Water Separation Performance in Bitumen Recovery from Athabasca Oil Sands: Implementation of Separation Efficiency Index
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The oil (diluted bitumen)–water separation efficiency at steam-assisted gravity drainage (SAGD) process conditions has been evaluated in a laboratory environment by using a custom-built batch gravity setup, using SAGD field fluids and commercial gas condensate as a diluent. The key parameters and conditions investigated are solvent amount, shear conditions, water-to-oil ratio, and the presence and wettability of fine solids. The results demonstrate the complexity of the oil–water separation process, affected by the dependence of the investigated parameters from one another. A new quantification approach is introduced to facilitate the oil–water separation efficiency evaluation, based on the proposed descriptor, referred to as a separation efficiency index (SEI). Defined as the average of the residual water-in-oil and oil-in-water indices, SEI ranges from 0 to 1, where 1 represents a “perfect” (complete) separation and 0 corresponds to a complete emulsification. The SEI allows one to describe the separation efficiency throughout the entire separation vessel volume, using discrete vertical water distribution profiles, and represents the separation efficiency with a single number, regardless of the experimental approach taken. The findings show that in the range of solvent concentrations of 30 vol % or lower, the mixing speed affects the separation performance and becomes predominant at the relatively low solvent concentrations of 10 and 20 vol %. The amount of solvent added becomes predominant in the oil–water separation process and overcomes all other effects in the highest solvent addition (40 and 50 vol %) range. The presence of water-wet solids improves the separation performance, while the presence of oil-wet solids impedes the oil–water separation. The results presented in this study, in particular the proposed SEI, are important for improving the oil–water separation efficiency and can be used to develop operational envelopes and new solvent injection strategies, in terms of location, amount, and stages, further improving the quality of the oil product obtained in SAGD.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".