Thermophysical properties of dimethyl ether/Athabasca bitumen system
Bibliographic record
Abstract
Solvent‐aided thermal recovery processes have recently gained practical and research interests among other thermal recovery methods due to their reduced environmental footprint and superior energy efficiency. One of the main challenges in design of solvent‐based methods is selection of an appropriate solvent that maximizes the bitumen and solvent recoveries. This study attempts to introduce dimethyl ether (DME) as a non‐conventional solvent for heavy oil and bitumen recovery. To investigate the performance of the proposed solvent, thermophysical properties of DME/bitumen are studied. Vapour‐liquid equilibrium measurements including solubility, density, and viscosity are performed at three temperatures (100, 125, and 150 °C) and pressures up to 6 MPa. The results were compared with propane/bitumen and butane/bitumen systems. All the measured properties fall between propane and butane systems. The solubility and density data were fairly represented using PR‐EoS with AARDs of 10.3 and 1.43 %, respectively, and viscosity data were correlated applying the Pederson corresponding state model with an AARD of 10.7 %. The results suggest that DME is a suitable substitute for solvents such as propane and butane in solvent‐aided thermal recovery of bitumen from oil sands.
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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) | 0.003 | 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".