A fractal effective permeability model for dual-wet porous Media
Bibliographic record
Abstract
Recent studies have shown that the pores of some unconventional rocks can be categorized into hydrophilic pores that boarded by inorganic minerals such as quartz and hydrophobic pores that within the organic matter. The rock which consists of both hydrophilic and hydrophobic pores shows a dual-wettability behavior. The previously-proposed imbibition transient analysis technique has been applied in characterizing the pore size distribution of the dual-wet rocks by analyzing comparative oil and water imbibition data. On the basis of the determined pore size distribution, a fractal model for estimating effective permeability of the dual-wet rock was proposed. The proposed model, together with the imbibition transient analysis technique, is able to estimate effective permeability of the dual-wet rocks by using imbibition data. The proposed model can also estimate the effective permeability of hydrophilic pores and hydrophobic pores. The proposed model takes injection pressure, wettability behavior and pore size distribution of the dual-wet rock into the consideration. Our sensitivity analyses show that injection pressure affects effective permeability and hydrophobic permeability by controlling the water saturation within hydrophobic pores. The rock with higher volumetric fraction of hydrophilic pores tends to have higher hydrophilic permeability and lower hydrophobic permeability. By keeping the porosity constant, effective permeability decreases as the volumetric fraction of small pores increases. Cited as: Shi, Y., Guo, Y., Dehghanpour, H., Song, H. A fractal effective permeability model for dual-wet porous media. Advances in Geo-Energy Research, 2023, 8(2): 100-111. https://doi.org/10.46690/ager.2023.05.04
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".