Robust Seismic Denoising Framework: A GAN-Based Approach with Multi-Scale Feature Fusion and Signal Preservation

Seismic data acquisition is often affected by complex field conditions and equipment precision limitations, leading to the generation of multiple types of noise that reduce the accuracy of reservoir inversion and geological interpretation. Deep learning techniques have begun to be applied in seismic data denoising due to their efficient feature learning capabilities. However, the complex characteristics of seismic noise pose challenges for conventional convolutional neural networks in learning d