Asphaltene Deposition during Bitumen Extraction with Natural Gas Condensate and Naphtha
Bibliographic record
Abstract
Solvent bitumen extraction processes are alternatives to thermal processes with potential for improved economic and environmental performance. However, solvent interaction with bitumen commonly results in in situ asphaltene precipitation and deposition, which can hinder flow and reduce the process efficiency. Successful implementation requires one to select a solvent that improves recovery with minimal flow assurance problems. The majority of candidate industrial solvents are in the form of mixtures containing a wide range of hydrocarbon fractions, further complicating the selection process. In this study, we quantify the pore-scale asphaltene deposition using two commonly available solvent mixtures, natural gas condensate and naphtha, using a microfluidic platform. The results are also compared with those of two typical pure solvents, n -pentane and n -heptane, with all cases evaluated with both 50 and 100 μm pore-throat spacing. The condensate produced more asphaltenes and pore-space damage than the naphtha and exhibited deposition dynamics similar to that of pentane and heptane. This similarity is due to the presence of a large amount of light hydrocarbon fractions in condensate (∼85 wt % of C 5 s–C 7 s) dictating the overall deposition dynamics. Naphtha, which contains heavier fractions (∼70 wt % of C 8 s–C 11 s) and aromatic/naphthenic components, generated less asphaltenes and exhibited a slower deposition rate, resulting in less pore damage and overall better performance.
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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 | 0.001 | 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".