Effects of the Deposition of Various Fines during Hydrotreating of a Bitumen Derived Gas Oil
Bibliographic record
Abstract
The processing and upgrading of the Canadian Athabasca Oil Sands is necessary to meet the demands of a growing global economy in a world of diminishing reserves. As such, the reduction in operating costs is imperative to further increase the amount of economically feasible reserves. Hydrotreating is a secondary upgrading method which, at elevated temperatures and pressures in the presence of hydrogen and a catalyst, removes contaminants from the oil stream. This both improves the quality of the produced oil by increasing the H/C ratio and allows the contaminants to be processed at the upgrading facility rather than be vented as exhaust. The purpose of this research was to compare the different types of fine particles that enter an industrial hydrotreating unit within a controlled setting. By comparing the catalyst activity and pressure buildup between mineral fines (namely kaolinite, montmorillonite, and pyrite), produced solids (petroleum coke), and corrosion products (iron (III) oxide), it was hoped that any discovered differences could be exploited through optimization of reactor conditions to lessen the quantity and/or impact of their fouling. This was performed using a laboratory-scale continuous-flow packed bed reactor, which is similar to the equipment used industrially. By comparing the pressure profiles during accelerated fines deposition of the different types of fines, it was found that mineral fines would create the earliest pressure buildup, taking 7-10 days and having a maximum pressure growth of 2885 kPa. The expected mechanism for these fines is that the surrounding asphaltene layers would desorb under hydrotreating conditions, leaving behind the minerals that were not oil-wetting, and couldn’t be carried by the passing oil stream. As more of these minerals were left behind, flow channels were blocked, and a filter cake formed at the inlet of the reactor. The second category of fines to result in pressure buildup was petroleum coke, reaching a 1193 kPa pressure drop. The mechanism driving this is that, as the petroleum coke solids break apart, any heavy metals that were contained within are left behind on the packing. This leads to the formation of a filter cake overtop of the catalyst bed. The category that took the longest for pressure to appear was corrosion products, where it was found that Fe_2 O_3 was converting to FeS under hydrotreating conditions. This formed FeS was then fouling the reactor system. This took over 40 days to be observed, with a final reactor differential pressure of 336 kPa. In analyzing the conversion of nitrogen and sulphur within the oil stream for each experiment, it was found that catalyst deactivation due to fouling was minimal, with the main impact to hydrotreater performance being due to the pressure buildup. The one exception to this was for the iron (III) oxide experiment, where the formed FeS improved catalyst activity. However, a significant amount of iron deposition was required to achieve the same benefits as the cobalt or nickel promotors that are typically impregnated onto the catalysts during preparation. Finally, through analysis of the textural and surface properties of the catalysts before and after the fouling had occurred, it was determined that fouling only occurred along the outer surface of the catalysts, and none of the active sites within the pores were reached. This is primarily due to the relative size between the foulants and the catalyst pores. Catalyst specific surface area was between 140-148 m2/g for all samples. Future research into this area should focus on optimizing reactor conditions to increase the period until pressure buildup occurs, as this is the first issue that a hydrotreater will experience due to the fouling of fine particles. Additionally, any research into possible methods for the removal of the asphaltene layer and filtration of the mineral fines prior to entering the hydrotreater could be considered as another avenue by which the reactor life cycle can be extended.
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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".