Viscosity Measurement and Modeling for Mixtures of Athabasca Bitumen/<i>n</i>-Pentane at Temperatures Up to 200°C
Bibliographic record
Abstract
Summary The phase-behavior and thermophysical properties of bitumen/solvent systems are of crucial importance for heavy-oil and bitumen in-situ recovery methods. The viscosity reduction as a result of solvent dissolution and/or steam heating is the main recovery mechanism in the solvent-based bitumen-recovery processes. In this paper, the viscosity of bitumen, pentane, and their mixtures at different pentane weight fractions (0.05, 0.1, 0.2, 0.3, 0.4, and 0.5) are accurately measured. The measurements are conducted under conditions applicable for both in-situ recovery methods and the pipeline transportation of heavy oil. The experiments are taken with Athabasca bitumen at temperatures varying from ambient up to 200°C and at pressures up to 10 MPa. The data for the mixtures are evaluated with predictive schemes as well as with correlation models representing certain mixing rules proposed in the literature. The influences of pressure, temperature, and solvent weight fraction on the viscosity of mixtures are considered in the models and evaluated from the experimental data. The results indicated that the power-law model and the Cragoe model (Cragoe 1933) represent the data better than other models that use a volume-fraction basis.
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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 | 0.000 |
| 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 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".