A simple hydromechanical approach for simulating squirt-type flow
Bibliographic record
Abstract
ABSTRACT The deformations caused by an acoustic wavefield in subsurface rock can induce fluid flow within hydraulically interconnected mesoscopic fractures, from one fracture into the other. The viscous friction associated with this squirt-type fluid flow parallel to the fracture walls results in energy dissipation and velocity dispersion. We have developed a quasi-static hydromechanical approach that is suitable for simulating squirt-type flow in the mesoscopic scale range and microscopic squirt flow. Our approach couples Navier-Stokes equation with Hooke’s law to describe the laminar flow of a viscous compressible fluid in conduits embedded in an elastic solid background. Results from the proposed method were compared with those obtained with Biot’s equations for a model containing interconnected mesoscopic fractures embedded in a background of very low porosity and permeability. Despite significant differences in the flow and dissipation spatial patterns, we have observed an essentially perfect agreement of the attenuation and modulus dispersion characteristics predicted by the two approaches. The difference in the flow and dissipation spatial patterns are associated with the “upscaling” inherent to Biot’s equations and, correspondingly, with differing boundary conditions at the fracture walls. Our results demonstrate that the proposed hydromechanical approach can provide additional insights on the physics of squirt-type flow in the mesoscopic and microscopic scale ranges.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".