Browsing by Author "Bureva V."
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Item Experience in Processing Alternative Crude Oils to Replace Design Oil in the Refinery(2024-06-01) Stratiev D.; Shiskova I.; Toteva V.; Georgiev G.; Dinkov R.; Kolev I.; Petrov I.; Argirov G.; Bureva V.; Ribagin S.; Atanassov K.; Nenov S.; Sotirov S.; Nikolova R.; Veli A.A comprehensive investigation of a highly complex petroleum refinery (Nelson complexity index of 10.7) during the processing of 11 crude oils and an imported atmospheric residue replacing the design Urals crude oil was performed. Various laboratory oil tests were carried out to characterize both crude oils, and their fractions. The results of oil laboratory assays along with intercriteria and regression analyses were employed to find quantitative relations between crude oil mixture quality and refining unit performance. It was found that the acidity of petroleum cannot be judged by its total acid number, and acid crudes with lower than 0.5 mg KOH/g and low sulphur content required repeated caustic treatment enhancement and provoked increased corrosion rate and sodium contamination of the hydrocracking catalyst. Increased fouling in the H-Oil hydrocracker was observed during the transfer of design Urals crude oil to other petroleum crudes. The vacuum residues with higher sulphur, lower nitrogen contents, and a lower colloidal instability index provide a higher conversion rate and lower fouling rate in the H-Oil unit. The regression equations developed in this work allow quantitative assessment of the performance of crucial refining units like the H-Oil, fluid catalytic cracker, naphtha reformer, and gas oil hydrotreatment based on laboratory oil test results.Item Feed Variability Effect on Performance of a Commercial Residue Hydrocracker(2025-11-01) Stratiev D.; Dinkov R.; Shiskova I.; Nedelchev A.; Kolev I.; Argirov G.; Sotirov S.; Sotirova E.; Bureva V.; Atanassov K.; Yordanov D.; Nenov S.; Stratiev D.Feed quality has been found to be related to both reactivity and sediment formation propensity in the residue hydrocracking process defining the conversion level. In this research, unlike other investigations, which examine hydrocrackability of individual vacuum residues, 529 mixtures of 33 vacuum residues were investigated for their hydrocrackability in a commercial H-Oil ebullated bed reactor unit. Intercriteria and regression analyses, together with singular value decomposition (SVD) and deep learning neural network techniques were employed to analyze data and model the vacuum residue conversion in the H-Oil unit. It was found that SVD model provided the best fit of H-Oil conversion training data (standard error of 0.95 wt.%). However, due to overfitting, the SVD model failed to predict H-Oil conversion on unseen data (standard error of 5.1 wt.%). The deep learning neural network exhibited standard error for all data (training, validation and testing) of 1.99 wt.%, while for the test data it was 2.35 wt.%. The linear regression model showed a standard error of 3.9 wt.% for the training data and 7.5 wt.% for the test data. Eleven properties of the vacuum residue (density, microcarbon residue, sulfur, nitrogen, saturate, aromatic, resin, C5-asphaltene, C7-asphaltene, Na, and Ni+V content) seem to be sufficiently informative for the purposes of modeling and predicting H-Oil conversion, thus enabling the assessment of the suitability of a given vacuum residue to be used as a feedstock for the H-Oil process. The best predicting model was found to be the deep learning neural network, which can be used for the purpose of the crude selection process.Item Industrial Investigation of the Combined Action of Vacuum Residue Hydrocracking and Vacuum Gas Oil Catalytic Cracking While Processing Different Feeds and Operating under Distinct Conditions(2023-11-01) Stratiev D.; Toteva V.; Shishkova I.; Nenov S.; Pilev D.; Atanassov K.; Bureva V.; Vasilev S.; Stratiev D.D.Ebullated bed vacuum residue hydrocracking and fluid catalytic cracking (FCC) are among the most profitable processes in modern refining. Their optimal performance is vital for petroleum refining profitability. That is why a better understanding of their combined action and the interrelations between these two heavy oil conversion processes in a real-world refinery could provide valuable information for further performance optimization. Nine distinct petroleum crudes belonging to the extra light, light, and medium petroleum crude types were processed in the LUKOIL Neftohim Burgas refinery to study the combined performance of two processes: FCC of vacuum gas oil and ebullated bed vacuum residue H-Oil hydrocracking. The operating conditions along with the characterization data of the feeds and products of both processes were evaluated through the employment of intercriteria analysis to define the variables with statistically significant relationships. Maple 2023 Academic Edition mathematics software was used to develop models to predict the vacuum residue conversion level under different operating conditions. The plug flow reactor model with an activation energy of 215 kJ/mol and a reaction order of 1.59 was found to provide the highest accuracy of vacuum residue conversion, with an average absolute deviation of 2.2%. H-Oil yields were found to correlate with the vacuum residue conversion level and the content of FCC slurry oil (SLO), the recycling of partially blended fuel oil, a material boiling point below 360 °C, and the vacuum gas oil (VGO) in the H-Oil feed. FCC conversion was found to depend on the H-Oil VGO content in the FCC feed and the content of FCC SLO in the H-Oil feed.Item Roles of Catalysts and Feedstock in Optimizing the Performance of Heavy Fraction Conversion Processes: Fluid Catalytic Cracking and Ebullated Bed Vacuum Residue Hydrocracking(2024-09-01) Stratiev D.; Shishkova I.; Argirov G.; Dinkov R.; Ivanov M.; Sotirov S.; Sotirova E.; Bureva V.; Nenov S.; Atanassov K.; Stratiev D.; Vasilev S.Petroleum refining has been, is still, and is expected to remain in the next decades the main source of energy required to drive transport for mankind. The demand for automotive and aviation fuels has urged refiners to search for ways to extract more light oil products per barrel of crude oil. The heavy oil conversion processes of ebullated bed vacuum residue hydrocracking (EBVRHC) and fluid catalytic cracking (FCC) can assist refiners in their aim to produce more transportation fuels and feeds for petrochemistry from a ton of petroleum. However, a good understanding of the roles of feed quality and catalyst characteristics is needed to optimize the performance of both heavy oil conversion processes. Three knowledge discovery database techniques—intercriteria and regression analyses, and artificial neural networks—were used to evaluate the performance of commercial FCC and EBVRHC in processing 19 different heavy oils. Seven diverse FCC catalysts were assessed using a cascade and parallel fresh catalyst addition system in an EBVRHC unit. It was found that the vacuum residue conversion in the EBVRHC depended on feed reactivity, which, calculated on the basis of pilot plant tests, varied by 16.4%; the content of vacuum residue (VR) in the mixed EBVRHC unit feed (each 10% fluctuation in VR content leads to an alteration in VR conversion of 1.6%); the reaction temperature (a 1 °C deviation in reaction temperature is associated with a 0.8% shift in VR conversion); and the liquid hourly space velocity (0.01 h-1 change of LHSV leads to 0.85% conversion alteration). The vacuum gas oil conversion in the FCC unit was determined to correlate with feed crackability, which, calculated on the basis of pilot plant tests, varied by 8.2%, and the catalyst ΔCoke (each 0.03% ΔCoke increase reduces FCC conversion by 1%), which was unveiled to depend on FCC feed density and equilibrium FCC micro-activity. The developed correlations can be used to optimize the performance of FCC and EBVRHC units by selecting the appropriate feed slate and catalyst.