What Is Behind the High Values of Hot Filtration Test of the Ebullated Bed Residue H-Oil Hydrocracker Residual Oils?
Bibliographic record
Abstract
This work summarizes the results of multiple experiments performed in the LUKOIL Neftohim Burgas Research Laboratory related to the issue of high values of hot filtration test (HFT) of the residue H-Oil hydrocracking residual oil products. After the start-up of the new residue H-Oil hydrocracker in the LUKOIL Neftohim Burgas refinery during the second half of 2015 the values of the HFT of the vacuum tower bottom product varied between 0.01 and 8.7%. It was found that the vacuum residual oil feed source has a profound effect on the processes of sedimentation in the H-Oil hydrocracker. The processing of vacuum residual oils from Arab medium, Arab heavy, and Basrah light crudes reduced the sedimentation and allowed achievement of a higher conversion. The H/C ratios of asphaltenes from all studied feeds decreased after hydrocracking. However, the decrease of the H/C ratio was the least pronounced with the Basra light asphaltenes, while the H/C ratios of asphaltenes from the vacuum residual oils originating from the crudes Urals and El Bouri became much lower. The maltene fraction H/C ratio could become lower, the same, or higher after hydrocracking depending on the feed source, catalyst metal (vanadium) loading, or the hydrocracking unit (commercial, pilot plant, or laboratory unit). It was found that after addition of high aromatic fluid catalytic cracking gas oils the H-Oil residue HFT dropped and the dependence of the residue HFT on the concentration of FCC gas oils in the blend could be approximated by a third order polynomial. Correlations were developed to predict the H-Oil based residual fuel oil HFT from information on the base H-Oil residue HFT and the amount of added fluid catalytic cracking (FCC) gas oil. The treatment of the H-Oil residual oils with commercial HFT reducers may decrease the residual oil HFT. However, the efficiency in HFT reduction turned out to depend on the nature of the H-Oil residue and on the concentration range of the HFT reducing additive. From all studied additives solely the dodecylbenzenesulfonic acid (DBSA) was capable of reducing the H-Oil residual oil below 0.1%. However, the treatment rate of the DBSA was an order higher than that of the commercial additives A, B, and C. DBSA was an order of magnitude more effective in the reduction of the total sediment existent, and the total sediment potential than the FCC HCO.
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".