基于小波分析在地震信号噪声消除中的应用

在地震勘探中,随机噪声是一种频带较宽、严重影响有效波的干扰波,因此随机噪声的有效去除在地震信号处理中显得尤为重要。傅里叶变换是信号处理传统的随机噪声去除方法。它能够反映信号在整个时间域的频谱特征,但不能对非平稳信号进行分析处理。而小波分析技术可以根据局部图像的差异来调整参数,对保留图像的边缘部分和其它高频部分很有用。本文利用小波分析技术对地震信号进行去噪声处理,结果表明小波分析对噪声有较为彻底的压制,地震信号估计精度得到很大改善。

Application of a Novel Method to Removing Random Noises in Seismic Data Processing Based on Wavelet Analysis

The random noise is a kind of noise with wide frequency band in seismic data and influences the useful signal very much. It is very important to remove the random noise from the seismic data. Fast Fourier Transform （FFT） is the traditional method to remove the random noise and can analysis a signal on the whole spectrum, however, cannot analysis non-stationary sig- nal. Wavelet analysis is a novel method to improve the practical data and remove the noise and is prior to other methods. This pa- per uses the wavelet analysis to remove the random noise from the seismic data, the results show that wavelet analysis can more ef- ficiently remove the noise and improve the precision of seismic data.