基于大数据的管道系统数据分析模型及应用  

Data analysis model for pipeline system and its application based on Big Data

作　　者：董绍华 安宇 

机构地区：[1]中石油北京天然气管道有限公司,北京100101

出　　处：《油气储运》2015年第10期1027-1032,共6页Oil & Gas Storage and Transportation

摘　　要：以往管道企业数据分析侧重于因果关系,而在大数据时代,管道系统一系列的信息集成、管理程序、检测记录以及日常运维记录等都将通过物联网、云计算等数据网络串联起来,其数据分析方向逐渐由因果关系向非因果(关联性)关系转变。通过对大数据分析模型进行研究,得出大数据分析将是管道企业未来发展的重要趋势之一,建立了适合于未来发展的管道系统大数据管理架构模型,提出了基于大数据的管道数据算法模型,进一步完善了内检测数据管理模型,并在管道泄漏和预警、管道地质灾害、管道腐蚀管理、管道内检测数据分析等方面实践应用,获得了能耗控制、灾害管理、风险控制等综合性、全局性的分析结论,对于管道大数据领域在管道行业的发展和应用具有重要意义。Previously, analysis on the data of pipeline enterprise focused on the causality. However, in the Big Data Era, a series of information integrations, management procedures, detection records and routine operation and maintenance records of the pipeline system are linked up by data networks like internet of things （IOT） and cloud computing, making the data analysis gradually change from causality to non-causal relationship （relevance）. In this paper, based on study on the Big Data analysis model, it is concluded that Big Data analysis will be one of the major trends of pipeline enterprise. Consequently, this paper builds a Big Data management architecture model suitable for the future pipeline system, proposes a Big Data based pipeline data algorithm model, and further improves the inline detection data management model. All these models were actually used for data analysis in the aspects like pipeline leakage and warning, pipeline geologic disaster, pipeline corrosion management and pipeline inline detection. Integrated and global analysis conclusions related to energy consumption control, hazard control and risk control have been obtained, showing the significances of Big Data in the development of pipeline industry. （7 Figures, 2 Tables, 13 References）

关 键 词：大数据 管道系统 数据分析模型 内检测数据管理 腐蚀管理 

分 类 号：TE972[石油与天然气工程—石油机械设备]