Effective properties of two‐phase flow in heterogeneous aquifers
Bibliographic record
Abstract
The spectral perturbation approach is employed to predict the field‐scale relative permeabilities and the variance of capillary pressure and saturation under steady two‐phase flow conditions. The theoretical analysis treats stationary three‐dimensional variations in pressure and flow produced as a result of spatial variations of permeability and two‐phase flow characteristics. The analysis is developed in a general form that is applied to different commonly used two‐phase flow characterizations, and results are illustrated for two‐phase flow characteristics corresponding to those observed at the Borden site in Canada. For gravity‐driven flow in horizontally layered aquifers, both nonwetting phase flow (dense nonaqueous phase liquid (DNAPL) flow) and wetting phase flow (water, unsaturated flow) show effective vertical relative permeabilities that are substantially decreased in comparison with those corresponding to a homogeneous system. The resulting saturation‐dependent anisotropy of effective permeability is substantially larger for DNAPL flow than for the case of unsaturated flow. The Leverett scaling characterization frequently used in Monte Carlo simulations is shown to underestimate system anisotropy owing to omission of variability of the parameter governing the slope in the capillary pressure–saturation function. Application of the Brooks‐Corey characterization of the relative permeability resulted in significantly greater anisotropy than with the van Genuchten characterization. In contrast to the strong influence of heterogeneity predicted in the case of effective permeabilities, the effective capillary pressure characteristic (mean capillary pressure versus mean saturation curve) is only weakly influenced by heterogeneity.
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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 | 0.002 |
| 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 | 0.001 |
| 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".