基于小波分析的断层检测  

Fault detection based on wavelet analysis

作　　者：薛姣[1] 蔡成国[1] 

机构地区：[1]中国地质大学(武汉)地空学院,武汉430074

出　　处：《地球物理学进展》2010年第6期2091-2095,共5页Progress in Geophysics

基　　金：中国地质大学(武汉)优秀青年教帅资助计划项目(CUGQNL0941)资助

摘　　要：断层在地震数据中显示出奇异性,经过小波变换可以得到断层位置处地震数据的奇异性属性.对包含断层的地震数据进行小波分析处理,能够得到断层的垂直和水平位置.在实际地震资料中将地震信号表示成不同尺度和不同位置的基本单元,然后对变换系数进行极值提取,检测出不同尺度下的地震信号突变特征,从而进行断层检测.对实际地震资料进行地震信号奇异性检测时,首先将地震剖面划分成层,然后在每一层内将尺度参数进行离散化,计算地震记录的小波变换系数,对于某一个尺度求取每一道小波变换系数的最大值,将每一道地震记录小波变换系数的最大值根据原地震道的位置进行排列,得到奇异性曲线.对于某一尺度,断层所在的水平位置对应着奇异性曲线的最值位置,最后绘出整个剖面的极值点检测结果.The singularity of the seismic data caused by faults is important in geophysiccal interpretation. After wavelet transform, the singularity attribute of the seismic data can be used to estimate faults. The vertical and horizontal positions of the faults can be estimated by transformation of the seismic data. In real seismic data, the seismic signal can he decomposed into basic units of different scales and positions. Then, relative extrema can be estimated on the basis of transformation coefficient. The positions of the singularity can be interpreted as faults of different scales. When is comes to real seismic data, the seismic profiles are divided into layers, scale parameters are discreted, and wavelet transform coefficients are calculated. The maximum wavelet transform coefficients of every scale are obtained and arrayed, thus the singular curves are obtained. For a certain scale, horizon positions of the faults are related to the maximum values of the singular curve. Faults on the seismic profile can be determined.

关 键 词：小波变换 地震奇异性属性 断层检测 

分 类 号：P631[天文地球—地质矿产勘探]