Generating 1D depth profile of shear-wave velocity from ambient noise cross-correlation: application to Jakarta array

Abstract

In the past decade, cross-correlations of ambient seismic noise have been exploited in various applications to model the shallow-to-deep structure of Earth’s interior through tomographic inversions. The stack of cross-correlations between a 2-station pair represents empirical Green’s function and comprises the information of the subsurface structure between those stations. In practice, noise correlation function (NCF) is analyzed to reconstruct surface wave group or phase velocity dispersion; then, the dispersion data is used to model shear-wave velocity (Vs). This study presents a case for temporary seismic networks deployed in the Jakarta Basin; we applied a two-step routine to obtain a representative 1D Vs profile beneath an array. First, we extracted our array’s average phase velocity dispersion based on the relationship between NCF’s spectra and the Bessel function. Then, we invert for the 1D depth profile of Vs using a transdimensional Bayesian inversion to allow for exploring a number of layers in parameterizations. We successfully generate a 1D Vs profile up to 5 km depth reflecting the regional stratigraphy of the Jakarta Basin. In general, a sedimentary basin fill covers the area reaching a depth of 650 m. We suggest that this simple routine can be undertaken for other ambient noise cross-correlation cases; such a 1D depth profile would be beneficial to be used as a reference model.