小波分析在地震资料去噪中的应用

小波变换方法已广泛应用于信号处理领域。应用多尺度小波分析方法来消除地震观测信号中的噪声是一种行之有效的方法。这里从小波变换的基本原理出发,详细介绍了地震信号的阈值去噪原理,并根据模拟信号和实测地震信号的频谱分析,讨论了如何选择小波基及去噪过程中的阈值取值问题。从小波分解理论知道,利用多尺度分解方式对地震资料进行分析处理,相当于对实测地震资料进行不同尺度的细化分析,由于对不同地区、不同资料的精度要求不同,我们只要使用不同的尺度进行小波变换处理,就可以得到去除原信号的细部巨变(噪声干扰)特征的信号。同时,我们对小波变换处理后重构的地震信号与原信号进行了对比分析,误差结果分析表明该方法切实可行。我们还利用MATLAB语言及其小波工具箱,实现了对地震资料的去噪处理。

Application of wavelet analysis in seismic data denoising

The method of wavelet transform is widely used in the signal processing and it is a useful method to apply multi-scale wavelet transform method to wipe off the noise from the seismic signals. In the paper, the basic principle of the wavelet transform and the de-value wiping off the noise from the seismic signals are introduced in details. Then according to the spectrum analysis of the analog signal and actual seismic signals ,the selection of the wavelet base and threshold in denoising are discussed. To start from the wavelet decomposition, the multi-scale decomposition is applied to analyze the seismic data. The processing results with wavelet transform are compared with the original data as well and error analyzing shows that the method of wavelet transform is useful for the denoising of the seismic signal. Based on the Matlab language and its toolbox, the denoising to seismic data is fulfilled.