钻井井漏风险实时监测与诊断系统设计  

Real-time Monitoring and Diagnosis System of Lost-circulation Risk

作　　者：袁本福[1] 李黔[1] 梁海波[1] 张继军 

机构地区：[1]西南石油大学石油工程学院,四川成都610500 [2]中国石油长城钻探录井公司,辽宁盘锦124010

出　　处：《天然气技术与经济》2013年第1期46-48,79,共3页Natural Gas Technology and Economy

基　　金："十一五"国家油气重大科技攻关项目(编号:2008ZX05000-021-006)

摘　　要：为了有效识别与预防钻井工程中的井漏风险,将理论研究与现场实际相结合,自主开发了井漏风险实时监测与诊断系统。其主要特点是采用BP神经网络算法,通过神经网络对邻井风险样本的自学习、记忆和分类,获取井漏风险因素之间的内在联系,对蕴含在钻井工程运行中的规律进行映射,从而使井漏风险推理更具参考性和准确性。分析了井漏风险实时监测与诊断流程,详细介绍了系统的各个模块组成以及主要模块的功能。现场应用表明,该系统能够对井漏风险进行实时监测与诊断。A real-time monitoring and diagnosis system is developed in order to identify and prevent lost-circulation risk during drilling. An algorithm of BP neural network is adopted for this system. At first, the relationship among risk factors is gained through recording and classifying the risk samples from surrounding wells; and then, the operation laws in drilling engineering are reflected to make the risk reasoning more helpful and accurate. In addition, the process of real-time monitoring and diagnosis system is analyzed, and the module composition in this system and the function of main module are presented. Field application shows that the system is effective.

关 键 词：井漏 监测 诊断系统 BP神经网络 

分 类 号：TE28[石油与天然气工程—油气井工程]