Use of Biodiesel as an Additive in Thermal Recovery of Heavy Oil and Bitumen
Bibliographic record
Abstract
Summary Bitumen extraction in oil sands-ore water slurry systems was studied by using lipids and lipid derivatives such as biodiesel (BD) as surfactant additive to promote bitumen recovery efficiency. Performance of BDs (i.e., canola and tall oil, a by-product of pulp mills using the bleached Kraft process) fatty acids methyl ester and food-grade fatty acids monoglycerides were evaluated as surfactant additives. Experimental findings suggest that BDs such as fatty acids methyl esters could also be used as surfactant additives to increase the efficiency of bitumen recovery in thermal in-situ processes such as steam assisted gravity drainage (SAGD) and cyclic steam stimulation (CSS) processes. The required dosage for the surfactant additive is about 0.1% of bitumen by mass. Also, interfacial tension measurements between bitumen and process water (YB,W) and BD and process water (YBD,W) support the surfactant behavior of BD.
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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) | 0.001 | 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".