Visual analysis of immiscible displacement processes in porous media under ultrasound effect
Bibliographic record
Abstract
The effect of sonic waves, in particular, ultrasonic radiation, on immiscible displacement in porous media and enhanced oil recovery has been of interest for more than five decades. Attempts were made to investigate the effect through core scale experimental or theoretical models. Visual experiments are useful to scrutinize the reason for improved oil recovery under acoustic waves of different frequency but are not abundant in literature. In this paper, we report observations and analyses as to the effects of ultrasonic energy on immiscible displacement and interaction of the fluid matrix visually in porous media through two-dimensional (2D) sand pack experiments. 2D glass bead models with different wettabilities were saturated with different viscosity oils and water was injected into the models. The experiments were conducted with and without ultrasound. Dynamic water injection experiments were preferred as they had both viscous and capillary forces in effect. The displacement patterns were evaluated both in terms of their shape, size, and the interface characteristics quantitatively and qualitatively to account for the effects of ultrasonic waves on the displacement and the reason for increased oil production under this type of sonic wave. More compact clusters were observed when ultrasonic energy was present in water-wet systems. In the oil-wet cases, more oil was produced after breakthrough when ultrasound was applied and no compact clusters were formed in contrast to the water-wet cases.
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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 | 0.001 | 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".