A Novel Technique to Determine Concentration-Dependent Solvent Dispersion in Vapex
Bibliographic record
Abstract
Vapex (vapor extraction of heavy oil and bitumen) is a promising recovery technology because it consumes low energy, and is very environmentally-friendly. The dispersion of solvents into heavy oil and bitumen is a crucial transport property governing Vapex. The accurate determination of solvent dispersion in Vapex is essential to effectively predict the amount and time scale of oil recovery as well to optimize the field operations. In this work, a novel technique is developed to experimentally determine the concentration-dependent dispersion coefficient of a solvent in Vapex process. The principles of variational calculus are utilized in conjunction with a mass transfer model of the experimental Vapex process. A computational algorithm is developed to optimally compute solvent dispersion as a function of its concentration in heavy oil. The developed technique is applied to Vapex utilizing propane as a solvent. The results show that dispersion of propane is a unimodal function of its concentration in bitumen.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".