AN APPARATUS FOR SIMULTANEOUS MEASUREMENT OF RELATIVE PERMEABILITY AND DYNAMIC CAPILLARY PRESSURE
Bibliographic record
Abstract
The simultaneous measurement of accurate relative permeability and capillary pressure data is essential for studying the phenomena of two-phase flow in porous media. Conventionally, relative permeability and capillary pressure data are measured separately using different equipment and non-identical core samples or sandpacks. It is rather difficult to maintain the same experimental conditions when measurements are made using different equipment and different porous media samples. Moreover, because relative permeability and capillary pressure can be very sensitive to common variables such as saturation and rock/fluid properties, simultaneous measurement of these properties is extremely important to achieve consistency. A relatively new experimental setup has been constructed to obtain dynamic phase pressure and saturation profiles simultaneously during two-phase flow through porous media under steady state and unsteady state conditions. These experimentally measured properties, along with the other needed data, have then been used to calculate the relative permeability and dynamic capillary pressure profiles. Based on the presented experimental results, it has been found that the new experimental setup is reliable and can reproduce stable relative permeability and dynamic capillary pressure profiles with a minimum level of uncertainty.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".