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Possibility of ultrahigh resolution mass-spectrometry application to analyze petroleum hetero-atomic compounds
Chemical sciences

Authors: Anna V. STAVITSKAYA graduated from Gubkin Russian State University of Oil and Gas in 2011. She is postgraduate student at Gubkin Russian State University of Oil and Gas, Department of Organic Chemistry and Petroleum Chemistry. She has autho- red 3 scientific publications in the field of chemistry of oil disperse systems and methods of research. E-mail: stavitsko@mail.ru
Ravilya Z. SAFIEVA graduated from Lomonosov Moscow State University in 1978. She is Doctor of Science (Technology) and chief researcher of the Department of Organic Chemistry and Petroleum Chemistry of Gubkin Russian State University of Oil and Gas. She has authored 125 scientific publications in the field of physical chemistry of the oil disperse systems and methods of research. E-mail: safieva@mail.ru

Abstract: The paper describes the possibility of ultra-high resolution ion-cyclotron resonance mass spectrometry (FT–ICR–MS) application in conjunction with the «soft» ionization techniques for molecular level characterization of petroleum hetero-atomic compounds. Two petroleum samples were analyzed and 19 classes of hetero-atomic compounds with CcHhNnOoSs composition were discovered, including carboxylic acid, pyridine bases, pyrrole-type compounds, compounds with one and two sulfur atoms in the molecule, as well as hybrid compound (SO, NS, O2S2, ONS and others). Different ionization techniques such as electrospray (ESI) and atmospheric pressure photoionization (APPI) allow us to study the composition of petroleum high molecular compounds while the high sensitivity of the method enables to simultaneously identify thousands of compounds in minimum volume of petroleum (12 mkl). The uniqueness of the method is the ability to analyze the heavy part of petroleum (including resinasphaltene substances). The ultra-high resolution, sensitivity and accuracy of the method combined with simplicity of use make the method an excellent tool for petrochemical analysis

Index UDK: УДК 54.07

Keywords: ion cyclotron resonance mass spectrometry, petroleum hetero-atomic compounds, resolution, ionization techniques

1. Ivanova L.V., Koshelev V.N., Sokova N.A., Burov Е.А., Primerova О.V. Petroleum acids and its derivatives. Production and application (review). Trudi Rossiiskogo Gosudarstvennogo Yniversiteta nefti i gaza im. I.M. Gubkina, vol. 270, no. 1, p. 68-80, 2013. (In Russian).
2. Hajiyev S.N., Shpirt M.J. Microelements in petroleum and products of its refinery. М.: Nauka, 2012. (In Russian).
3. Mukhamedovich G.F., Rakibovich G.M., Renatovich B.T., Failovich G.R., Adievich S.A. Sub- and supercritical fluids in some problems of fillers extraction from solid matrices. Vesti gazovoi nauki, vol. 11, no. 3, 2010. (In Russian).
4. Demetrius A.N., Skibitskaya N.A., Zekel L.A., Nawrocki D.C., Krasnobaeva N.V., Doma- nova E.G. The composition and properties of natural high-molecular components of gas condensate and oil and gas fields, Chimiya tverdogo topliva, 2010, vol. 3, p. 67–77.
5. Gaspar A., Zellermann E., Lababidi S., Reece J., Schrader W. Characterization of Saturates, Aromatics, Resins, and Asphaltenes Heavy Crude Oil Fractions by Atmospheric Pressure Laser Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry//Energy Fuels, 2012, no. 26, p. 3481-3487.
6. Zhao X., Shi Q., Gray M.R., Xu C. New Vanadium Compounds in Venezuela Heavy Crude Oil Detected by Positive-ion Electrospray Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry//Sci. Rep., Jun. 2014, vol. 4.
7. Zhang L., Zhang Y., Zhao S., Xu C., Chung K. H., Shi Q. Characterization of heavy petroleum fraction by positive-ion electrospray ionization FT-ICR mass spectrometry and collision induced dissociation: Bond dissociation behavior and aromatic ring architecture of basic nitrogen compounds// Sci. China Chem., Jun. 2013, vol. 56, no. 7, p. 874–882.
8. Tanner R.P.R., Schaub M. Speciation of Aromatic Compounds in Petroleum Refinery Streams by Continuous Flow Field Desorption Ionization FT-ICR Mass Spectrometry//Energy Amp Fuels — ENERG FUEL, 2005, vol. 19, no. 4.
9. Klein G.C., Rodgers R.P., Marshall A.G. Identification of hydrotreatment-resistant heteroatomic species in a crude oil distillation cut by electrospray ionization FT-ICR mass spectrometry// Fuel, Oct. 2006, vol. 85, no. 14–15, p. 2071–2080.
10. Qian K., Edwards K.E., Dechert G.J., Jaffe S.B., Green L.A., Olmstead W.N. Measurement of Total Acid Number (TAN) and TAN Boiling Point Distribution in Petroleum Products by Electrospray Ionization Mass Spectrometry//Anal. Chem., 2008, vol. 80, no. 3, p. 849–85.
11. Marshall A.G., Rodgers R.P. Petroleomics: chemistry of the underworld//Proc. Natl. Acad. Sci. U.S.A., Nov. 2008, vol. 105, no. 47, p. 18090–18095.
12. A barrel load of compounds//Chemistry World, May 2010, p. 46–49.
13. De Hoffmann E., Stroobant V. Mass Spectrometry: Principles and Applications. — John Wiley & Sons, 2007.
14. Quan Shi D.H. Characterization of Heteroatom Compounds in a Crude Oil and Its Saturates, Aromatics, Resins, and Asphaltenes (SARA) and Non-basic Nitrogen Fractions Analyzed by Negative-Ion Electrospray Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry//Energy Amp Fuels, 2010, vol. 24, p. 2545-2553.
15. Kim S., Rodgers R.P., Blakney G.T., Hendrickson C.L., Marshall A.G. Automated Electrospray Ionization FT-ICR Mass Spectrometry for Petroleum Analysis//J. Am. Soc. Mass Spectrom, Feb. 2009, vol. 20, no. 2, p. 263–268.
16. Kim Y.H., Kim S. Improved abundance sensitivity of molecular ions in positive-ion APCI MS analysis of petroleum in toluene//J. Am. Soc. Mass Spectrom, Mar. 2010, vol. 21, no. 3, p. 386–39.
17. Fernandez-Lima F.A., Becker C., McKenna A.M., Rodgers R.P., Marshall A.G., Rus- sell D.H. Petroleum Crude Oil Characterization by IMS-MS and FTICR MS//Anal. Chem., 2009, vol. 81, no. 24, p. 9941–9947.
18. Panda S.K., Brockmann K.J., Benter T., Schrader W. Atmospheric pressure laser ionization (APLI) coupled with Fourier transform ion cyclotron resonance mass spectrometry applied to petroleum samples analysis: comparison with electrospray ionization and atmospheric pressure photoionization methods//Rapid Commun. Mass Spectrom, 2011, no. 25, p. 2317–2326.
19. Esther Lorente C.B. The detection of high-mass aliphatics in petroleum by matrix-assisted laser desorption/ionisation mass spectrometry//Rapid Commun. Mass Spectrom. RCM, 2012, vol. 26, no. 14, P. 1581–90.
20. Speight J.G. High Acid Crudes. — Gulf Professional Publishing, 2014.
21. Li X., Zhu J., Wu B. Characterization of Basic Nitrogen-Containing Compounds in the Products of Lube Base Oil Processing by Electrospray Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry//Bull. Korean Chem. Soc., 2014, vol. 35, no. 1, p. 165–172.
22. Marshall A.G., Rodgers R.P. Petroleomics: The Next Grand Challenge for Chemical Analysis//Acc. Chem. Res., 2003, vol. 37, no. 1, p. 53–59.
23. Yunju Cho A.A. Developments in FT-ICR MS Instrumentation, Ionization Techniques, and Data Interpretation Methods for Petroleomics — a Review//Mass Spectrom. Rev., 2014, vol. in press.
24. Wang L., He C., Zhang Y., Zhao S., Chung K.H., Xu C., Hsu C.S., Shi Q. Characterization of Acidic Compounds in Heavy Petroleum Resid by Fractionation and Negative-Ion Electrospray Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Analysis//Energy Fuels, Aug. 2013, vol. 27, no. 8, p. 4555–4563.
25. Kuangnan Qian W.K.R. Resolution and Identification of Elemental Compositions for More than 3000 Crude Acids in Heavy Petroleum by Negative-Ion Microelectrospray High-Field Fourier Transform Ion Cyclotron Resonance Mass Spectrometry//Energy Amp Fuels — ENERG FUEL, 2001, vol. 15, no. 6.
26. Yingrong L., Wei W., Qiuling H., Yuxia Z., Jinghui D., Songbai T. Characterization of Basic Nitrogen Aromatic Species Obtained during Fluid Catalytic Cracking by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry//Scientific Research., 2012, vol. 14, no. 2, p. 18–24.
27. Liu P., Xu C., Shi Q., Pan N., Zhang Y., Zhao S., Chung K.H. Characterization of Sulfide Compounds in Petroleum: Selective Oxidation Followed by Positive-Ion Electrospray Fourier Transform Ion Cyclotron Resonance Mass Spectrometry//Anal. Chem., Aug. 2010, vol. 82, no. 15, p. 6601–6606.

Near-infrared spectroscopy for monitoring quality of commodity and raw material flows of gasoline blending station
Oil and gas processing, chemistry of oil and gas

Authors: Ravilya Z. SAFIEVA graduated from Lomonosov Moscow State University in 1978. She is Doctor of Technical Sciences, Full Professor of the Department of Organic Chemistry and Petroleum Chemistry of Gubkin Russian State University of Oil and Gas. She is a specialist in the field of physical chemistry of oil disperse systems and methods of research. She is author of over 100 scientific publications. E-mail: safieva@gubkin.ru
Irina V. IVANOVA graduated from Kazan State University named after VI Ulyanov-Lenin in 2006. She is postgraduate student of the Department of Organic Chemistry and Petroleum Chemistry at Gubkin Russian State University of Oil and Gas. She is a specialist in the field of molecular spectroscopy. E-mail: irina20051984@rambler.ru

Abstract: Near-infrared spectroscopy (NIR) is becoming an effective and popular analytical technique in the petrochemical and refining industries, mainly because of the reliability and convenience for routine use. In this paper we have accumulated and systematized a large amount of spectral data obtained for the raw materials and commodity flows of gasoline blending station using near-infrared spectrometer with Fourier transform (FT-NIR) in ON-LINE mode. A correlation between the spectral data and the quality parameters, namely, octane numbers using research and motor methods, density, content: aromatic hydrocarbons, benzol and olefinic hydrocarbons; fractional composition, saturated vapors pressure. We have constructed and validated calibration models for these parameters and proposed these for use in real-time. The prediction error of the obtained gauge model lies within the reproducibility of the standard methods for each parameter

Index UDK: УДК 665.773.3

Keywords: infrared spectrometer with Fourier transform, spectroscopy of near-in-frared (NIR) range, commodity flows, commercial gasoline, gauge model, independent verification of models

1. Barsamian A. Get the Most Out of Your NIR Analyzers. Hydrocarbon Processing, January, 2001, p. 69-72.
2. Espinosa M.S. et al. On-line NIR Analysis and Advanced Control Improve Gasoline Blending. Oil and Gas Journal, Oct. 17, 1994.
3. Reboucas M.V., Dos Santos J.B., Domingos D. and Massa A.R. Near-infrared spectroscopic prediction of chemical composition of a series of petrochemical process streams for aromatics production. Vibr. Spectrosc. 52, 97 (2010). oi: 10.1016/j.vibspec.2009.09.006.
4. Watari M., Ozaki Y. Du and Y. Variations in predicted values from near-infrared spectra of samples in vials by using a calibration model developed from spectra of samples in vials: causes of the variations and compensation methods, Appl. Spectrosc. 61(4), 397 (2007). doi: 10.1366/ 000370207780466244.
5. Chung H. Applications of near infrared spectroscopy in refineries and important issues to address. Appl. Spectrosc. Rev. 42(3), 251 (2007). doi: 10.1080/05704920701293778.
6. Hoeil Chung, Hyuk-Jin Choi, and Min-Sik Ku. Rapid Identification of Petroleum Products by Near-Infrared spectroscopy. Bull. Korean Chem. Soc. 1999, vol. 20, no. 9.
7. Tonkov M.V. Fourier spectroscopy —maximum information for minimum time. Sorosovskiy education journal, t. 7, no. 1, 2001. (in Russian).
8. Carlos-A. Baldrich Ferrer, Luz-Angela Novoa Mantilla. Infrared spectrophotometry, a rapid and effective tool for characterization of direct distillation naphthas. CT&F, Colombia, 2005, no. 3.
9. Chung H., Ku M.S., Lee J.S. Comparison of near-infrared and mid-infrared spectroscopy for the determination of distillation property of kerosene. Vib. Spectrosc. 1999, no. 20, p. 155–163.
10. Ingrid Komorizono de Oliveira, Werickson F. de Carvalho Rocha, Ronei J. Poppi Application of near infrared spectroscopy and multivariate control charts for monitoring biodiesel blends. Analytica Chimica Acta, 2009, 642, p. 217–221.
11. Monteiro M.R., Ferreira A.G. Determination of biodiesel blend levels in different diesel samples by 1H NMR. Fuel, 2009, no. 88, p. 691–696.
12. Peinder P., Visser T. Partial least squares modeling of combined infrared, 1H NMR and 13C NMR spectra to predict long residue properties of crude oils. Vibrational spectroscopy, 2009, p. 8.
13. Narve Aske, Harald Kallevik, and Johan Sjoblom Determination of saturate, aromatic, resin, and asphaltenic (SARA) components in crude oils by means of infrared and near-infrared spectroscopy. Energy & Fuels, 2001, no. 15, p. 1304–1312.
14.< Safieva R.Z. Physics chemistry of crude oil. М.: Chemistry, 1998, 448 с. (in Russian).
15. http://www.fda.gov/cder/OPS/PAT.htm.
16. Krichenko V.P. Near Infrared spectroscopy, M., 1997. (in Russian)
17. Burns D.A., Ciurczak E.W. Handbook of Near-Infrared Analysis; Marcel Dekker: New York, USA, 1992.
18. Belova O.A. Operativno and Dostoverno. Article in Lukoil Sintez, 2012, no. 49, 1 p. (in Russian).
19. Filatov V.M., Safieva R.Z. Chemometrics for analysis refinery and petro chemistry products; Neftepererabotka and Neftechimistry, 2009, no. 9, p. 33–38. (in Russian).
20. Purevseren Sarangerel. Express method for analysis of crude oils and crude oil fractions properties during crude oil refining. Dokt, Diss., Moscow, Gubkin Russian State University of Oil and Gas, 2003, 177 p. (in Russian).
21. Filatov V.M. Razrabotka xemometricheskix metodik express-analisa pokazateley kachestva I sostava neftyanix system s primeneniem metoda blizhney infrakarasnoy spectroscopii, Dokt, Diss., Moscow, Gubkin Russian State University of Oil and Gas, 2010, 117 p. (in Russian).
22. Balabin P.M. Sozdanie express metodov analisa pokazateley kachestva distillyatnix fracsii na osnove kolebatelnoy spectroskopii. Dokt, Diss., Moscow, Gubkin Russian State University of Oil and Gas, 2013, 110 p. (in Russian).
23. Balabin R.M., Lomakina E.I. Support vector machine regression (SVR/LS-SVM) — an alternative to neural networks (ANN) for analytical chemistry. Comparison of nonlinear methods on near infrared (NIR) spectroscopy data. Analyst 136, 1703, 2011.
24. Balabin R.M., Safieva R.Z. Near-infrared (NIR) spectroscopy for biodiesel analysis: Fractional composition, iodine value, and cold filter plugging point from one vibrational spectrum. Energy & Fuels 25, 2373, 2011.
25. Balabin R.M., Safieva R.Z., Lomakina E.I. Gasoline classification using near infrared (NIR) spectroscopy data: Comparison of multivariate techniques. Anal. Chim. Acta 671, 27, 2010.
26. Balabin R.M., Safieva R.Z. Gasoline classification by source and type based on near infrared (NIR) spectroscopy data. Fuel 87, 1096, 2008.
27. Balabin R.M., Smirnov S.V. Variable selection in near-infrared (NIR) spectroscopy: Benchmarking of feature selection methods on biodiesel data. Anal. Chem. Acta 692, 63, 2011.
28. ASTM 1655-04 Standard Practices for Infrared Multivariate Quantitative Analysis.
29. ASTM 6122 Standard Practice for Validation of Multivariate Process Infrared Spectrophotometers.
30. www.brukeroptics.com/www.bruker.ru.
31. Martens, H.; Naes, T. M. Multivariate Calibration; John Wiley and Sons: New York, USA, 1989, p. 116.
32. Massart D.L.: Chemometrics: a textbook, Elsevier, NY, 1988.