Experimental study on the performance of emulsions produced during ASP flooding
Why this work is in the frame
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Bibliographic record
Abstract
Abstract ASP (Alkaline/Surfactant/Polymer) flooding is one of the most promising techniques that has proven to have successful application in several laboratory and pilot tests. However, the formation of persistent and stable emulsions is one of the associated problems with ASP flooding. The present work investigated the effect of sodium carbonate alkaline, Alpha Olefin Sulfonate (AOS) surfactant, and GLP100 polymer on produced crude oil emulsion. The study was conducted by measuring the emulsion stability in terms of water separation and rag layer volume using a TurbiScan analyzer, the dispersed droplet size using cross-polarization microscopy, the interfacial tension using spinning drop tensiometer, and rheological properties using rheometer. The experimental results have shown that AOS presence increased the emulsion stability only when its concentration is above 100 ppm. Meanwhile, below 100 ppm, the presence of AOS promoted water separation and reduced the rag layer volume. In a less significant manner, a high concentration of sodium carbonate alkali increased the stability of the emulsion. The use of GLP100 Polymer has shown substantial ability in promoting water separation and reducing the rag layer volume to a minimal level. It is believed that the outcomes of this work will aid in developing a suitable destabilization process to enhance the oil–water separation and produced water treatment from ASP flooding in the oil production fields. Further investigations on AS, AP, SP as well as the ASP's combined effect on emulsion stability, droplet size, interfacial tension and rheological properties are highly recommended to support the decision-makers on the EOR implementations with chemical additives.
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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 | 0.000 | 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 it