BP神经网络技术在声波测井曲线重构中的运用  

APPLICATION OF BP NEURAL NETWORK TECHNOLOGY IN SONIC LOG DATA REBUILDING

作　　者：杨志力[1] 周路[2] 彭文利[3] 郑金云[2] 

机构地区：[1]杭州地质研究院,浙江杭州310023 [2]西南石油大学资源与环境学院,四川成都610500 [3]新疆油田公司勘探开发研究院,新疆克拉玛依834000

出　　处：《西南石油大学学报（自然科学版）》2008年第1期63-66,共4页Journal of Southwest Petroleum University(Science & Technology Edition)

摘　　要：基于神经网络的曲线重构法是提高声波测井曲线质量的有效方法。该方法通过神经网络技术的非线性算法,在声波曲线与自然电位、电阻率、自然伽马等多条测井曲线之间建立一种非线性关系。运用BP神经网络技术综合了自然电位、电阻率、自然伽马等多条曲线的信息对声波曲线进行重构,以此增加曲线重构的信息量,为曲线重构的准确性提供了保障。通过在准噶尔盆地石南地区的运用,证明该方法能大大提高受井壁垮塌影响的声波测井曲线的质量。The log reconstruction method based on neural network is a effective one to improve the quality of sonic log.The method,by means of non-linear algorithm of neural network technology,is used to set up a non-linear relation among sonic log curve,SP,Rt,Gr and curves.The sonic log curve is reconstructed by using BP neural network technology combining SP,Rt,Gr curves data as to enhance the information quality of curve reconstruction and ensure the accuracy of curve reconstruction.The practice in Shinan area,Junggar Basin proves the method can greatly improve the quality of sonic log curve where well wall is affected by collapse.

关 键 词：曲线重构 神经网络 声波测井 准噶尔盆地 石南地区 

分 类 号：TE822[石油与天然气工程—油气储运工程]