基于贝叶斯网络的井口采油树风险评价研究
Research on Risk Assessment of Wellhead Christmas Tree Based on Bayesian Network
苑赫 1李政杰 2桑勇 1桂聪娇 3梁昌晶4
作者信息
- 1. 河北渤海石油装备专用车有限公司,河北任丘 062552
- 2. 渤海钻探工程有限公司油气井测试分公司,河北廊坊 065000
- 3. 中国石油集团渤海石油装备制造有限公司石油机械厂,河北任丘 062552
- 4. 中国石油华北油田分公司,河北任丘 062552
- 折叠
摘要
为降低采油树服役期间发生失效的可能性,在构建采油树失效故障树模型的基础上,实现了故障树模型向贝叶斯网络模型的转化;基于层次分析法和模糊集理论,实现了根节点先验概率的求解,并通过定义相关节点的时间变化特性,得到了不同时间采油树的失效概率变化情况.结果表明:采油树失效的发生概率为1.24×10-2,其中阀门泄漏的可能性最大,其次为法兰泄漏,计算结果与现场实际情况相符;介质腐蚀、流体含杂质、冲刷腐蚀、螺母松动、盘根变形是导致采油树失效的主要因素,应在现场管理中予以重视.
Abstract
In order to reduce the failure possibility of christmas tree during service,on the basis of building the failure tree model of the christmas tree,the transformation of the failure tree model to the Bayesian network model is realized.Based on the analytic hierarchy process and fuzzy set theory,the prior probability of the root node is solved.By defining the time variation characteristics of the relevant nodes,the change of the failure probability of the christmas tree at different times is obtained.The results show that the failure probability of christmas tree is 1.24×10-2,in which the valve leakage is the highest,followed by flange leakage.The calculated results are consistent with the actual situation.Medium corrosion,impurities influid,erosion corrosion,nut loosening and disc deformation are the main factors leading to christmas tree failure,which should be paid attention to in field management.
关键词
贝叶斯网络/故障树/采油树/风险评价/阀门泄漏Key words
Bayesian network/fault tree/christmas tree/risk assessment/valve leakage引用本文复制引用
出版年
2024
NETL
NSTL
万方数据