A Novel Tripod Methodology of Scrutinizing Two-Phase Fluid Snap-Off in Low Permeability Formations from the Microscopic Perspective
Bibliographic record
Abstract
According to the requirements of carbon-neutral development, this study explores the comparison and new discussion of replacing nitrogen with carbon dioxide in the conventional two-phase microfluid flow. Thus, carbon dioxide application in various fields can be more precise and convenient. This research uses an artificially continuously tapering micro model to mimic the natural rock channel in low permeability formation, where the liquid imbibition process is entirely under surface tension-dominant. The tested capillary number decreased to 8.49 × 10−6, and the thinnest observed liquid film was reduced to 2 μm. The comparison results in two gas groups (nitrogen and carbon dioxide) show that CO2 gas fluid in microscopic porous media would have more tendency to snap off and leave fewer residual bubbles blocked between the constrictions. However, the N2 gas fluid forms smaller isolated gas bubbles after snap-off. By combining the experimental data and numerical output with the theoretical evolution equation by Beresnev and Deng and by Quevedo Tiznado et al., the results of interface radius, temporal capillary pressure, and velocity profiles for axisymmetric and continuously tapering models are presented and validated. Those findings create a paradigm for future studies of the evolution of microscopic multiphase fluid and enhance a deeper understanding of geological underground fluid properties for greenhouse gas storage and utilization in low permeability formations.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".