Direct Tomography of S-wave Structure Using Subarray Surface Wave Dispersion Data: Methodology and Validation

Surface wave imaging based on ambient noise, especially with the deployment of increasingly dense arrays (such as nodal seismometers and Distributed Acoustic Sensing), has become an effective tool for investigating subsurface velocity structures. While segmenting dense arrays into subarrays has emerged as a promising approach, traditional subarray surface wave imaging (SSWI) methods face challenges in positioning the average phase velocity dispersion data of subarrays, leading to velocity jumps and poor lateral constraints. We propose a novel subarray surface wave direct imaging (SSWDI) method that establishes a sensitivity kernel between subarray average dispersion data and subsurface parameters. Through numerical experiments and real-world applications, we demonstrate that SSWDI can reduce velocity artifacts compared to traditional methods. The method’s key advantages include inherent spatial smoothing constraints and the ability to jointly utilize multiscale subarray dispersion data, providing more reliable constraints on subsurface S-wave velocity structures from shallow to deep depths. The SSWDI method shows broad application potential in the future.