小波变换与地震奇异性属性

英文篇名：WAVELET TRANSFORM AND SEISMIC SINGULARITY ATTRIBUTE
中文刊名：物探化探计算技术
英文刊名：Computing Techniques for Geophysical and Geochemical Exploration
作者：周静毅 ; 印兴耀 ; 吴国忱
英文作者：ZHOU Jing-yi ; YING Xing-yao ; WU Guo-chen(Faculty of Geo-resources and Information Petroleum University ; Dongying 257061 ; China).
中文关键词：地震属性 ; 奇异性属性 ; 小波变换 ; 奇异指数
英文关键词：seismic attribute ; singularity attribute ; wavelet Transform ; singularity exponent
出版日期：2006-05-28
机构：中国石油大学地球资源与信息学院,中国石油大学地球资源与信息学院,中国石油大学地球资源与信息学院山东东营257061,山东东营257061,山东东营257061
年：2006
期：02
出版单位：物探化探计算技术

摘要

地震属性是由地震数据提取的有关地震波的几何形态、运动学特征、动力学特征和统计学特征等组成。这里主要讨论了一种新的地震属性(奇异性属性)计算方法。由于地震数据携带着大量的奇异性信息,因此,这一新的地震属性是在偏移地震数据的小波变换和奇异性分析的基础上形成的。小波变换使检测数据中的局部奇异程度成为可能。为能够估计出偏移地震数据每一采样点的局部奇异规律,从小波变换系数的角度来提取地震信号的奇异指数。这种新属性实行单道处理,不需要子波和速度信息,它给出了地下分层情况和断层位置。在地震数据奇异性属性的基础上,用小波变换来划分地层旋回,从而提高了小波变换在地震解释中的应用。
Seismic attributes are specific measurements of geometric,kinematic,dynamic,or statistical features derived from seismic data.This paper discusses computational method of a new seismic attribute(singularity attribute).Seismic data has much singular information,the new seismic attribute is developed based on wavelet transform and singularity analysis of seismic data.Wavelet transform make it possible to measure local singularity.To estimate local singularity of each sample of migrated seismic data,singularity exponent of seismic signal is extracted from the point of view of wavelet transform coefficients.The singularity attribute is computed directly from the migration data as a single-channel process.No velocity information is required to generate this result.The new attribute provides a layered model of the subsurface and precision fault location.On the basis of singularity attribute extracted from seismic data,stratum gyration is partitioned using wavelet transform.The method can improve the application of wavelet transform in seismic interpretation.

引文

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