Pore-Scale Study on Shale Oil–CO<sub>2</sub>–Water Miscibility, Competitive Adsorption, and Multiphase Flow Behaviors
Bibliographic record
Abstract
Due to the fracturing fluid imbibition and primary water, oil–water two-phase fluids generally exist in shale nanoporous media. The effects of water phase on shale oil recovery and geological carbon sequestration via CO 2 huff-n-puff is non-negligible. Meanwhile, oil–CO 2 miscibility after CO 2 huff-n-puff also has an important effect on oil–water two-phase flow behaviors. In this work, by considering the oil–CO 2 competitive adsorption behaviors and the effects of oil–CO 2 miscibility on water wettability, an improved multicomponent and multiphase lattice Boltzmann method is proposed to study the effects of water phase on CO 2 huff-n-puff. Additionally, the effects of oil–CO 2 miscibility on oil–water flow behaviors and relative permeability are also discussed. The results show that due to Jamin’s effect of water droplets in oil-wetting pores and the capillary resistance of bridge-like water phase in water-wetting pores, CO 2 can hardly diffuse into the oil phase, causing a large amount of remaining oil. As water saturation increases, Jamin’s effect and the capillary resistance become more pronounced, and the CO 2 storage mass gradually decreases. Then, based on the results from molecular dynamics simulations, the influences of oil–CO 2 miscibility on oil–water relative permeability in calcite nanoporous media are studied, and as the oil mass percentage in the oil–CO 2 miscible system decreases, the oil/water relative permeability decreases/increases. The improved lattice Boltzmann model can be readily extended to quantitatively calculate geological CO 2 storage mass considering water saturation and calculate the accurate oil–water relative permeability based on the real 3D digital core.
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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 | 0.000 | 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) | 0.000 | 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".