Macroscopic mechanical properties of fluid-saturated sandstone at variable temperatures
Bibliographic record
Abstract
ABSTRACT Rocks can be viewed as composites of solid minerals with pores or cracks filled with softer material such as pore fluids, kerogen, bitumen, and other organic matter. The mechanical properties of highly viscous soft phases are highly sensitive to ambient temperatures and lead to temperature-dependent static and dynamic observations with the composite rock. However, the constituents operate by forming some effective (averaged) mechanical properties of the composite rock, and yet these averaged properties are still little known. To reveal such macroscopic temperature-dependent mechanical properties and measure their values in rock samples, a double-porosity model of porous rock with nonlinear viscosity is developed. The model is based on rigorous continuum mechanics with physically meaningful, real-valued, and time- and frequency-independent material properties and elegantly unifies the existing frequency-dependent microscopic squirt flow and mesoscopic wave-induced fluid flow models. The approach is used to accurately model the broad attenuation peaks and Young’s modulus dispersion observed in previously published laboratory experiments with glycerol-saturated Berea sandstone and invert for its mechanical properties. The observations are explained as mainly due to the temperature-dependent elastic coupling caused by non-Newtonian fluid within microcracks. Several hitherto unknown mechanical properties of the rock are constrained quantitatively: the average porosity of the microcracks, the effective high-pressure bulk modulus of the drained frame, the internal stiffness defect within the rock frame, the solid viscosities associated with bulk and shear deformations, and an exponent of nonlinearity for viscosity. These parameters constitute a Biot-consistent mechanical model of the rock, which can be used to simulate its behavior in arbitrary experimental environments. The rigorous first-principle model can be used in many applications: detailed and physically accurate interpretations of laboratory experiments, numerical wavefield simulations and seismic data inversion, reservoir characterization, geothermal exploration, thermal-enhanced oil recovery, and exploration for deep oil and gas resources in high-temperature environments.
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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 | 0.000 | 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".