On the effect of temperature on precipitation and aggregation of asphaltenes in light live oils
Bibliographic record
Abstract
Abstract Asphaltene precipitation and deposition is a serious issue in all facets of petroleum production and processing. Despite the numerous experimental efforts concerning asphaltenes, the effect of temperature on asphaltene precipitation and aggregation in live oils remains an elusive and controversial subject in the available literature. In this work, a series of high pressure‐high temperature depressurization experiments were designed to assess the effect of temperature on asphaltene precipitation and aggregation in light live oils. Asphaltene related experiments were performed using a high pressure microscope and high pressure‐high temperature filtration setup on a light live oil with a low asphaltene content and a high potential of asphaltene formation. The results of the experiments were interpreted in terms of asphaltene onset pressure, size distribution and average diameter of the aggregates, fractal dimension of the asphaltene aggregates, and the amount of precipitated asphaltene. It was found that the depressurization process at higher temperatures resulted in higher asphaltene onset pressure or earlier formation of asphaltenes. Visualization experiments showed that asphaltene aggregates in light live oil are pressure‐temperature fractal structures. The depressurization process at lower temperatures led to the formation of highly porous and loose aggregate structures with relatively low fractal dimensions. As the temperature of the depressurization process decreases, the mechanism of asphaltene aggregation changes gradually from reaction‐limited aggregation to diffusion‐limited aggregation. This research reveals that temperature has crucial effects on the asphaltene aggregation process in light live oils at elevated pressures, which is of great importance for asphaltene handling and separation.
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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 | 0.001 |
| 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) | 0.000 | 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".