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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.