Novel Bitumen Froth Cleaning Device and Rag Layer Characterization
Bibliographic record
Abstract
A primary bitumen froth product, from a bitumen extraction process, contains approximately 30% water, 10% solids, and 60% bitumen. In bitumen froth treatment vessels, “rag layer” between the top organic phase and the bottom aqueous phase builds up from time to time. The presence of a thick layer of rag renders a two-phase separation into a three-phase separation, causing a significant reduction in oil/water/solids separation efficiency. A novel setup was built in our laboratory, which allows for a two-step water washing of naphtha-diluted bitumen froth (NDBF) and buildup of rag layer to be collected efficiently for further investigation of rag formation mechanisms. In the first step of bitumen froth cleaning, 1–5 mm diameter NDBF drops were introduced into an aqueous phase to allow the NDBF drops to rise to the top as the organic phase. In the second step, the top organic phase was then washed using the bottom aqueous phase by circulating the top organic phase back to the aqueous phase. The bitumen froth cleaning at 80 °C was tested for two different naphtha-to-bitumen mass ratios (N/B) of 0.7 and 7. In both cases, after the first washing, the water and solid contents were reduced by more than 91% and 87% of their original levels, respectively. In each of the two cases at N/B mass ratios of 0.7 and 7, the rag layer that formed in the device was collected and fractionated into five fractions, ranging from dry rags, chloroform solubles and insolubles, “asphaltenes”, and deasphalted organics. The emulsification potencies of these five fractions were tested using the simulated model system of heptane/toluene/water. The asphaltenes were characterized using elemental analysis, thermal gravimetric analysis (TGA), and Fourier transform infrared (FTIR) spectroscopy. The results showed that chloroform solubles and insolubles were in a mass ratio of about 1:1. Emulsion tests showed that the chloroform solubles and asphaltenes exhibited the highest emulsion stabilization potency. Elemental analysis and TGA showed that asphaltenes isolated from rags had twice more heteroatoms (N, S, and O) and contained more volatiles and residues than the asphaltenes obtained from normal bulk bitumen. FTIR characterization confirmed the results of elemental analysis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".