Advances in Array-based Overtone Surface Wave Imaging and Its Application to Lithospheric Structure Imaging

Surface wave imaging based on ambient noise cross-correlation technology is one of the most significant advancements in geophysical imaging over the past two decades, widely applied to shear wave velocity structure imaging from near-surface to lithospheric scales. In recent years, with breakthroughs in array-based surface wave techniques, ambient noise surface wave imaging has entered a new phase of studying overtone surface waves. The inclusion of overtone surface waves effectively enhances the ability of surface wave dispersion curve inversion to constrain subsurface structures, particularly low-velocity layers in the crust and lithosphere.

However, in three-dimensional imaging, array methods typically treat the velocity structure inverted from an array as a spatially averaged result, assigning it to the centroid of the array for interpolation. This approach introduces spatial averaging effects, which, to some extent, affect the accuracy of phase velocity and horizontal spatial resolution, while the size and shape of sub-arrays may also influence the results.

To address these issues, we recently developed a framework involving multiple random Voronoi polygon partitioning and spatial phase velocity re-inversion (SPFI). By generating a large number of observations of varying sizes and shapes using random methods, and establishing mathematical relationships between horizontal spatial distributions of phase velocity and observed dispersion curves, we successfully resolved the issues of adaptive partitioning in array-based surface wave methods and improved estimation of horizontal resolution. This report primarily introduces the aforementioned new array-based multi-mode surface wave method and its recent progress in imaging continental lithospheric structures.