Evaluating the feasibility of using a rapeseed oil‐derived anionic polymeric surfactant for enhanced oil recovery from carbonate/sandstone composite reservoirs
Bibliographic record
Abstract
Abstract This study aims to investigate enhanced oil recovery from carbonate/sandstone composite (CSC) reservoirs using a negative‐charged rapeseed oil‐based polymeric surfactant. The polymeric surfactant was first synthesized and characterized. Temperature stability and salt tolerance were then measured. The experiments of interfacial tension (IFT), viscosity, contact angle, and injection of chemical slugs into the CSC plugs were performed. Based on the results, the surfactant remained stable at reservoir temperature and salinity up to 90,000 ppm, and increased viscosity to optimal levels at the critical micelle concentration (CMC) of 4000 ppm and higher. At concentrations ≥3000 ppm, it exhibited non‐Newtonian behaviour, and the IFT was significantly reduced to 62 × 10−3 mN/m at CMC and 21 × 10−3 mN/m at optimum salinity and alkalinity. It also altered the wettability of the rock, reducing the contact angle to 56.29° at CMC. After injecting the polymeric surfactant into a rock plug, oil recovery increased by 26.5%, and water‐cut was minimized to 20%.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".