Scientific and technical journal

«Proceedings of Gubkin University»

ISSN 2073-9028

Proceedings of Gubkin University
NEAR-INFRARED SPECTROSCOPY FOR MONITORING QUALITY OF COMMODITY AND RAW MATERIAL FLOWS OF GASOLINE BLENDING STATION

UDC: 665.773.3
DOI: -

Authors:

Safieva Ravilya Z.1,
Ivanova Irina V.1

1 Gubkin Russian State University of Oil and Gas

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

Annotation:

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.

Bibliography:

1. Barsamian A. Get the Most Out of Your NIR Analyzers. Hydrocarbon Processing, January, 2001, p. 69-72.
2. Espinosa, M.S. et Аl. On-line NIR Analysis and Advanced Control Improve Gasoline Blen-ding. 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. Chung H., Choi Hyuk-Jin and Ku Min-Sik. Rapid Identification of Petroleum Products by Near-Infrared spectroscopy, Bull. Korean Chem. Soc. 1999, vol. 20, no. 9.
7. Тонков М.В. Фурье-спектроскопия — максимум информации за минимум времени//Со-росовский образовательный журнал, 2001. — Т. 7. — № 1.
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. — № 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, № 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. Сафиева Р.З. Физикохимия нефти. — М.: Химия, 1998. — 448 с.
15. http://www.fda.gov/cder/OPS/PAT.htm.
16. Крищенко В.П. Ближняя инфракрасная спектроскопия. — Москва, 1997.
17. Burns D.A., Ciurczak E.W. Handbook of Near-Infrared Analysis. Marcel Dekker: New York, USA, 1992.
18. Белова О.А. Оперативно и достоверно//Лукойл СИНТЕЗ (корпоративная газета ОАО „ЛУКОЙЛ-Нижегороднефтеоргсинтез”), 2012. — № 49. — С. 1-2.
19. Филатов В.М., Сафиева Р.З. Хемометрические методы анализа продукции нефтепереработки и нефтехимии//Нефтепереработка и Нефтехимия. — 2009. — № 9. — С. 33-38.
20. Пурэвсурэн Сарангэрэл „Экспресс-метод анализа свойств нефтей и нефтяных фракций при их переработке”, дисс. на соиск. уч. степ.канд. техн. наук. — М.: РГУ нефти и газа им. И.М. Губкина, 2003. — 177 с.
21. Филатов В.М. „Разработка хемометрических методик экспресс-анализа показателей качества и состава нефтяных систем с применением метода ближней инфракрасной спектроскопии”, дисс. на соиск. уч. степ.канд. техн. наук. — М.: РГУ нефти и газа им. И.М. Губкина, 2010. — 117 с.
22. Балабин Р.М. „Создание экспресс-методов анализа показателей качества дистиллятных фракций основе методов колебательной спектроскопии”, дисс. на соиск. уч. степ. канд. техн. наук. — М.: РГУ нефти и газа им. И.М. Губкина, 2013. — 110 с.
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.