Inverse Analysis of Weak and Strong Motion Downhole Array Data: A Hybrid Optimization Algorithm

Abstract

A seismic waveform inversion algorithm is proposed for the estimation of elastic soil properties using low amplitude, downhole array recordings. Based on a global optimization scheme in the wavelet domain, complemented by a local least-square fit operator in the frequency domain, the hybrid scheme can efficiently identify the optimal solution vicinity in the stochastic search space, whereas the best fit model detection is substantially accelerated through the local deterministic inversion. The applicability of the algorithm is next illustrated using downhole array data obtained by the Kik-net strong motion network during the Mw7.0 Sanriku-Minami earthquake. Inversion of low-amplitude waveforms is first employed for the estimation of low-strain dynamic soil properties at five stations. Successively, inversion of the mainshock empirical site response is employed to extract the equivalent linear dynamic soil properties at the same locations. The inversion algorithm is shown to provide robust estimates of the linear and equivalent linear impedance profiles, while the attenuation structures are strongly affected by scattering effects in the near-surficial heterogeneous layers.