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石油勘探开发一体化数据仓的建立和应用
引用本文:赵贵菊,王彦春,崔其山,崔淑红.石油勘探开发一体化数据仓的建立和应用[J].物探与化探,2010,34(1):108-110.
作者姓名:赵贵菊  王彦春  崔其山  崔淑红
作者单位:1. 中国地质大学,地下信息探测技术与仪器教育部重点实验室,北京,100083
2. 中国地质大学工程技术学院,北京,100083;中国石油工程建设公司,北京,100011
3. 中国地质大学水资源与环境学院,北京,100083
基金项目:中国石油天然气股份有限公司资助项目 
摘    要:随着石油勘探开发数据信息的海量增加,勘探和开发部门都建立了数据库,但由于勘探数据和开发数据分属不同的部门管理,从某种程度上 来形成了两大“信息孤岛”,所以迫切需要一种集勘探和开发为一体的数据仓管理方案,一是实现数据的共享,二是为综合性应用研究提供支持。通 过对勘探开发数据的调研和分析,提出了勘探开发为一体的石油专业数据仓库模型管理模式,并结合勘探开发业务需求,实现了基于此数据仓模型 的典型应用,证明了勘探开发一体化数据仓建立的可行性和科学性。

关 键 词:数据仓库  勘探开发  模型搭建  应用研究

THE CONSTRUCTION AND APPLICATION OF DATA WAREHOUSE FOR OIL EXPLORATION AND DEVELOPMENT
ZHAO Gui-ju,WANG Yan-chun,CUI Qi-shan,CUI Shu-hong.THE CONSTRUCTION AND APPLICATION OF DATA WAREHOUSE FOR OIL EXPLORATION AND DEVELOPMENT[J].Geophysical and Geochemical Exploration,2010,34(1):108-110.
Authors:ZHAO Gui-ju  WANG Yan-chun  CUI Qi-shan  CUI Shu-hong
Institution:ZHAO Gui-ju1,WANG Yan-chun1,CUI Qi-shan2,3,CUI Shu-hong4(1.Geo-detection Laboratory,Ministry of Education,China University of Geosciences,Beijing 100083,China,2.School of Engineering , Technology,3.China Petroleum Engineering & Construction Corporation,Beijing 100011,4.School of Water Resources & Environment,China)
Abstract:With the increase of data information on oil exploration and development, some departments have set up databases. Nevertheless, as exploration and development belong to different branches, two isolated big information islands have come into being. Therefore, a solution must be put forward which combines the exploration with development. This plan can not only implement the data share but also provide technical support for the application and research. Through an analysis of database and a study of data mining technology, the authors put forward a designing scheme based on the exploration and development of data warehouse, which is in connection with the requirement of production flow. A typical software has been designed, which is based on the model. The result obtained shows that the incorporated data warehouse is feasible and reasonable.
Keywords:   data warehouse  exploration and development  model construction  research and application
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