Efficiency of the Green Surfactant Derived from Avena sativa Plant in the Presence of Different Salts for EOR Purposes
Bibliographic record
Abstract
In this investigation, a unique approach using a green surfactant extracted from the Avena sativa (AS) plant in conjunction with three different salts, including Na2CO3, NaCl, and Na2SO4, was examined for enhanced oil recovery. In addition, the efficiency of NaOH as a supplementary chemical in the process was investigated. Based on the results of the interfacial tension (IFT), the optimum value of NaOH was found to be 2,000 ppm, while the green surfactant had a CMC value of 4,000 ppm. The IFT value at the CMC point of NaOH was 2.34 mN/m, when the FB was used, and the IFT value was 2.78 mN/m, when deionized water was used. In addition, in terms of IFT reduction, wettability modification, and oil recovery factor enhancement, Na2CO3 was the most suitable salt with the AS surfactant at the CMC point (4,000 ppm), followed by NaCl and then Na2SO4. The IFT values at the optimum salinity point (10,000 ppm) of Na2SO4, NaCl, and Na2CO3 were 3.18, 3.05, and 2.87 mN/m, respectively. Moreover, the contact angles at the optimum salinity point of 10,000 ppm after 150 hr and at the reservoir temperature (80°C) were 36.58°, 40.76°, and 44.18° with Na2CO3, NaCl, and Na2SO4, respectively. Furthermore, the addition of NaOH improved the efficiency of the green surfactant in terms of maximizing the recovery factor by decreasing the IFT values and changing the wettability of the rock toward a more water-wet state. The final recovery factors of 88.45%, 80.87%, and 7.98% were attained using Na2CO3, NaCl, and Na2SO4, respectively, when 1 PV of NaOH was injected as the preflush, followed by 4 PVs of natural AS surfactant.
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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".