Solubility of <i>n</i>-Butane in Athabasca Bitumen and Saturated Densities and Viscosities at Temperatures Up to 200°C
Bibliographic record
Abstract
Summary The steam- and/or solvent-based recovery processes are efficient methods for recovery of heavy and extraheavy oils. The performance of these techniques depends on the amount of solvent dissolved in the oil and the variation of oil viscosity with temperature. Thus, full understanding of the quantitative effects of the solvent on heavy-oil viscosity and phase behavior is crucial for feasibility studies, design, and prediction of field-scale processes. Phase-behavior study of bitumen diluted with heavy hydrocarbon solvents, such as butane and pentane, has gained less attention in recent years. These solvents, as good candidates for recently developed recovery methods such as expanding solvent steam-assisted gravity drainage (ES-SAGD), could provide promising oil-production rates. Thus, the aim of this research is the development of an understanding of the phase behavior of n-butane/Athabasca-bitumen mixtures. It includes both experimental and modeling studies of solubilities and saturated liquid densities and viscosities over wide ranges of temperatures (up to 200 °C) and pressures (up to 8 MPa). Experimental results indicate that the dissolved n-butane in bitumen leads to a significant oil-viscosity reduction, and the effect is more pronounced at lower temperatures and/or higher pressures. The modeling results show that the measured solubilities are adequately represented by the Peng-Robinson equation of state (EOS) with an average absolute relative deviation (AARD) of 9.7%. The saturated liquid densities are also correlated with both the EOS and the effective liquid-density approach with 0.86 and 0.55% AARDs, respectively. The viscosity data are reasonably matched with Pedersen corresponding state.
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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".