MEU Convolutional Neural Network and Random Noise Suppression of Seismic Data

Abstract

In allusion to the strong interference problem of random noise in seismic exploration, this paper proposed a Multiscale enhancement U-Net (MEU-Net) for the first time. First, the network carries out multiple convolution and pooling on the data in the backbone feature extraction network, then conducts channel addition, convolution and upsampling in the enhancement feature extraction network for extracting and restoring data information, finally, further improve the denoising effect through the dilated convolution, residual module and attention mechanism in the multi-scale enhancement module. The actual data application shows that the method in this paper can achieve good denoising effect under noise with different intensities, and can be widely used in data denoising processing.