应用光学, 2018, 39 (3): 436, 网络出版: 2018-06-29   

基于激光拉曼检测技术的输油管道原油鉴别方法

Identification method of crude oil in petroleum pipeline based on laser Raman detection technology
作者单位
辽宁石油化工大学 石油天然气工程学院,辽宁 抚顺 113000
摘要
为降低长距离原油输送过程中混油产生的损失,需定时检测管线原油成分以确定是否出现混油事故。常规检测输油管线原油成分需从现场管线中取样后,再进行室内检测,该类技术操作复杂且易受环境因素的影响,未能实时反映管道混油后油品成分变化。文中应用激光拉曼光谱对原油识别检测进行了实验研究,试验选取辽河油田不同区块2种原油,通过特征峰及图谱分析,实现不同类型原油的识别。结果表明,2 800 cm-1~3 000 cm-1区域特征峰是激光拉曼证明烷烃存在的重要标志,该段拉曼谱图特征峰的不同代表了烷烃组分的差异性,可以有效区分不同类型的原油。该方法的进一步研究,有望形成一套油品快速、实时检测的技术方法。
Abstract
In order to reduce the wastage due to mixing oil in long distance transportation of crude oil, it is necessary to detect the pipeline crude oil composition in time to determine whether there is a mixed oils accident. Routine examination of crude oil components in oil pipelines need to obtain sample from the field pipeline and make test in laboratory. This technology operation is complicated and easily affected by environmental factors, and failed to reflect the real-time changes of oil composition after oils are mixed.The application of laser Raman spectroscopy for the detection and identification of crude oil has been studied experimentally. In the experiment, two kinds of crude oils were selected from different blocks of Liaohe oil field. Identification of different types of crude oils was carried out through characteristic peaks and spectral analysis. The results show that the characteristic peak of 2 800 cm-1~3 000 cm-1 region is an important sign for the identification of saturated hydrocarbons by laser Raman spectroscopy. This section of Raman spectrum represents the diversity of saturated hydrocarbons components and distinguish between different types of crude oils. Further research is expected to form a set of rapid and real-time detection methods during transportation of crude oils.

刘建美, 李存磊, 高鹏, 王瑞, 朱宁, 付洪涛. 基于激光拉曼检测技术的输油管道原油鉴别方法[J]. 应用光学, 2018, 39(3): 436. Liu Jianmei, Li Cunlei, Gao Peng, Wang Rui, Zhu Ning, Fu Hongtao. Identification method of crude oil in petroleum pipeline based on laser Raman detection technology[J]. Journal of Applied Optics, 2018, 39(3): 436.

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