VSP wavefields separating method based on parallel local slope scanning

Due to the detectors being distributed in the target medium, vertical seismic profile (VSP) is a seismic observation method that has the advantages of high resolution and a high signal-to-noise ratio. Separating the mixed wavefields into upgoing and downgoing waves can obtain more obvious dynamic and kinematic characteristics of seismic waves, guiding subsequent imaging and interpretation. The traditional method is mainly based on the pickup of first breaks. Flattening the global seismic data by first breaks can enhance the seismic events through techniques like median filter and singular value decomposition (SVD). However, this method relies on high-precision pickup of first breaks and is limited by zero offset. To address this limitation, we introduce an improved median filtering separation method. This method employs separations of the local dip angles into positive and negative through multi-window scanning (MWS). Due to the high accuracy and robustness of this method in 2-D VSP data, we propose to use the local dip angle of the wavefields to median filter the wavefield through positive and negative angles to obtain upgoing and downgoing waves. This method for wavefield separation is optimized by iteratively identifying the directions of the seismic data. However, this optimization comes at the cost of increased computational requirements, especially under high-precision conditions. To help alleviate this problem, we use multi-thread parallel computing technique on a multi-core central processing unit (CPU) to improve computational efficiency. Finally, we validate the proposed method by testing it on synthetic seismic data and field VSP data, respectively. The results show that this wavefield separation method has advantages in terms of accuracy and robustness compared to the median filtering method based on the first break picking.