Saturation-functions models in CO2-brine system: A comparative study
Bibliographic record
Abstract
CO2 injections into deep saline aquifers create a multiphase flow system within the porous media. In this context, relative permeability and capillary pressure, as saturation functions, are key parameters that control flow dynamics, simulation accuracy, and operational decisions. Since various models have been proposed for the saturation functions, this study aims to assess the existing models and investigate which model performs best under different circumstances. To this end, we first gathered a comprehensive data set to evaluate the existing models. Following that, the nonlinear fitting of experimental data was used to obtain the parameters of each model. Finally, the root-mean-square error and correlation coefficients were used to assess the accuracy of the fit. Based on the results of capillary pressure analysis, the models can be classified into two main categories. The first category includes models with power-law behavior suitable for homogeneous formations (single curvature), such as Brooks-Corey, Li-Horne, Lambda, Thomeer, Leverett J-function, and modified J-function models. The second category includes Van Genuchten, Kosugi, Skelt-Harison, Johnson, and Jing-Van Wunnik, which can be applied to homogeneous and heterogeneous formations (capture more than one curvature). Regarding relative permeability, the L.E.T., Chierici, Van Genuchten, and Corey models exhibit comparable performance across all scenarios. Corey offers simplicity with minimal parameters, while Van Genuchten provides more adaptability for complex data sets with more physically based parameters. Document Type: Original article Cited as: Faramarzi, M., Tabatabaei, S. M., Sedaee, B., Attari, N., Panahi, S. A. Saturation-functions models in CO2-brine system: A comparative study. Capillarity, 2025, 14(2): 35-52. https://doi.org/10.46690/capi.2025.02.01
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".