Imbibition behaviors in shale nanoporous media from pore-scale perspectives
Bibliographic record
Abstract
In shale reservoirs, spontaneous imbibition is an important mechanism of fracturing fluid loss, which has an important impact on enhanced oil recovery and water resource demand. However, spontaneous imbibition behaviors are more complicated to characterize and clarify due to the nanoscale effects of the boundary slip, oil-water interfacial slip, and heterogeneous fluid properties caused by intermolecular interactions. A nanoscale multi-relaxation-time multicomponent and multiphase lattice Boltzmann method was applied to investigate the water imbibition into oil-saturated nanoscale space. The effects of pore size, fluid-surface slip, water film, oil-water interfacial slip, water bridge, and pore structures on the imbibition behaviors in a single nanopore were investigated. Then, the spontaneous imbibition behaviors in nanoporous media based on the pore scale microsimulation parameters obtained from the molecular simulation velocity results were simulated, and the effects of water saturations on imbibition behaviors were discussed. The results show that as the water saturation increases from 0 to 0.1, the imbibition mass in nanoporous media increases because of the oil-water interfacial slip and a completely hydrophilic wall. As water saturation continues to increase, the imbibition mass decreases gradually because the existence of water bridges impedes the water imbibition. Document Type: Original article Cited as: Wang, H., Cai, J., Su, Y., Jin, Z., Wang, W., Li, G. Imbibition behaviors in shale nanoporous media from pore-scale perspectives. Capillarity, 2023, 9(2): 32-44. https://doi.org/10.46690/capi.2023.11.02
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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 | 0.000 | 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".