检索结果-南通市图书馆

Application of adaptive neuro-fuzzy inference system and data mining approach to predict lost circulation using DOE technique (case study: Maroon oilfield)

引用

Petroleum 2020年第4期6卷 423-437页

作者： farough agin Rasool Khosravanian Mohsen Karimifard Amirhosein Jahanshahi Department of Petroleum Engineering Amirkabir University of Technology(Tehran Polytechnic)424 Hafez AvenueTehran15875-4413Iran Research Institute of Petroleum Industry(RIPI) West Blvd.Near Azadi Sports ComplexTehran14857-33111Iran Department of Petroleum Engineering Petroleum University of TechnologyAhwazIran School of Mining Engineering College of EngineeringUniversity of Tehran14174-66191TehranIran

Lost circulation is the most common problem encountered while drilling oil *** of such a problem can cause a lot of time and cost *** order to drill oil wells,a fast and profitable way is necessary to predict and solve lost circulation *** system is a method used lately for problems that deal with *** this paper,three approaches are carried out for prediction of lost circulation *** approaches include design of experiments(DOE),data mining,and adaptive neuro-fuzzy inference system(ANFIS).Data of 61 wells of Maroon oilfield are selected and sorted as the feed of the *** variables are used as inputs of the approaches and one variable is used as the ***,DOE is conducted to observe the effects of ***-Burman method is used to determine the effects of variables on lost *** that,data mining is conducted to predict the amount of lost *** class of regression is used to determine a function to model the data and the error of the ***,ANFIS is applied to predict the amount of lost *** chosen data are used in order to train,test,and control the ***,subtractive clustering is used to train the fuzzy inference system(FIS)of the *** performance of the ANFIS model is assessed through the root mean squared error(RMSE).The results suggest that ANFIS method can be successfully applied to establish lost circulation prediction *** addition,results of ANFIS and data mining are investigated through their prediction *** comparison of both methods reveals that ANFIS error is much lower than data mining.

关键词： Lost circulation Maroon oilfield ANFIS RMSE Expert system

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：