sample with a viscosity of 5,875 cP. Results show that (1) foamy oil could effectively re-saturate the solvent chamber; (2) more pressure pulses would lead to more oil production, while the oil production decreases with pulse number in one cycle; (3) the oil production rate of PP-CSI is 4.37 times of that of conventional CSI, and the final recovery factor of PP-CSI is 17.9% higher than that of CSI. (4) flooding-induced viscous fingering can accelerate the mass-transfer rate; meanwhile, the viscous fingering will not cause an early breakthrough of the solvent chamber.
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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".