oa Two-Stage Multi-Task U-Network VSP Wavefield Separation

In this paper, we address the limitations of the popular iterative vertical seismic profiling (VSP) wavefield separation method, which may not achieve high-precision results due to factors like the first break, time-variant wavelet, and strata dip angle. To overcome these challenges, we propose a novel two-stage multi-task U-Network VSP wavefield separation method, leveraging the iterative VSP wavefield separation method, U-Network, and multi-task deep learning. The two-stage multi-task U- Network can effectively extract high-precision downgoing, upgoing, and residual wavefields. Additionally, we introduce synthetic VSP training data automatic generation to facilitate the creation of diverse training datasets. Experimental results using synthetic and actual VSP data demonstrate the efficacy and potential of our proposed method for achieving high-precision VSP wavefield separation.