Dynamic capillarity during displacement process in fractured tight reservoirs with multiple fluid viscosities
Bibliographic record
Abstract
Abstract Dynamic capillarity commonly exists for multiphase flow in porous media, during which fluid viscosity varies and has strong influence. Displacement experiments are conducted on water‐wet, fractured tight rock at in situ pressure and temperature of an oil reservoir via a specially designed apparatus to investigate the effects of fluid viscosity on the dynamic capillarity. The dynamic effect in the matrix is examined through the measurement and calculation of capillary pressure, the dynamic coefficient, and the fluid flow behavior. The results show that with a higher oil viscosity: (a) both the steady and the dynamic capillary pressures reverse their directions more quickly and behave as larger resistances in the matrix; (b) the difference between the steady and the dynamic capillary pressures becomes around 5%‐19% more significant; (c) water saturation changes more slowly corresponding to the lower water relative permeability, while oil relative permeability quickly becomes lower than that during the basic displacement process; and (d) the dynamic coefficient becomes 2‐3 times higher, and the dynamic contact angle becomes 10%‐25% larger, showing a more variable interface. A contact angle advancement coefficient is proposed to identify the significance of contact angle advancement and the competition between capillary pressure and viscous force. The findings of this study can help for better understanding of multiphase flow in tight reservoirs and enhancing oil recovery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".