Effective Thermal and Electrical Conductivity of Two-Phase Saturated Porous Media
Bibliographic record
Abstract
Abstract Precise pore-level knowledge of effective thermal and electrical conductivities guarantees proper thermophysical and petrophysical characterization of the multiphase saturated porous media. High resolution advancing imaging techniques and developing modeling approaches are capable of simulating pore-scale phenomena in micro- and nano-scales. In this paper, a numerical framework is presented to predict relative electrical and thermal conductivity curves of two-phase saturated pore-level structures. Displacement scenarios are first performed applying a geometrical filling process. A set of rules to construct the fluid interfaces under capillary-driven transport are implemented. Subsequently effective thermal and electrical conductivity curves, quantifying the relationship between conductivity and saturation, are determined using steady state diffusion equation. The media under consideration include three-dimensional binary images of oil/water-wet sandstone and carbonate formations and the fluid systems contain steam-oil and water-oil equilibriums. The result packages, including thermal diffusivity and conductivity, electrical conductivity, formation factor, apparent diffusion coefficient, and saturation exponent, are generated and discussed considering rock types and fluid configurations.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".