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Optimization and Intelligent Control for Operation Parameters of Multiphase Mixture Transportation Pipeline in Oilfield: A Case Study

Journal of pipeline science and engineering(2021)

引用 22|浏览14
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摘要
In order to achieve the purpose of efficient, safe and reliable operation, it has become the development trend and direction to build an intelligent oilfield transportation pipeline network with big data analysis, comprehensive situation awareness and automatic control and management capabilities in the future. In this paper, Supervisory Control and Data Acquisition (SCADA) system was used to collect the production and operation data of an oilfield in Western China. The thermal and hydraulic models have been corrected based on these collected data. Then, the influence factors of thermal characteristics of several categories of pipelines were analyzed, and the critical temperature gradient of various categories of pipelines was obtained by interpolating fitting method. Furthermore, the optimal operation conditions of the transportation pipelines were obtained, and the universal relationship of pipeline operation parameters was established as well. The results indicated that the corrected models can predict the temperature drop and pressure drop of multiphase mixture transportation pipeline well, liquid flow rate, water cut and initial temperature do have obvious influences on pipeline operation parameters, and the universal relationship of pipeline operation parameters can effectively guide the production practice of oilfield. However, the operation parameters optimization universal relationship cannot meet the requirements of personalized control of all pipelines. Therefore, this paper proposed an intelligent control strategy for multiphase mixture transportation pipeline in oilfield. This case study is of great significance to guide the optimization of operation parameters and ensure high efficiency and safe operation of multiphase mixture transportation pipelines in oilfield.
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关键词
Mixture transportation pipeline,Data analysis,Model correction,Operation parameters optimization,Intelligent control
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