Haar小波变换在测井曲线相似性对比中的应用  

Application of Haar Wavelet Transform in Well-logging Curve Similarity

作　　者：柴艳领 唐志涛 

机构地区：[1]东北石油大学计算机与信息技术学院 [2]内蒙古大唐国际锡林浩特矿业

出　　处：《计算机技术与发展》2016年第1期119-123,共5页Computer Technology and Development

基　　金：国家自然科学基金资助项目(61170132);国家重大专项(2011ZX05020-007);黑龙江省教育厅科学技术研究资助项目(12521055)

摘　　要：针对测井曲线信号中存在的噪声以及其形态特征的性质,结合分析了Haar小波变换以及测井曲线小波变换原理,提出基于Haar小波变换的测井曲线相似性识别方法。应用小波分解将测井曲线的信号分解为宏观特征信息、细节信息和噪音信息三部分,把下套管前得到的自然伽马曲线与下套管后测得的自然伽马曲线作为同一类,用于完井深度校正中的砂岩对比层识别中,利用形态特征的相似计算方法判别分析曲线的宏观信息。这些曲线信息是经Haar小波变换后得到的,对测井曲线的相似性进行对比,准确查找射孔深度对比层位。实验结果表明,该方法能够有效地用于测井曲线相似性对比识别中。According to the nature of the morphological features and the existence of the noise of logging curve,combined with the analysis of the Haar wavelet transform and the wavelet transform principle of logging curve,the identification method of the well- logging curve similarity based on Haar wavelet transform was presented. Wavelet decomposition is used to decompose log curve of the signal into macro characteristic information,details and noise. The former and the after natural Gamma curve is regarding as the same,used in sandstone layer recognition of the completion depth correction. The method of the similarity of morphological characteristics is applied to analyze the macro information for curve,which is obtained by Haar wavelet transform for similarity comparison of logging curve,finding the perforation depth contrast layers accurately. The experiments showthe effectiveness of this method.

关 键 词：形态特征 小波变换 测井曲线 相似性对比 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]