Joint inversion of phase velocity dispersion and H/V ratio curves from seismic noise recordings using a genetic algorithm, considering higher modes

Seismic noise contains information on the local S-wave velocity structure, which can be obtained from the phase velocity dispersion curve by means of array measurements. The H/V ratio from single stations also contains information on the average S-wave velocity and the total thickness of the sedimentary cover. A joint inversion of the two data sets therefore might allow constraining the final model well. We propose a scheme that does not require a starting model because of usage of a genetic algorithm. Furthermore, we tested two suitable cost functions for our data set, using a-priori and data driven weighting. The latter one was more appropriate in our case. In addition, we consider the influence of higher modes on the data sets and use a suitable forward modeling procedure. Using real data we show that the joint inversion indeed allows for better fitting the observed data than using the dispersion curve only.