Comparative Static and Dynamic Analyses of Solvents for Removal of Asphaltene and Wax Deposits above- and below-Surface at an Iranian Carbonate Oil Field
Bibliographic record
Abstract
During production from oil wells, the deposition of asphaltene and wax at surface facilities and porous media is one of the major operational challenges. The crude oil production rate is significantly reduced due to asphaltene deposition inside the reservoir. In addition, the deposition of these solids inside the surface facilities is costly to oil companies. In this study, the efficiency of different solvents in dissolving asphaltene and wax was investigated through static and dynamic tests. The analysis of solid deposits from the surface choke of one of the Iranian carbonate oil fields showed that they consisted of 41.3 wt % asphaltene, and the balance was predominantly wax. In addition, the asphaltenes obtained from the surface choke solid deposits had a more complex structure than that of asphaltenes extracted from the crude oil itself. The static tests showed that xylene, toluene, gasoline, kerosene, and gas condensate had the highest efficiencies in dissolving solid deposits; conversely, diesel had a negative impact on dissolving solid deposits. Static tests on pure asphaltene showed that, among the tested solvents, gas condensate and diesel had a negative effect on the solubility of asphaltene. The dynamic core flooding results showed that asphaltene deposition inside the cores reduced the permeability by 79-91%. Among the tested solvents, xylene, gasoline, and kerosene resulted in the highest efficacy in restoring the damaged permeability, and higher efficiency was obtained with an equivalent solvent injection rate of 1 bbl/min versus 3 bbl/min.
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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".