We introduce a passive surface wave method using seismic ambient noise obtained from dozens of receivers forming spatially unaliased two-dimensional (2D) arrays. The method delineates two- or three-dimensional (2D or 3D) S-wave velocity ( VS) models to depths of several hundreds of meters, without using any sources. Typical data acquisition uses 50 to 100 vertical-component 2 Hz geophones on the surface with 5 to 30 m receiver spacing. Cableless seismographs with GPS record 20 to 60 minutes of ambient noise. We establish a 2D grid covering the investigation area and use a common midpoint spatial autocorrelation (CMP-SPAC) method to calculate phase velocities, resulting in a dispersion curve for each grid point. The method provides dozens of dispersion curves in the investigation area. We use a one-dimensional (1D) non-linear inversion to estimate a 1D VS profile for each grid point, and then construct pseudo 2D or pseudo 3D VS models from the 1D VS profiles. Precision and accuracy of the CMP-SPAC method was tested with a numerical simulation using a 3D finite-difference method. The results of the simulation demonstrated the applicability of the method to complex velocity structures. We applied the method to an active fault investigation in China. Sixty-four cableless seismographs were deployed in an investigation area 330 × 660 m (217,800 m2) with 5 m and 30 m receiver spacings for dense and sparse grids, respectively. A 3D VS model was obtained to a depth of 150 m from CMP-SPAC analysis. The resultant 3D VS model indicates approximately 50 m of vertical displacement on a known fault.
Three-dimensional ambient noise tomography across the Taiwan Strait: The structure of a magma-poor rifted margin
