Effects of Viscous and Capillary Forces on CO<sub>2</sub>Enhanced Oil Recovery under Reservoir Conditions
Bibliographic record
Abstract
Carbon dioxide flooding has been proven to be one of the most effective and viable enhanced oil recovery (EOR) processes for light and medium oil reservoirs. In the past, an extremely large number of laboratory experiments and numerical simulations have been conducted to study the CO 2 EOR process. However, the specific effects of viscous and capillary forces on this tertiary oil recovery process are neither thoroughly studied nor well understood yet. In this paper, an experimental study is carried out to examine the detailed effects of viscous and capillary forces on the CO 2 EOR under the actual reservoir conditions. First, the equilibrium interfacial tensions between a light crude oil and CO 2 are measured at different equilibrium pressures. Second, a series of CO 2 coreflood tests are performed to measure the CO 2 EOR at different CO 2 injection pore volumes, pressures, and rates. Each CO 2 coreflood test is terminated after a total of 1.5 pore volume of CO 2 is injected. The detailed experimental results show that, in general, the measured equilibrium interfacial tension is reduced with the equilibrium pressure but the measured CO 2 EOR at 1.5 pore volume of CO 2 is increased with the CO 2 injection pressure and rate. Finally, the measured CO 2 EOR at 1.5 pore volume versus injection pressure data at different CO 2 injection rates are related to the measured equilibrium interfacial tension versus equilibrium pressure data in terms of the complete capillary number, which is defined as the ratio of the viscous force to the capillary force for each CO 2 coreflood test. This study shows that if the complete capillary number is in an intermediate range, the CO 2 EOR increases quickly with the complete capillary number. Otherwise, the CO 2 EOR is lower and remains almost constant for a smaller complete capillary number, or it is higher and remains unchanged for a larger complete capillary number.
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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 | 0.001 |
| 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 | 0.001 |
| 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".