Adsorption and Dissolution Behaviors of Carbon Dioxide and <i>n</i>-Dodecane Mixtures in Shale
Bibliographic record
Abstract
CO 2 cyclic injection is a promising method for enhanced shale oil recovery. However, the enhanced shale oil recovery mechanism is unclear, especially the adsorption and dissolution of CO 2 and oil in kerogen. Therefore, it is of great importance to study the adsorption and dissolution mechanisms of CO 2 and oil mixtures in shale. In this study, a new experimental apparatus was designed to test the change in the mole fractions of CO 2 and oil before and after adsorption and dissolution at equilibrium conditions. For simplicity, n -dodecane ( n -C 12 ) was used as the oil. The adsorption and dissolution amounts of CO 2 and n -C 12 were obtained using a mathematical method. Moreover, the adsorption and dissolution characteristics of the CO 2 and n -C 12 mixtures in shale and the effect of pressure on the adsorption and dissolution amounts were studied. Finally, the swelling factor of the shale, which was caused by the dissolution of the mixtures, was calculated from the experimental results. The results show that dissolved n -C 12 in shale could be replaced by CO 2 when the mole fraction of CO 2 in the free phase was larger than a threshold. The adsorption and dissolution amounts of CO 2 and n -C 12 increased with pressure. The lower pressure and larger mole fraction of CO 2 enabled a lower swelling factor of shale. This study provides a straightforward method to experimentally determine the adsorption and dissolution properties of shale, which can be used to evaluate enhanced shale oil recovery by CO 2 injection and the geological storage of CO 2 .
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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".