Oil Recovery and Permeability Reduction of a Tight Sandstone Reservoir in Immiscible and Miscible CO<sub>2</sub> Flooding Processes
Bibliographic record
Abstract
In this paper, oil recovery and permeability reduction of a tight sandstone reservoir in immiscible and miscible CO 2 flooding processes are experimentally studied. First, a series of saturation tests are conducted to determine the onset pressure of asphaltene precipitation from a light crude oil−CO 2 system. Second, the vanishing interfacial tension (VIT) technique is applied to determine the minimum miscibility pressure (MMP) between the light crude oil and CO 2 . Third, a total of nine CO 2 coreflood tests under immiscible and miscible conditions are performed through the so-called dry, secondary, and tertiary oil recovery processes, respectively. It is found that the onset pressure of asphaltene precipitation is much lower than the MMP. In the CO 2 secondary oil recovery process, the coreflood test data show that, when the injection pressure is between the onset pressure of asphaltene precipitation and the MMP, the oil recovery factor is higher but the oil effective permeability reduction is larger at a higher injection pressure in the immiscible CO 2 flooding. They both reach almost constant maximum values in the miscible CO 2 flooding ( P ≥ MMP). It is also found that, in three different miscible CO 2 oil recovery processes, the CO 2 tertiary flooding process gives the lowest oil recovery factor but the largest oil effective permeability reduction. This is attributed to the most severe codeposition of asphaltenes and metal carbonates. However, the CO 2 dry or secondary flooding process has a significantly higher oil recovery factor but a much smaller oil effective permeability reduction due to asphaltene deposition alone in the former process or codeposition of asphaltenes and metal carbonates in the latter process.
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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".