On the application of Particle Swarm Optimization strategies on Scholte-wave inversion

We investigate different aspects concerning the application of swarm intelligence optimization to the inversion of Scholte-wave phase-slowness frequency (p—f) spectra with respect to shear wave velocity structure. Besides human influence due to the dependence on a priori information for starting models and interpretation of p—f spectra as well as noise, the model resolution of the inversion problem is strongly influenced by the multimodality of the misfit function. We thus tested the efficiency of global, stochastic optimization approaches with focus on swarm intelligence methods that can explore the multiple minima of the misfit function. A comparison among different PSO schemes by applying them to synthetic Scholte-wave spectra led to a hybrid of Particle Swarm Optimization and Downhill Simplex providing the best resolution of inverted shear wave velocity depth models. The results showed a very low spread of best fitting solutions of 7 per cent in shear wave velocity and an average of 9 per cent for noisy synthetic data and a very good fit to the true synthetic model used for computation of the input data. To classify this method we also compared the probability of finding a good fit in synthetic spectra inversion with that of Evolutionary Algorithm, Simulated Annealing, Neighbourhood Algorithm and Artificial Bee Colony algorithm. Again the hybrid optimization scheme showed its predominance. The usage of stochastic algorithms furthermore allowed a new way of misfit definition in terms of dispersion curve slowness residuals making the inversion scheme independent on Scholte-wave mode identification and allowing joint inversion of fundamental mode and higher mode information. Finally we used the hybrid optimization scheme and the misfit calculation for the inversion of 2-D shear wave velocity profiles from two locations in the North- and Baltic Sea. The models show acceptable resolution and a very good structural correlation to high resolution reflection seismic data.