摘要
重力数据是所有地下场源产生的重力场的叠加,探测对象经常被淹没在区域背景场之中,因此剩余异常的分离对于重力资料研究至关重要,而近来被引入位场领域的小波算子作为了滤波器和场源分析工具,在这里我们分析研究基于小波分析与谱分析的二维离散小波变换用于提高重力异常的分辨能力,再现出由简单形状场源描述密度不均匀的几何特征.本文先介绍二维多分辨率分析小波的基本理论及其提升算法,利用对数功率谱估计平均深度方法理论,接着对理论模型数据进行多尺度异常分解,估计地质体的形状、大小和深度,最后又对实测重力数据进行分析,并与传统常规方法进行比较分析,结果表明对于实际数据分析其方法也是具有可行性的.
Gravity data is the result of gravity force field composition by all underground source. Detection object constantly are submerged in background field. Therefore one of the most common problems encountered in gravity data studies is how to separate each anomaly. The wavelet transform operator has recently been introduced in the domain of potential fields both as a filtering and as a source-analysis tool. Here we study the ability of improving resolution gravity anomaly based on wavelet analysis and power spectrum analysis. 2D discreet Wavelet transform for the multi- scale separation of gravity anomalies, in order to recover the geometric characteristics of density heterogeneities described by simple--shaped sources. In this paper, we first introduce the basic theory of the multiresolution wavelet analysis, its lifting scheme and the spectral factorization method for the gravity power, decompose model and reality gravity data by 2D discreet Wavelet transform, estimate approximately the shape, size and depth of the buried objects, and then compare them with the result of the traditional method, which demonstrated this way is effective for gravity data processing.
出处
《地球物理学进展》
CSCD
北大核心
2007年第1期112-120,共9页
Progress in Geophysics
基金
中国石油天然气集团公司科学研究与技术开发项目(04B020500)
湖北省自然科学基金项目(2005ABA275)资助
关键词
多分辨率分析
小波变换
提升算法
对数功率谱
重力异常
multiresolution analysis, wavelet transform, lifting scheme, power spectrum analysis, gravity anomaly
