Optimization of CO2 Flooding Strategy to Enhance Heavy Oil Recovery
Bibliographic record
Abstract
Abstract CO2 flooding is one of the most promising techniques to enhance both light and heavy oil recovery. In light oil recovery, the production pressure in CO2 flooding in general keeps constant in order to maintain the miscibility of injected CO2 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 work, different pressure control schemes were tested by 1-D core-flooding experiments to obtain an optimized one. Numerical simulations were then conducted to history match all experimental data to understand the mechanisms and characteristics of different CO2 flooding strategies. For the core-flooding experiments, 1500mD 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 CO2 flooding test, early stage water-flooding was conducted until the water cut reached 90%. Different CO2 injection rates and production pressure control strategies were tested through core-flooding experiments. Experimental results indicated that a slower CO2 injection rate (2ml/min) led to a higher recovery factor from 31.1% to 36.7%, compared with a high CO2 injection rate of 7ml/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 47.2KPa/min at the production port yielded 7% more oil recovery; and the best pressure control scheme in which the production pressure keeping constant during CO2 injection period, then depleting the model pressure with the injector shut-in yielded a recovery factor of 42.5% of the initial OOIP. Numerical simulations were conducted to history match the experimental results. The same oil relative permeability curve was used 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 was 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 CO2 injection performance for enhanced heavy oil recovery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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 teacher head, 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".