CO2 flooding strategy to enhance heavy oil recovery
Bibliographic record
Abstract
CO 2 flooding is one of the most promising techniques to enhance both light and heavy oil recovery. In light oil recovery, the production pressure in CO 2 flooding in general keeps constant in order to maintain the miscibility of injected CO 2 and crude oil; while in heavy oil recovery, a depleting pressure scheme may be able to induce foamy oil flow, thus the oil recovery could be further enhanced. In this study, different pressure control schemes were tested by 1-D core-flooding experiments to obtain an optimized one. Numerical simulations were conducted to history match all experimental data to understand the mechanisms and characteristics of different CO 2 flooding strategies. For the core-flooding experiments, 1500 mD sandstone cores, formation brine and a heavy oil sample with a viscosity of about 869.3 cp at reservoir condition (55 °C and 11 MPa) were used. Before each CO 2 flooding test, early stage water-flooding was conducted until the water cut reached 90%. Different CO 2 injection rates and production pressure control strategies were tested through core-flooding experiments. Experimental results indicated that a slower CO 2 injection rate (2 ml/min) led to a higher recovery factor from 31.1% to 36.7%, compared with a high CO 2 injection rate of 7 ml/min; for the effects of different production strategies, a constant production pressure at the production port yielded a recovery factor of 31.1%; while a pressure depletion with 47.2 kPa/min at the production port yielded 7% more oil recovery; and the best pressure control scheme in which the production pressure keeping constant during CO 2 injection period, then depleting the model pressure with the injector shut-in yielded a recovery factor of 42.5% of the initial OOIP. For the numerical simulations study, the same oil relative permeability curve was applied to match the experimental results to all tests. Different gas relative permeability curves were obtained when the production pressure schemes are different. A much lower gas relative permeability curve and a higher critical gas saturation were achieved in the best pressure control scheme case compared to other cases. The lower gas relative permeability curve indicates that foamy oil was formed in the pressure depletion processes. Through this study, it is suggested that the pressure control scheme can be optimized in order to maximize the CO 2 injection performance for enhanced heavy oil recovery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".