普光智能气田数据资源共享中心建设
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摘要
普光气田在建设之初建成了信息化基础设施,但由于缺乏统一的规划部署,各系统数据形成了多个"信息孤岛",数据资源不能满足智能气田建设的需要。为此,在分析该气田数据资源现状与问题的基础上,根据普光智能气田整体规划,提出了数据资源共享中心建设总体构想,设计了业务数据模型;通过构建数据标准、梳理数据来源、设计数据服务,实现了数据采、存、算、用一体化,并进行了现场应用。研究结果表明:(1)数据资源共享中心是普光智能气田建设的重要基础,其总体架构自下而上分为数据规范标准、数据"采、存、算、用"以及数据管控3层;(2)该数据资源共享中心实现了勘探开发、集输净化、生产经营、安全环保等数据一次采集、集中存储、共享使用、统一管理的目标,为智能气田业务系统建设提供了重要的数据基础,也为普光气田智能应用和移动应用系统提供了全面、可靠的数据支撑。
During the initial construction of the Puguang Gas Field, information infrastructure was built. Due to the absence of unified planning and deployment, however, many "isolated information islands" are formed in data systems, and the data resources cannot meet the construction requirements of intelligent gas field. In this paper, the status quo and problems of data resources in the Puguang Gas Field were analyzed, and a data resource sharing center was constructed according to the overall architecture design of the Puguang Intelligent Gas-field Project. Based on the architecture design of data resource sharing center, the overall construction conception of data resource sharing center was put forward and the business data model was designed. Finally, the integrated data collection, storage, calculation and utilization was realized by establishing data standard, combing data source and designing data service, and then it was applied on site. And the following research results were obtained. First, the data resource sharing center is an important foundation for the construction of this Project, and its overall architecture is divided into three layers from bottom to top, i.e., data specification and standard, data collection, storage, calculation and utilization, and data control. Second, the data resource sharing center achieves the one-time collection, centralized storage, shared use and unified management of exploration & development, gathering & purification, production & operation and safety & environmental protection data, and provides an important data base for the construction of business system of intelligent gas field and a comprehensive, reliable and effective data support for the intelligent and mobile application in the Puguang Gas Field.
During the initial construction of the Puguang Gas Field, information infrastructure was built. Due to the absence of unified planning and deployment, however, many "isolated information islands" are formed in data systems, and the data resources cannot meet the construction requirements of intelligent gas field. In this paper, the status quo and problems of data resources in the Puguang Gas Field were analyzed, and a data resource sharing center was constructed according to the overall architecture design of the Puguang Intelligent Gas-field Project. Based on the architecture design of data resource sharing center, the overall construction conception of data resource sharing center was put forward and the business data model was designed. Finally, the integrated data collection, storage, calculation and utilization was realized by establishing data standard, combing data source and designing data service, and then it was applied on site. And the following research results were obtained. First, the data resource sharing center is an important foundation for the construction of this Project, and its overall architecture is divided into three layers from bottom to top, i.e., data specification and standard, data collection, storage, calculation and utilization, and data control. Second, the data resource sharing center achieves the one-time collection, centralized storage, shared use and unified management of exploration & development, gathering & purification, production & operation and safety & environmental protection data, and provides an important data base for the construction of business system of intelligent gas field and a comprehensive, reliable and effective data support for the intelligent and mobile application in the Puguang Gas Field.
引文
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[3]杨栋枢,郭振,蔡云飞.企业数据标准及其管理体系研究[J].软件,2017,38(12):258-261.Yang Dongshu,Guo Zhen&Cai Yunfei.The research of enterprise data standards and management system[J].Computer Engineering&Software,2017,38(12):258-261.
[4]刘洋,李海燕.基于中医药事业管理业务域的数据集分类研究[J].国际中医中药杂志,2016,38(5):390-393.Liu Yang&Li Haiyan.Study of classification of traditional Chinese medicine datasets based on the business domain[J].International Journal of Traditional Chinese Medicine,2016,38(5):390-393.
[5]王韬,石昊东,季春梅.基于OPC协议的集中自动化控制系统[J].机械制造与自动化,2016,45(1):212-214.Wang Tao,Shi Haodong&Ji Chunmei.Centralized automatic controller based on OPC protocol[J].Machine Building&Automation,2016,45(1):212-214.
[6]于丽芳,张珍珍,杨贤,李赵红.基于P帧PU划分模式的H.264至HEVC视频转码重压缩检测算法[J].应用科学学报,2018,36(2):278-286.Yu Lifang,Zhang Zhenzhen,Yang Xian&Li Zhaohong.Frame PU partitioning mode based H.264 to HEVC video transcoding detection[J].Journal of Applied Sciences,2018,36(2):278-286.
[7]孙学波,石飞达.基于Hadoop的Apriori算法研究与优化[J].计算机工程与设计,2018,39(1):126-133.Sun Xuebo&Shi Feida.Reserch and optimization of Apriori algorithm based on Hadoop[J].Computer Engineering and Design,2018,39(1):126-133.
[8]周娜,何铮.云计算和云存储在安防系统中的应用[J].电脑知识与技术,2018,14(7):51-52.Zhou Na&He Zheng.The application of cloud computing and cloud storage in security system[J].Computer Knowledge and Technology,2018,14(7):51-52.
[9]张庆丹.基于Tong GTP的一种异地备份实现方式[J].信息安全与技术,2014,5(1):76-77.Zhang Qingdan.Remote backup based on TongGTP[J].Information Security and Technology,2014,5(1):76-77.
[10]欧志洪,胡天牧,康永.浅谈主数据管理应用问题治理[J].电子世界,2018(2):62-63.Ou Zhihong,Hu Tianmu&Kang Yong.Discussion on the application of main data management[J].Electronics World,2018(2):62-63.