A Theoretical Explanation for Wettability Alteration by Adding Nanoparticles in Oil-Water-Tight Rock Systems
Bibliographic record
Abstract
We evaluated the idea of adding nanoparticles in an aqueous phase to enhance its wetting affinity to siltstone core plugs by conducting dynamic contact-angle experiments and by calculating the total interaction energy. We analyzed the performance of a colloidal dispersion with highly surface-modified silicon dioxide nanoparticles (NP). The rock samples are oil-wet when they are initially aged in the reservoir brine, and they are water-wet when initially soaked in the NP solutions (limiting conditions). To mimic the downhole conditions when the pumped fluid with nanoparticles is mixed with reservoir brine, we measured the change in contact angle of oil droplets initially equilibrated on the rock surface soaked in the reservoir brine during diffusion of the introduced nanoparticles. The results show that the diffusion of nanoparticles through the brine toward the oil droplet alters the system wettability from oil-wet to water-wet conditions. To investigate the mechanisms responsible for the observed wettability alteration, we analyzed aqueous-film stability using the Derjaguin, Landau, Verwey, and Overbeek theory. The calculated interaction energy for the cases of NP solutions is higher than that for the tap water and brine cases, indicating stronger repulsion between the rock and oil across the film of NP solution, leading to a more stable film. Increasing water salinity reduces the stability of water film due to the reduction of total interaction energy. The wettability alteration by the NP solution is more pronounced in the presence of low-salinity water.
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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".