Microscopic Study of Oil Flocculation and Coalescence Processes for Understanding the Role of Surfactants in EOR Performance
Bibliographic record
Abstract
A preliminary microscopic study of oil/oil droplet interactions in surfactant-added water is carried out to understand the oil/water interface changes with time and its effects on oil/oil droplet coalescence. This study is carried out on two oils (olive and crude oil) with varying concentrations of surfactant water ratios. The radii of curvature of the interface between coalescing oil droplets is used as a measure to reflect the change in surface energy. As oil droplets were placed in surfactant-added water, the radii of curvature were measured at three different states. Early state shows very little effect on oil/oil interfaces; in the later state, the effect is greater and interfacial tension decreases rapidly. At quasi-steady state, the state between the early and later, faster rate stage reduces with surfactant concentration in the case of olive oil. Increasing the surfactant concentration does not show the same effect on crude oil. The radii of curvature increase with time by increasing surfactant concentrations in olive oil; an inverse effect is found in crude oil. A natural surfactant prepared from the outer shell of pericarp of soapnut fruit was also used to study droplet formation and coalescence as well as to investigate the impact in interfacial tension and oil mobility.
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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) | 0.002 | 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".