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8738776 
Journal Article 
Detection and Analysis of Water Content of Crude Oil by Near Infrared Spectroscopy 
Liu, HM; Liu, YJ; Zhong, ZC; Song, Y; Li, Z; Xu, Y 
2021 
Yes 
Guangpuxue yu Guangpu Fenxi / Spectroscopy and Spectral Analysis
ISSN: 1000-0593 
41 
2 
505-510 
Chinese 
WOS:000626516700029 
As an important strategic resource, petroleum has an important significance in real-time analysis and detection of its components in the petrochemical industry. With the continuous development of petroleum resources, in the production process of long-term oil wells and before the exploitation of new oil wells, it is necessary to analyze and test the components of underground crude oil to determine the necessity of mining. Real-time detection of crude oil components plays a key role in the process of crude oil exploitation, production, storage, transportation and sales. In view of the low accuracy and low efficiency of traditional detection methods, near-infrared spectroscopy, which has been widely and effectively applied in the field of measurement, has been introduced into the research methods of crude oil components detection technology in recent years. In this paper, the underground crude oil was used as the research object, and the experimental samples of 39 components with crude oil ratio of 1%~20% were prepared by using the purified crude oil and water obtained from Daqing Oilfield to simulate the underground crude oil. In this paper, the basic principle of the measurement of crude oil components by near-infrared spectroscopy is studied. The near-infrared spectroscopy data measurement system of crude oil samples is integrated with the halogen source and supporting components by SW2520 near-infrared spectroscopy, and 39 groups are collected by this measurement after system standardization testing. Moving window smoothing Savitzky-Golay convolution smoothing and Savitzky-Golay convolution derivation method of near infrared spectrum data of crude oil near infrared spectral data is used to remove noise, two analysis methods of near-infrared spectra of crude sample partial least squares and support vector machine (SVM) regression method are used for retreatment modeling, crude oil component analysis prediction model is established respectively. The results show that the RMS predicted by partial least square method is 0.003 755 14, and the coefficient of determination R2 was 0.999 999. The prediction effect is very good. In this study, the near infrared spectroscopy (NIRS) technology is used to test and analyze the simulated test samples with different proportions, which provides a new idea for the detection of the components of the downhole crude oil. This method effectively solves the detection problem of the water content of the crude oil and provides technical support for the development of the real-time crude oil detection and analysis equipment in the field. © 2021, Peking University Press. All right reserved. 
Crude oil; Near infrared spectrum; Partial least squares; Pretreatment