基于SVD的叠后地震资料随机噪声分离方法

Method on random noise separation from poststack seismic data based on SVD

笔者提出基于SVD的叠后地震资料随机噪声分离方法,在地震剖面的同相轴水平或接近水平时可以有效地分离出地震剖面中的随机噪声,提高地震剖面的分辨率。为了说明SVD随机噪声分离方法的有效性和高效性,建立模型试验,在合成地震记录中加入随机噪声,之后进行实际地震资料处理,分别用SVD方法和基于小波变换的分层阈值方法对加入随机噪声的合成记录和加入随机噪声的实际资料进行随机噪声分离处理。对比发现,SVD随机噪声分离方法相比于基于小波变换的分层阈值方法更加有效且高效。

The authors present a new method of random noise separation from poststack seismic data based on SVD. If the events of seismic profile are horizontal or closely horizontal,this method can separate the random noise from the seismic data validly and greatly improve the resolution of the seismic profile. In order to demonstrate the validity and high efficiency of de-noising method based on SVD,the authors set up model experiments firstly,then add random noise into the synthetic seismic data and field data. The noisy synthetic seismic data and field data with SVD method and wavelet threshold de-noising method have been processed respectively. The results show that compared with wavelet threshold de-noising method,SVD method can separate the random noise from the seismic data more validly and efficiently.