重力异常分离的小波域优化位变滤波方法  

Preferential spatially varying filtering method in the wavelet domain for gravity anomaly separation

作　　者：刘彩云[1,2] 姚长利[2] 郑元满[2] 

机构地区：[1]长江大学信息与数学学院,湖北荆州434023 [2]中国地质大学地球物理与信息技术学院,北京100083

出　　处：《地球物理学报》2015年第12期4740-4755,共16页Chinese Journal of Geophysics

基　　金：国家高技术研究发展计划(863计划)课题(2014AA06A613);国家自然科学基金项目(61273179);湖北省教育厅科学技术研究项目(D20131206)联合资助

摘　　要：在重力异常分离中,频率域滤波分离方法是以全局数据频谱特征设计针对性的滤波器实现的.滤波器参数与空间位置无关,因此无法针对局部数据频谱特征动态调整滤波器参数.针对该局限性,在小波域滤波理论和优化滤波方法的基础上,本文研究提出了小波域优化位变滤波法,该方法具有空间变化滤波能力,在不同空间位置实现不同的滤波器特性,从而能实现局部数据频谱与全局数据频谱存在较大差异的重力异常分离问题.理论模型数据分离实验结果表明,在局部数据频谱与全局数据频谱差异较大的情况下,该方法相对于Butterworth滤波和优化滤波等方法具有优势.最后,用一个实例进行检验计算,体现了所提方法技术的效果和应用前景.The classical frequency domain filtering method for gravity anomaly separation cannot change its frequency response at different spatial positions to adapt the frequency characteristic of local data,for the reason of lacking spatial information with Fourier transform.A preferential spatially varying filtering method in the wavelet domain（PSVF-WD）is proposed based on the scaling filtering theory and preferential filtering method,in order to overcome the limitation of the classical frequency domain filtering method mentioned above.This method uses a preferential spatially varying filter to separate gravity anomalies.Firstly,it segments gravity anomaly data into several blocks after analyzing the spatial distribution characteristics of frequency components with the wavelet analysis method.Secondly,it obtains the local translation function with the preferential filtering method and calculates the local equivalent coefficients with the method derived in this paper.Thirdly,it combines the localequivalent coefficients to global ones according to the position information of them and achieves the design of PSVF-WD.Lastly,it obtains separated gravity anomalies using the global equivalent coefficients of PSVF-WD and wavelet coefficients of gravity anomalies.We test the PSVF-WD with gravity-anomaly separation experiments of three synthetic data and one real data.In experiment 1,the PSVF-WD separates the composite signal of four different frequency sinusoidal signals using low-high filtering at one time.The results of this experiment show the spatially varying filtering ability of PSVF-WD.In experiment 2,the synthetic model consists of four prisms.Two of them belong to a relatively shallower layer and the other two of them belong to relatively deeper layer.However,one prism of the relatively shallower layer is deeper than another prism of the relatively deeper layer.The PSVF-WD method separates the anomalies of the relative shallower layer and deeper layer pretty well,while the preferential filtering method only separates

关 键 词：异常分离 小波域 优化滤波 位变滤波 重力异常 

分 类 号：P631[天文地球—地质矿产勘探]