Browsing by Author "Nedanovski D."
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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 Different nonlinear regression techniques and sensitivity analysis as tools to optimize oil viscosity modeling(2021-10-01) Stratiev D.; Nenov S.; Nedanovski D.; Shishkova I.; Dinkov R.; Stratiev D.D.; Stratiev D.D.; Sotirov S.; Sotirova E.; Atanassova V.; Atanassov K.; Yordanov D.; Angelova N.A.; Ribagin S.; Todorova-Yankova L.Four nonlinear regression techniques were explored to model gas oil viscosity on the base of Walther’s empirical equation. With the initial database of 41 primary and secondary vacuum gas oils, four models were developed with a comparable accuracy of viscosity calculation. The Akaike information criterion and Bayesian information criterion selected the least square relative errors (LSRE) model as the best one. The sensitivity analysis with respect to the given data also revealed that the LSRE model is the most stable one with the lowest values of standard deviations of derivatives. Verification of the gas oil viscosity prediction ability was carried out with another set of 43 gas oils showing remarkably better accuracy with the LSRE model. The LSRE was also found to predict better viscosity for the 43 test gas oils relative to the Aboul Seoud and Moharam model and the Kotzakoulakis and George.Item Empirical Modeling of Viscosities and Softening Points of Straight-Run Vacuum Residues from Different Origins and of Hydrocracked Unconverted Vacuum Residues Obtained in Different Conversions(2022-03-01) Stratiev D.; Nenov S.; Nedanovski D.; Shishkova I.; Dinkov R.; Stratiev D.D.; Stratiev D.D.; Sotirov S.; Sotirova E.; Atanassova V.; Ribagin S.; Atanassov K.; Yordanov D.; Angelova N.A.; Todorova-Yankova L.The use of hydrocracked and straight-run vacuum residues in the production of road pavement bitumen requires a good understanding of how the viscosity and softening point can be modeled and controlled. Scientific reports on modeling of these rheological properties for hydroc-racked and straight-run vacuum residues are scarce. For that reason, 30 straight-run vacuum residues and 33 hydrocracked vacuum residues obtained in a conversion range of 55–93% were investigated, and the characterization data were employed for modeling purposes. An intercriteria analysis was applied to investigate the statistically meaningful relations between the studied vacuum residue properties. It revealed that the straight-run and hydrocracked vacuum residues were completely different, and therefore their viscosity and softening point should be separately modeled. Through the use of nonlinear regression by applying CAS Maple and NLPSolve with the modified Newton iterative method and the vacuum residue bulk properties the viscosity and softening point were modeled. It was found that the straight-run vacuum residue viscosity was best modeled from the molecular weight and specific gravity, whereas the softening point was found to be best modeled from the molecular weight and C7-asphaltene content. The hydrocracked vacuum residue viscosity and softening point were modeled from a single property: the Conradson carbon content. The vacuum residue viscosity models developed in this work were found to allow prediction of the asphaltene content from the molecular weight and specific gravity with an average absolute relative error of 20.9%, which was lower of that of the model of Samie and Mortaheb (Fuel. 2021, 305, 121609)—32.6%.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.