Effect of Wettability on Vaporization of Hydrocarbon Solvents in Capillary Media
Bibliographic record
Abstract
Summary Tight rock reservoirs have gained popularity and become a subject of great interest because of their huge recovery potential. A substantial portion of the potential hydrocarbon could be removed from the reservoir by injecting solvent gases [hydrocarbon or carbon dioxide (CO2)] as an enhanced-oil-recovery (EOR) application. Achieving precise modeling of these processes and an accurate description of hydrocarbon dynamics requires a clear understanding of phase-change behavior in a confined (capillary) medium. It was previously shown that early vaporization of liquids could occur in channels that were larger than 1000 nm. The surface wettability plays a critical role in influencing the vaporization and condensation nature in confined systems. This paper studies the influence of the medium wettability on phase-transition temperatures of liquid hydrocarbons in macrochannels (greater than 1000 nm) and nanochannels (less than 500 nm) by using different types of rock samples. The boiling temperature of hydrocarbon solvents was measured in two extreme wetting conditions: (1) strongly water-wet and (2) strongly oil-wet. Boiling temperatures of heptane and octane in sandstone, limestone, and tight sandstone were observed to be lower than their bulk boiling points by 13% (4% in Kelvin units), on average. Altering rock wettability characteristically changes the average hydrocarbon nucleation temperatures, being as critical as the pore size. Changing sandstone’s wettability to strongly oil-wet shifted the average nucleation temperature of heptane and octane by 6% (1.3% in Kelvin units) and 15% (0.8% in Kelvin units), compared with cases before wettability alteration. The experimental outcomes also showed that reducing the solvent adsorption on clays in Berea sandstone lowers the nucleation temperature of heptane and octane from their normal phase-change temperatures by 20% (4.3% in Kelvin units) and 30% (6.5% in Kelvin units). In comparison with the medium wettability alteration, reducing the solvent adsorption had a greater influence on nucleation temperatures. Such a phenomenon shows that molecule-solid interactions have more control of altering the phase behavior of solvents than of medium wettability.
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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".