Synchrotron X-ray imaging study on the mechanism of solids transfer to bitumen froth during oil sands flotation 1: True flotation
Bibliographic record
Abstract
Unwanted mineral solids in bitumen froth can lead to increased solvent usage and higher hydrocarbon loss in downstream processing, negatively impacting the cost-effectiveness and sustainability of synthetic crude oil production. Enhancing the quality of bitumen froth with fewer solids is a goal for oil sands processors. This study presents an in-situ analysis of the particle size distribution and association of solids in bitumen froth, thereby uncovering solids transport mechanisms, such as true flotation. Oil sands flotation experiments were conducted with 30% pulp density, at 50 °C and pH 8.5. The collected bitumen froth was immediately characterized using synchrotron-based X-ray imaging by a monochromatic X-ray with photon energy of 60 keV provided by 05ID-2 beamline of the BioMedical Imaging and Therapy (BMIT) facility at the Canadian Light Source (CLS). This characterization method can finish a typical CT scan with 2000 projections in less than 3 min, and thus allows for in-situ imaging of freshly prepared bitumen froth without the need for special arrangements, such as freezing. 14, 234 unwanted solids carried over into bitumen froth were visualized, 98.9 wt% of them were sand particles, which is consistent with mineral liberation analysis (MLA) results. This study introduced an innovative image segmentation technique to quantify the transfer of particles into the bitumen froth via true flotation. Statistical analysis revealed that approximately 53 wt% of sand particles were collected due to true flotation. Furthermore, the median particle size (P50) for sand particles entering froth by true flotation was determined to be 67.6 μm, significantly larger than the 30.6 μm observed for particles transferring through entrainment or entrapment.
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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".