A new inversion procedure for spectral analysis of surface waves (sasw) using a genetic algorithm (ga) is presented. The inversion process proposed in this study starts by running a forward solution for the Rayleigh dispersion equation, with sets of random inputs, to find the theoretical phase velocities. Then, it continues by finding new and better sets of inputs through processes that mimic natural mating, selection, and mutation in each generation. The goal of the ga is to find the best match between the theoretical and the experimental dispersion curves. Therefore, with each new generation there is a better agreement between the calculated output theoretical dispersion curve and the input experimental dispersion curve. To start the procedure, two options are available, either requesting the ga-based optimization process to obtain shear-wave velocities and thicknesses for each layer, or providing the thicknesses and requesting the optimization process to obtain the best set of shear-wave velocities. The ga part of the procedure is fast, stable, and accurate, with several advantages compared to the traditional methods. The strength and accuracy of the proposed procedure are presented through two example problems. We show that (1) the inversion process using a ga results in a good agreement between the theoretical and experimental dispersion curves, and (2) the shear-wave velocity profiles obtained from the approach presented in this study and a downhole seismic survey show a good level of agreement.

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