Seismic Imaging of the Southern Vienna Basin (Austria) Using Probabilistic Ambient-Noise Tomography

Abstract

Surface-wave ambient noise tomography has proven to be a cost-effective and reliable tool for imaging sedimentary basins when coupled with dense nodal seismic arrays. Here, we deployed 181 seismic nodes in two asynchronous phases across the southern Vienna Basin in spring 2024. We retrieve fundamental-mode Rayleigh and Love wave group velocity dispersion curves from seismic noise cross-correlations. We then obtained a pseudo three-dimensional (3D) $V_{S_V}$ model and a seismic radial anisotropy ($\zeta$) model of the area from a 2-step approach that employs trans-dimensional probabilistic (Bayesian) inference. The 3D $V_{S_V}$ model highlights the structure of the Neogene basin. The 3D seismic radial anisotropy reveals several patterns, which may help constrain the presence and nature of faults and geologic fabrics in the study area. Combined, these models constrain first-order features of the basin structure that will be useful for planning further geothermal exploration. In particular, this work guides future detailed, spatially targeted two-dimensional/3D seismic reflection surveys.