A Review of Techniques for Measuring the Biot Coefficient and Other Effective Stress Parameters for Fluid-Saturated Rocks
Bibliographic record
Abstract
Abstract Predicting the behavior of a saturated rock with variations in pore fluid pressure during geo-energy production and storage, deep geological disposal of nuclear wastes, etc. with skeletal mechanical behavior in the linear elastic range is carried out using the isothermal theory of poroelasticity that incorporates Biot's effective stress principle. For conditions that are not within linear elasticity, other effective stress coefficients are used. Several experimental methods for determining Biot's and other effective stress coefficients have been documented in the literature. The objective of this study is to review the fundamentals of these techniques, their advantages and disadvantages, and to include several case studies. Current techniques for Biot's coefficient are based on different premises: jacketed and unjacketed bulk moduli or compressibility values; volume changes of the bulk and pore fluid from a drained triaxial test on a saturated sample; isotropic-isochoric compression tests on a saturated sample; matching volumetric strains for dry and saturated samples; estimation of the Biot coefficient from other poroelastic parameters; and approximation of the jacketed bulk modulus from ultrasonic wave velocities and/or unjacketed bulk modulus from the mineralogical compositions. Other effective stress coefficients are based on matching failure envelopes for dry and saturated samples and variations of rock properties (such as volumetric strain, permeability, and ultrasonic wave velocities) with respect to confining stress and pore pressure. This article discusses variations in Biot's and other effective stress coefficients produced using the different techniques and how factors such as pore geometry, test conditions, stress path, and test temperature affect the coefficients.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".