Asphaltene Aggregation in Crude Oils during Supercritical Gas Injection
Bibliographic record
Abstract
This paper presents the aggregation of asphaltenic materials in three dead crude oils, including two heavy samples from Hokkaido (Japan) and an extra heavy sample from Canada. In this study, a modified ASTM D3279 method and PVT test were used to estimate the amount of precipitated asphaltene and the experimental bubble-point pressures of the samples, respectively. Upon which, a crude oil characterization was performed following pseudocomponent approach with the use of molecular weight and specific gravity of single carbon number from oil assay data as distribution variables. A simplified thermodynamic model, derived from the solubility model, was used to correlate the maximum asphaltene soluble with the aggregated amount. This study has highlighted that oil precipitation, during its titration, occurs as a function of both the molecular weight of the titrant and the carbon-to-hydrogen ratio in the asphaltene phase. Furthermore, the kinetics and the stability of intermolecular forces, developed during the miscibility process, are believed to alter oil polarity and gas solubility. More specifically, pressurization of the system [oil-supercritical gas] decreases the solubility parameters of the asphaltene fraction and increases the solvating strength of gas. Both effects were found to occur concurrently. This study has also demonstrated that asphaltenes are less soluble in impure gases compared to the pure one. At/near the bubble-point pressure, the supercritical gas, in contact with the oil, develops a potential as either a flocculant or coagulant. The increase in pseudo equilibrium temperature attained after gas injection was found also to alter asphaltene aggregation.
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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".