摘要
为提高固井质量 ,实现固井质量的预测和跟踪分析 ,建立了一种基于人工神经网络的固井质量预测方法 ;采用SAS系统对影响固井质量的众多因素做相关分析 ,依据主要因素并通过人工神经网络建立了固井质量预测模型 .实际应用结果表明 ,该方法能够提高判断固井质量的精度 ,且特别适用于不确定或非结构化信息的处理 ,对固井中各种未知信息的预测有着较好的适用性 .
To improve cementing quality, a kind of forecasting method of cementing quality that is based on artificial neutral network is made to accomplish forecasting the cementing quality, tracing and analyzing. The SAS system is adopted to analyze many factors which affected cementing quality. According to main factors, a kind of forecasting model of cementing quality is established by artificial neutral network. The result of actual application shows that the method can not only improve accuracy of judging cementing quality but also process abscure or not-structural information and forecast all kinds of information that is not known in cementing.
出处
《大庆石油学院学报》
CAS
北大核心
2002年第2期52-55,共4页
Journal of Daqing Petroleum Institute
关键词
人工神经网络
固井质量
预测
应用
油气井
BP算法
artificial neutral network
cementing quality
BP algorithm
correlation analysis
Topology structure
