Browsing by Author "Ivanov V."
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Item Challenges in Petroleum Characterization—A Review(2022-10-01) Shishkova I.; Stratiev D.; Kolev I.V.; Nenov S.; Nedanovski D.; Atanassov K.; Ivanov V.; Ribagin S.252 literature sources and about 5000 crude oil assays were reviewed in this work. The review has shown that the petroleum characterization can be classified in three categories: crude oil assay; SARA characterization; and molecular characterization. It was found that the range of petroleum property variation is so wide that the same crude oil property cannot be measured by the use of a single standard method. To the best of our knowledge for the first time the application of the additive rule to predict crude oil asphaltene content from that of the vacuum residue multiplied by the vacuum residue TBP yield was examined. It was also discovered that a strong linear relation between the contents of C5-, and C7-asphaltenes in crude oil and derived thereof vacuum residue fraction exists. The six parameter Weibull extreme function showed to best fit the TBP data of all crude oil types, allowing construction of a correct TBP curve and detection of measurement errors. A new SARA reconstitution approach is proposed to overcome the poor SARA analysis mass balance when crude oils with lower density are analyzed. The use of a chemometric approach with combination of spectroscopic data was found very helpful in extracting information about the composition of complex petroleum matrices consisting of a large number of components.Item EPR as a tool for the evaluation of novel lyophilized blood products as absorbents for chemical gas masks(2011-04-01) Ivanov V.; Arora R.; Hadjiiliev V.; Stoyanova R.; Ruseva R.; Nikolov R.; Kumar R.; Sharma R.Item Intercriteria Analysis to Diagnose the Reasons for Increased Fouling in a Commercial Ebullated Bed Vacuum Residue Hydrocracker(2022-01-01) Stratiev D.; Shishkova I.; Dinkov R.; Kolev I.; Argirov G.; Ivanov V.; Ribagin S.; Atanassova V.; Atanassov K.; Stratiev D.; Nenov S.; Pilev D.; Yordanov D.The intercriteria analysis developed on the base of intuitionistic fuzziness and index matrices was applied to evaluate processing data of the LUKOIL Neftohim Burgas H-Oil ebullated bed vacuum residue hydrocracker with the aim of revealing the reasons for increased fouling registered during the 3rd cycle of the H-Oil hydrocracker. It was found that when the ratio of the δT of the 1st reactor to the δT of the 2nd reactor gets lower than 2.0, an excessive H-Oil equipment fouling occurs. The fouling was also found to be favored by processing of lower Conradson carbon content vacuum residual oils and increased throughput and depressed by increasing the dosage of the HCAT nanodispersed catalyst. The fouling in the atmospheric tower bottom section is facilitated by a lower aromatic content in the atmospheric tower bottom product. The addition of FCC slurry oil not only increases aromatic content but also dissolves some of the asphaltenes in the atmospheric residual hydrocracked oil and decreases its colloidal instability index. The fouling in the vacuum tower bottom section is facilitated by a higher saturate content in the VTB. Surprisingly, it was found that the asphaltene content in the VTB depresses the fouling rate. No relation was found of the sediment content in the hydrocracked residual oils measured by hot filtration tests and by the centrifuge method to the equipment fouling of the H-Oil hydrocracker.Item Study of Bulk Properties Relation to SARA Composition Data of Various Vacuum Residues Employing Intercriteria Analysis(2022-12-01) Stratiev D.; Shishkova I.; Palichev G.N.; Atanassov K.; Ribagin S.; Nenov S.; Nedanovski D.; Ivanov V.Twenty-two straight run vacuum residues extracted from extra light, light, medium, heavy, and extra heavy crude oils and nine different hydrocracked vacuum residues were characterized for their bulk properties and SARA composition using four and eight fractions (SAR-ADTM) methods. Intercriteria analysis was employed to determine the statistically meaningful relations between the SARA composition data and the bulk properties. The determined strong relations were modeled using the computer algebra system Maple and NLPSolve with the Modified Newton Iterative Method. It was found that the SAR-ADTM saturates, and the sum of the contents of saturates and ARO-1 can be predicted from vacuum residue density, while the SAR-ADTM asphaltene fraction content, and the sum of asphaltenes, and resins contents correlate with the softening point of the straight run vacuum residues. The softening point of hydrocracked vacuum residues was found to strongly negatively correlates with SAR-ADTM Aro-1 fraction, and strongly positively correlates with SAR-ADTM Aro-3 fraction. While in the straight run vacuum residues, the softening point is controlled by the content of SAR-ADTM asphaltene fraction in the H-Oil hydrocracked vacuum residues, the softening point is controlled by the content of SAR-ADTM Aro-3 fraction content. During high severity H-Oil operation, resulting in higher conversion, hydrocracked vacuum residue with higher SAR-ADTM Aro-3 fraction content is obtained, which makes it harder and more brittle.