Abstract: The random noise in seismic data seriously affects the accuracy of subsequent data processing and interpretation. Therefore, an intelligent seismic random noise suppression method based on convolution neural network is proposed. Firstly, a deep nonlinear noise suppression network is designed according to the principle of convolution neural network, and then the network is trained by using the constructed high-quality random noise training set, so as to realize the automatic learning of random noise characteristics in high-dimensional space, so as to fit the nonlinear mapping relationship between noisy seismic data records and random noise, Realize automatic suppression of random noise. This method is used for noise suppression of seismic data, and compared with the commonly used filtering algorithms ( mean filtering method and median filtering method ). The experimental results show that this method has higher signal-to-noise ratio and overcomes the problems of traditional methods. An example verifies the feasibility and effectiveness of this method.

Key words: seismic data;  , convolution neural network;  , deep learning;  , random noise;  , noise suppression