王巨洪, 张世斌, 王新, 李荣光, 王婷. 中俄东线智能管道数据可视化探索与实践[J]. 油气储运, 2020, 39(2): 169-175. DOI: 10.6047/j.issn.1000-8241.2020.02.006
引用本文: 王巨洪, 张世斌, 王新, 李荣光, 王婷. 中俄东线智能管道数据可视化探索与实践[J]. 油气储运, 2020, 39(2): 169-175. DOI: 10.6047/j.issn.1000-8241.2020.02.006
WANG Juhong, ZHANG Shibin, WANG Xin, LI Ronguang, WANG Ting. Exploration and practice of data visualization for intelligent pipeline in China–Russia Eastern Gas Pipeline[J]. Oil & Gas Storage and Transportation, 2020, 39(2): 169-175. DOI: 10.6047/j.issn.1000-8241.2020.02.006
Citation: WANG Juhong, ZHANG Shibin, WANG Xin, LI Ronguang, WANG Ting. Exploration and practice of data visualization for intelligent pipeline in China–Russia Eastern Gas Pipeline[J]. Oil & Gas Storage and Transportation, 2020, 39(2): 169-175. DOI: 10.6047/j.issn.1000-8241.2020.02.006

中俄东线智能管道数据可视化探索与实践

Exploration and practice of data visualization for intelligent pipeline in China–Russia Eastern Gas Pipeline

  • 摘要: 为了推动油气管道数据可视化及大数据分析技术发展,对中俄东线智能管道数据可视化建设成果进行了总结。从数据可视化角度,论述了中俄东线天然气管道的数据种类、数据现状及各信息系统的数据架构及数据量;从数据传输、数据ETL(Extract-Transform-Load)等方面,探索了数据可视化实现的做法和实践。通过中俄东线智能管道可视化交互系统的探索和实践,实现了建设期和运营期多源动静态数据的集成展示,提出需数据中心建设和应用层解决方案作为技术支撑的建议,对推进管道数据可视化、大数据分析有一定指导意义。

     

    Abstract: In order to summarize the achievements of the data visualization construction of the intelligent pipeline in China–Russia Eastern Gas Pipeline and promote the development of data visualization and big data analysis technology for oil and gas pipelines, the data types, data status, data structure and data volume of China–Russia Eastern Gas Pipeline were discussed from the perspective of data visualization. Methods and practices for realizing data visualization were also researched from the aspects of data transmission, data Extract-Transform-Load(ETL), etc. Through the exploration and practice of interactive visualization system of the intelligent pipeline in China–Russia Eastern Gas Pipeline, integrated display of multi-source dynamic and static data during construction and operation has been realized, and the proposed suggestions, which require the supports of data center construction and solutions for application layer, will provide certain guiding significance for promoting pipeline data visualization and big data analysis.

     

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