Complex Mass Transfer Phenomena in Bitumen Solvent Systems
Bibliographic record
Abstract
Abstract The overall objective of this study was to perform a series of diffusion experiments between liquid hydrocarbons (e.g., propane, pentane, and toluene) and bitumen or heavy oil to observe and analyze mass transfer in the systems. Some difficulties, such as the complex behavior of the phases, the high viscosity, and the opacity of hydrocarbons, generate the need for different techniques to measure mass transfer coefficients in heavy crude oils. In this work, X-ray tomography was used for such measurements. The measurements are carried out in environments where the sedimentation of solids is encouraged. To achieve this, a novel setup was designed and assembled to measure the mass transfer in these systems based on the density profiles established over time in aluminum containers that contain fluids. The containers were regularly scanned to track the behavior of the density profiles over time. The data was collected and analyzed, obtaining interesting results, which will be important as a starting point for future research related to systems that integrate interactions between solvents and oils in the recovery processes. Due to the novel results obtained in the original test, 7 sets of experiments were carried out, all with unique characteristics, trying to analyze its results in detail. One of the objectives is to analyze if the mass transfer is uniform and constant during long periods. This work shows results that were never published in the previous literature, such as partial miscibility when mixing n-propane and bitumen, oil swelling, oil shrinking, asphaltene precipitation and sedimentation, total miscibility, and the effect of adding pure asphaltenes and calcium carbonate to the mixture, among others. In addition, the impacts on the effectiveness of the proposed processes for the production and refining of these solvents are discussed.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".