Effect of kerosene aromaticity as a solvent on bulk and interfacial properties of Brazilian heavy crude oil with high asphaltene content
Bibliographic record
Abstract
Abstract This study investigated the effect of solvent aromaticity on asphaltene stability and interfacial behaviour using typical diluted heavy oils, which better represent the chemical diversity of petroleum components than previous studies that used simple solvent mixtures with low asphaltene concentrations. A Brazilian crude with high viscosity and asphaltene content was diluted with two kerosenes, one containing only saturated compounds (Ke S ), and the other a saturates/aromatics mixture (Ke SA ) to maintain total aromaticity in the oil mixture upon dilution. Viscosity, asphaltene stability, interfacial tension, and elasticity of the oil mixtures were measured, and correlated with emulsion stability, regarding the differences in solvent aromaticity and aromatics/saturates ratio. The results showed that the different kerosene compositions affected bulk viscosity and asphaltene flocculation, but had a lesser effect on oil/brine interfacial tension due to the high asphaltene content in the diluted oil. The elastic modulus decreased at higher dilutions with Ke S , while it remained consistent for Ke SA mixtures, which supported the differences obtained in emulsion stability, at solvent concentrations within the optimal aromaticity ratio reported for simple solvent mixtures. Interfacial segregation of the aromatics in Ke SA was also observed, which has not been reported in previous studies using complex solvents. These findings suggest that the trends reported with model oils, such as heptol with added asphaltenes, can also be applied to more realistic complex oil mixtures with higher asphaltene concentrations. Nevertheless, it was suggested that maintaining the aromatic content may not be enough to prevent asphaltene flocculation upon dilution, due to the concurrent increase in saturates.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".