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基于本体的钻具组合智能设计
引用本文:邵波,段友祥,孙歧峰,李洪强.基于本体的钻具组合智能设计[J].计算机系统应用,2018,27(6):47-52.
作者姓名:邵波  段友祥  孙歧峰  李洪强
作者单位:中国石油大学(华东) 计算机与通信工程学院, 青岛 266580,中国石油大学(华东) 计算机与通信工程学院, 青岛 266580,中国石油大学(华东) 计算机与通信工程学院, 青岛 266580,中石化胜利油田 钻井工艺研究院, 东营 257000
基金项目:“十三五”重大专项(2017ZX05009-001)
摘    要:为提高钻具组合设计过程中的设计知识利用率和设计效率,提出一种基于本体的钻具组合智能设计方法.该方法通过构建井眼参数、地层参数、模型知识以及钻井工程实例的本体模型,实现了对钻具组合设计知识的表示,构建钻具组合设计知识库,建立了本体间的语义映射关系,完成了对钻具组合设计知识的组织、推送和嵌入.最后,结合基于案例的推理方法,实现了对钻具组合的智能设计.

关 键 词:钻具组合设计  本体  知识库  案例推理
收稿时间:2017/9/25 0:00:00
修稿时间:2017/10/18 0:00:00

Intelligent Drilling Assembly Design Based on Ontology
SHAO Bo,DUAN You-Xiang,SUN Qi-Feng and LI Hong-Qiang.Intelligent Drilling Assembly Design Based on Ontology[J].Computer Systems& Applications,2018,27(6):47-52.
Authors:SHAO Bo  DUAN You-Xiang  SUN Qi-Feng and LI Hong-Qiang
Affiliation:College of Computer & Communication Engineering, China University of Petroleum, Qingdao 266580, China,College of Computer & Communication Engineering, China University of Petroleum, Qingdao 266580, China,College of Computer & Communication Engineering, China University of Petroleum, Qingdao 266580, China and Drilling Technology Research Institute, Shengli Oilfield, SINOPEC, Dongying 257000, China
Abstract:In order to improve the design knowledge utilization and design efficiency in drilling assembly design, an intelligent design method based on ontology is proposed in this study. The method realizes the representation of the design knowledge of the drilling assembly and constructs the knowledge base of the design of the drilling assembly by constructing ontology model including borehole parameters, formation parameters, model knowledge, and drilling engineering base. In the method, the semantic mapping relations among ontologies are built. Thus an intelligent drilling assembly design pattern was formed and the organization, push and embedding of design knowledge are realized. Combining the case-based reasoning method, the intelligent design of drilling assembly is realized.
Keywords:drilling assembly design  ontology  knowledge base  case reasoning
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