摘要
由于钻井工程的复杂性和不确定性,简单依靠传统数学建模的方法很难完全描述和表征钻井过程.引入本体和贝叶斯网络等人工智能技术,探究了钻井事故诊断的理论和方法,解决和描述了钻井领域的非结构化问题,进而更好地指导实践.
Drilling engineering is a field with huge investment and high risk.There are complexity and uncertainty in drilling process,so it is difficult to describe and characterize the drilling process using conventional mathematical modeling methods.For this reason,artificial intelligence technologies-ontology and Bayesian network are introduced to study the theory and method of drilling accident diagnosis for solving and describe the unstructured problems and concepts in drilling process,and guiding practice further.
出处
《西安石油大学学报（自然科学版）》
CAS
北大核心
2012年第3期50-53,4+3,共4页
Journal of Xi’an Shiyou University（Natural Science Edition）
基金
陕西省教育厅专项科研计划项目(编号:2010JK779)
关键词
钻井工程
钻井事故诊断
智能模型
知识本体
贝叶斯网络
drilling engineering
drilling accident diagnosis
intelligent model
ontology
Bayesian network
