Silica Nanoparticle Enhancement in the Efficiency of Surfactant Flooding of Heavy Oil in a Glass Micromodel
Why this work is in the frame
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Bibliographic record
Abstract
The synergistic effects of fumed-Si nanoparticles (Si-NPs) in combination with sodium dodecyl sulfate (SDS) surfactant as suitable agents for oil displacing in enhanced oil recovery (EOR) are evaluated using a 5-spot glass micromodel. Optimum oil recovery (45%) is obtained for SDS near the critical micelle concentration; however, the addition of fumed silica nanoparticles (Si-NPs) enables a further 13% enhancement in oil recovery for the maximum concentration of the SDS/Si-NPs (2.2 wt %) as well as delaying the breakthrough point. The optimum mass ratio of SDS:Si-NP (1:11) suggests that the Si-NPs are aggregated by the SDS micelles, consistent with increased viscosity upon addition of Si-NPs. The presence of the Si-NPs also greatly increases the wettability on the glass surface with a decrease in the contact angle from 73° for SDS (1800 ppm) to 11° for SDS/Si-NPs (1800 ppm/2.0 wt %). The effective changes in the oil sweeping mechanism are directly observed in the glass micromodel and correlate to these physical measurements. The results demonstrated that addition of Si-NPs to SDS solutions made a significant improvement to oil recovery values and is potentially beneficial in EOR applications.
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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 | 0.002 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it