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Comparative numerical analysis reveals superior accuracy for smooth least-squares inversion of Rayleigh wave dispersion curves, highlighting optimal strategies for subsurface seismic modeling.
This study examines the performance of different inversion techniques applied on Rayleigh surface wave dispersion curves. The kriSIS algorithms implement the Quasi‐Newton method, the L1 norm minimization, smoothness, damping and minimum gradient constraints and their combinations, as well as weighted inversion. Furthermore, any a priori geophysical or/and geotechnical information can be taken into account during the inversion. The proposed methodology is applied on two synthetic dispersion curves as well as two synthetic seismic records. Eight inversion parameters were tested per examined model resulting in 7680 tests. Three of them were tested on real data. The main outcome of this comparative study indicates that, for the tested models and real data, the Least Squares (L2 norm) inversion, using smoothness constraint and calculating the Jacobian matrix from analytical relationships or arithmetic differentiation, leads to the most reliable and accurate inversion results.
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Kritikakis et al. (2013) studied this question.
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