Modeling the permeability evolution of microcracked rocks from elastic wave velocity inversion at elevated isostatic pressure
Bibliographic record
Abstract
A key consequence of the presence of microcracks within rock is their significant influence upon elastic anisotropy and transport properties. Here two rock types (a basalt and a granite) with contrasting microstructures, dominated by microcracks, have been investigated using an advanced experimental arrangement capable of measuring porosity, P wave velocity, S wave velocity, and permeability contemporaneously at effective pressures up to 100 MPa. Using the Kachanov (1994) noninteractive effective medium theory, the measured elastic wave velocities are inverted using a least squares fit, permitting the recovery of the evolution of crack density and aspect ratio with increasing isostatic pressure. Overall, the agreement between measured and predicted velocities is good, with average error less than 0.05 km/s. At larger scales and above the percolation threshold, macroscopic fluid flow also depends on the crack density and aspect ratio. Using the permeability model of Guéguen and Dienes (1989) and the crack density and aspect ratio recovered from the elastic wave velocity inversion, we successfully predict the evolution of permeability with pressure for direct comparison with the laboratory measurements. We also calculate the evolution of the crack porosity with increasing isostatic pressure, on the basis of the calculated crack density, and compare this directly with the experimentally measured porosity. These combined experimental and modeling results illustrate the importance of understanding the details of how rock microstructures change in response to an external stimulus when predicting the simultaneous evolution of rock physical properties.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".