Full text loading...
The shallow subsurface structure plays a crucial role in human activities, necessitating accurate and rapid detection methods, especially in urban environments. Traditional active-source surface-wave methods, while effective for measuring shear-wave velocity, have limitations in exploration depth. Seismic interferometry (SI), which uses ambient seismic noise to estimate the Green’s function between receivers, has emerged as a valuable tool in extracting surface waves for subsurface studies. With increasing urbanization, the demand for higher spatiotemporal resolution has led to the adoption of distributed acoustic sensing (DAS), which utilizes optical fibers to detect seismic waves. DAS offers a low-cost, dense seismic data acquisition solution but faces challenges such as coupling conditions, complex noise sources, and low signal-to-noise ratios (SNR). This study focuses on improving the SNR of surface-wave signals by leveraging the spatial coherence between multiple DAS channels, enhancing the quality of virtual shot gathers (VSGs) for more effective shallow subsurface imaging.