Phase Behaviour Study of Butane / Athabasca Bitumen Mixtures Applicable for Thermal and Hybrid Solvent Recovery Processes
Bibliographic record
Abstract
Abstract World production of heavy and extra-heavy oils has increased as the production of conventional crudes decline. However, the conventional oil recovery methods cannot effectively recover the heavy oil due to their high viscosities. The steam and/or solvent-based recovery processes can be considered as an efficient method for recovery of these resources. The performance of these techniques depends on the amount of solvent dissolved in the crude and the variation of oil viscosity with temperature. Thus, full understanding of the quantitative effects of the solvent on heavy oil viscosity and phase behaviours are crucial for feasibility studies, design and prediction of field-scale processes. Phase behaviour study of bitumen diluted with heavy hydrocarbon solvents such as propane and butane have 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), would provide promising oil production rates. The aim of this research, thus, is the development of an understanding of the phase behaviour of butane / Athabasca bitumen systems. It deals with both vapor-liquid and liquid-liquid phase equilibriums over wide range of temperatures (up to 200°C) approaching the conditions of in situ steam processes and pressures up to 8 MPa. Experimental results indicated that the vapor-liquid and liquid-liquid equilibrium formed over the studied temperature and pressure ranges. In the case of vapor-liquid equilibrium, the dissolved butane in bitumen leads to a significant oil viscosity reduction. The effect was higher at lower temperature and higher pressure. For liquid-liquid equilibrium, butane extracted light components from oil and formed a butane-enriched phase while the heavier constitutes such as asphaltene separated as second heavy liquid phase. Finally, the measured solubility and density data were adequately modeled with Peng-Robinson equation of state.
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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) | 0.002 | 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".