Addressing non‐uniqueness in linearized multichannel surface wave inversion

ABSTRACT The multichannel analysis of the surface waves method is based on the inversion of observed Rayleigh‐wave phase‐velocity dispersion curves to estimate the shear‐wave velocity profile of the site under investigation. This inverse problem is nonlinear and it is often solved using ‘local’ or linearized inversion strategies. Among linearized inversion algorithms, least‐squares methods are widely used in research and prevailing in commercial software; the main drawback of this class of methods is their limited capability to explore the model parameter space. The possibility for the estimated solution to be trapped in local minima of the objective function strongly depends on the degree of nonuniqueness of the problem, which can be reduced by an adequate model parameterization and/or imposing constraints on the solution. In this article, a linearized algorithm based on inequality constraints is introduced for the inversion of observed dispersion curves; this provides a flexible way to insert a priori information as well as physical constraints into the inversion process. As linearized inversion methods are strongly dependent on the choice of the initial model and on the accuracy of partial derivative calculations, these factors are carefully reviewed. Attention is also focused on the appraisal of the inverted solution, using resolution analysis and uncertainty estimation together with a posteriori effective‐velocity modelling. Efficiency and stability of the proposed approach are demonstrated using both synthetic and real data; in the latter case, cross‐hole S‐wave velocity measurements are blind‐compared with the results of the inversion process.