The effects of the pore throat roughness on the water-oil flow in rock reservoirs
Bibliographic record
Abstract
As one of the important factors to affect the oil-water flow,it is requisite to study the influence of the pore throat roughness on flow behaviors.In this paper the Lattice Boltzmann method is employed to model the water displacing oil in the flat and the rough pore throat models.The comparisons of the water saturation and water-oil relative permeability in different models show that: 1) both in the flat and the rough pore throat models,the roughness would retard the oil and water flow in the process of water displacing oil no matter the pore throat wall is water-wet or oil-wet;2) some oil are trapped in the grooves between the rough elements and the maximal displacing efficiency is under 100% in the case of water displacing oil;3)the displacing efficiency in the water-wet models is higher than that in the oil-wet pore throat models,and there are higher water saturation,water and oil relative permeability in the water-wet models;4)the roughness has a more apparent effects in water-wet models than in the oil-wet models;5)once the wall roughness reaches a level,it effects on flow behaviors are not increased with the growing roughness any more in the oil-wet pore throat models.
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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 | 0.001 |
| 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) | 0.000 | 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".