Insight into the molecular level detachment process of crude oil from the calcite surface by CO2 and CO2/N2 gas injection
Bibliographic record
Abstract
CO2 flooding and CO2/N2 mixed flooding have demonstrated great potential in enhancing oil and gas recovery. However, the molecular-level mechanistic details, especially within complex systems involving specific mineral surfaces like calcite, require further clarification. To clarify these processes, we employed molecular dynamics simulations to examine oil phase adsorption on calcite and the microscopic interactions among gas, oil, and calcite walls. The findings reveal that the highly polar compounds, like benzoic acid and n-heptanoic acid, exhibit stronger and more stable adsorption to the calcite surface, making them less prone to removal by pure CO2. In contrast, less polar hydrocarbons like n-heptane and n-dodecane form oil films that are more easily stripped. Additionally, during the mixed oil phase adsorption, polar compounds tend to localize closer to the wall. The gas phase (CO2, CO2/N2) displaces oil molecules primarily through competitive adsorption on calcite and dissolution of oil molecules. The interaction between gas and oil is stronger than that between oil and calcite, highlighting a key condition for effective oil detachment. CO2 exhibits stronger adsorption on calcite and greater oil solubility than N2. Accordingly, the interaction between the gas and oil phases, along with the oil stripping efficiency, increases with the CO2 content. van der Waals energy dominates interactions between CO2/N2 and hydrocarbons, as well as between calcite and these hydrocarbons. In contrast, electrostatic energy governs interactions between calcite and polar compounds. These findings offer molecular-level insights to guide gas injection strategies for enhanced oil recovery in carbonate formation.
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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) | 0.003 | 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".