Characterization of Bitumen Properties Using Microscopy and Near Infrared Spectroscopy: Processability of Oxidized or Degraded Ores
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Bibliographic record
Abstract
Abstract Oxidized or degraded oil sands can exhibit poor processability, which is often not correlated with the fines or clay contents in the ore. Chemical markers (such as low pH and high soluble iron and calcium) for oil sands oxidation are sometimes not present even though significant changes in bitumen properties may have occurred. In these cases, changes in bitumen chemistry have been successfully quantified using microscopic techniques developed at CANMET. More recently, an on-line tool using near infrared (NIR) spectroscopy, which correlates with the CANMET microscopic method, has been developed with Suncor Energy Inc. An on-line technique based on NIR that can quantify the amount of degraded ore coming to the extraction plant from Suncor Energy Inc.'s Steepbank mine will be useful in effectively controlling additions of process aids for treating oxidized or degraded ores. This paper discusses the processability of oxidized or degraded ores along with a microscopic method for identifying oxidized ore and its correlation with the NIR spectroscopic technique. Introduction Oil sands processing efficiency is dependent upon many factors, including the quality of the ore. The operating companies have developed correlations between extraction recovery and bitumen and fines content in the ore. These correlations generally fit observed processability, but often ores are encountered with recoveries that fall well outside these simple relationships. These are variously known as bad ores, problem ores, type X ores, or ores with a high misery factor (the misery due to the loss in recovery or to the "difficult to settle" tailings). Detailed characterization can reveal the reasons for such poor processing behaviour and they can sometimes be traced to unusual water chemistries or unusual clay properties. Often, however, changes in bitumen chemistry can be the source of the problem, and this is the focus of the present discussion. Bitumen oxidation and its negative impact on processability has been extensively studied, mostly on stockpiled or stored samples(1–7). Experience at Suncor Energy Inc.'s Steepbank mine has shown that bitumen changes that may have occurred in geological time frames can also be important in determining processability(8–10). Steepbank Sampling During the commissioning of the Suncor Energy Inc. Steepbank mine, areas of ore were identified that created processing difficulties, in particular high froth densities. The high froth densities resulted in problems in downstream facilities where high solids content in the froth resulted in overloading of the froth treatment centrifuges. These effects were quickly identified with certain areas of the mine and a sampling program was undertaken to identify the causes of the poor processability. The ores linked to the poor processability were generally high-grade ores containing in excess of 12% w/w bitumen (occasionally >14% w/w) with low fines content, that do not fit the normal profile for poorly processing ores. Cryogenic sampling of the froths in the commercialscale separation cell was carried out in order to help identify the cause of the high froth densities. Macroscopic observation of the froths from the problem ores included very large bubble sizes and sometimes a distinct reddish froth colour(9,12).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it