Left- and right-going wavefield separation of high-speed train seismic records using randomized Cadzow filtering

Summary High-speed trains can serve as highly repeatable, low-cost seismic sources for subsurface imaging and monitoring along railway corridors. In viaduct settings, however, a passing train continuously excites multiple bridge piers, causing strong superposition of left- and right-going wavefields and severe crosstalk. As a result, train-passage records, despite their high signal-to-noise ratio, cannot be directly used. To address this limitation, we propose a wavefield-separation method based on randomized Cadzow filtering. The workflow integrates Radon-based apparent-velocity estimation, time flattening, local-block random permutation, and low-rank block Hankel reconstruction to separate left- and right-going wavefields in HST seismic data. Synthetic and field examples demonstrate that, compared with traditional methods, the proposed approach more effectively suppresses backward-propagating energy and wavefield crosstalk, while recovering unidirectional wavefields with improved continuity and greater amplitude and phase stability, leading to higher-quality virtual shot gathers and clearer dispersion images.