Modelling of viscoelastic properties of porous rocks saturated with viscous fluid at seismic frequencies at the Core Scale
Bibliographic record
Abstract
Summary Here we attempt to model the dynamic moduli of porous rocks saturated with viscous fluid at seismic frequencies on core scale based on the strain-stress method, aiming to provide a complement to real core measurements in lab. First, we build 2D geometrical models containing the pore structure information of porous rocks based on the digital images (such as thin section, SEM, CT, etc.) of real rocks. Then we assume the rock frames are linearly elastic, and use the standard Maxwell’s spring-dash pot model to describe the viscoelastic properties of pore fluids. Boundary conditions are set according to the stress-strain method; and the displacement field is calculated using the finite element method (FEM). We numerically test the effects of pore structure on the viscoelastic properties of saturated rocks. The preliminary results indicate that the pore structure parameters, such as porosity, aspect ratio (AR), and pore size affect the rock frame stiffness and results in different viscoelastic behavior of the saturated rocks. The stress-strain phase lags are larger with smaller stiffness contrasts between the rock frame and the pore fluid. The viscoelastic properties of saturated rocks are more sensitive to AR compared to other pore structure parameters.
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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 | 0.001 |
| 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 | 0.001 | 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".