An Improved CO<sub>2</sub>–Oil Minimum Miscibility Pressure Correlation for Live and Dead Crude Oils
Bibliographic record
Abstract
An improved CO 2 –oil minimum miscibility pressure (MMP) correlation has been successfully developed to more accurately determine the CO 2 –oil MMP for a wide range of live and dead crude oils. Experimentally, slim-tube tests have been conducted to determine the CO 2 –oil MMPs for four crude oil samples with high molecular weights of C 7+ fraction. Theoretically, the newly developed CO 2 –oil MMP correlation is originated from a CO 2 –oil MMP database from the literature that covers 51 CO 2 –oil MMP data for various live and dead oil samples, especially those with high C 7+ molecular weights. The new CO 2 –oil MMP correlation is expressed as a function of reservoir temperature, C 7+ molecular weight, and mole fraction ratio of volatile components (N 2 and CH 4 ) to intermediate components (CO 2, H 2 S, and C 2 –C 6 ). Compared to nine commonly used CO 2 –oil MMP correlations in the literature, it is found that the new CO 2 –oil MMP correlation provides the best reproduction of the literature CO 2 –oil MMP data with a percentage average absolute deviation (% AAD) of 8.08% and a percentage maximum absolute deviation (% MAD) of 22.99%, respectively. To further examine its predictive capability, the new CO 2 –oil MMP correlation is then validated with the four experimentally measured CO 2 –oil MMPs in this study. The newly developed CO 2 –oil MMP correlation leads to the best prediction accuracy of the four measured CO 2 –oil MMPs with a % AAD of 4.18% and a % MAD of 7.01%, respectively.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".