Challenges in Petroleum Characterization—A Review

Ivelina Shishkova, Dicho Stratiev (), Iliyan Venkov Kolev, Svetoslav Nenov, Dimitar Nedanovski, Krassimir Atanassov, Vitaly Ivanov and Simeon Ribagin
Additional contact information
Ivelina Shishkova: LUKOIL Neftohim Burgas, 8104 Burgas, Bulgaria
Dicho Stratiev: LUKOIL Neftohim Burgas, 8104 Burgas, Bulgaria
Iliyan Venkov Kolev: LUKOIL Neftohim Burgas, 8104 Burgas, Bulgaria
Svetoslav Nenov: Department of Mathematics, University of Chemical Technology and Metallurgy, Kliment Ohridski 8, 1756 Sofia, Bulgaria
Dimitar Nedanovski: Faculty of Mathematics and Informatics, “St. Kliment Ohridski” University, 15 Tsar Osvoboditel Blvd., 1504 Sofia, Bulgaria
Krassimir Atanassov: Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Academic GeorgiBonchev 105, 1113 Sofia, Bulgaria
Vitaly Ivanov: Department of Industrial Technologies and Management, University Prof. Dr. Assen Zlatarov, Professor Yakimov 1, 8010 Burgas, Bulgaria
Simeon Ribagin: Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Academic GeorgiBonchev 105, 1113 Sofia, Bulgaria

Energies, 2022, vol. 15, issue 20, 1-33

Abstract: 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 C 5 -, and C 7 -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.

Keywords: petroleum; crude oil; characterization; SARA; asphaltenes; TBP; modeling; ICrA (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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