Motion of an Oil Droplet Through a Water-Filled Uneven Pore
Bibliographic record
Abstract
\n The need to understand various mechanisms governing fluid-fluid displacements associated with enhanced oil recovery provides the motivation for this study. The observation of apparently linear dependence of flow rates upon pressure gradients during multiphase flow through porous media conceals the true nature of displacement phenomena such as Haine's jumps, droplet break-up, coalescence, etc. Most of these phenomena are understood only qualitatively. This study is on attempt to quantitatively describe them for a specific idealized pore geometry using approximate quasi steady-state calculations. The progress of a non-wetting oil droplet down a periodically convergent-divergent pore, the basic unit of which is a truncated bicone, shows a fluctuating, piecewise continuous track that resembles Haine's jumps. In addition to Haine's jumps, variations in the motion of droplets may also occur due to their break-up, coolescence or the instability of their interfacial configurations. Different parts of a droplet may be required to adjust to different curvatures and sometimes it may fail to maintain a constant mean curvature throughout its interface. Consequently, while flowing through constrictions, a droplet may break-up. Some portions of broken droplets may then travel in the middle of the pore and sometimes may coalesce with each other in different portions of the pore. The droplets become immobilized whevener the pressure gradients available across them are insufficient to overcome the threshold pressure offered by their interfaces. Possible implications of these phenomena in the entrapment of residual oil, hystereses in capillary pressure and relative permeability curves, and fluctuations in the multiphase flovv of fluids through porous media are discussed.\n
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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 | 0.001 |
| 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".