Ahybrid algorithm, combining Monte-Carlo (MC) optimization with Simultaneous Iterative Reconstructive Technique (SIRT) tomography, is used to invert the first-arrival travel times from seismic data for building velocity models. Stochastic algorithms may localize a point around the global minimum of the misfit function, but are not suitable to identify the precise solution. On the other hand, tomographic model reconstruction, based on a local linearization, will be successful only if an initial model already close to the best solution is available. To overcome these problems, in the new method a model obtained using a classical Monte-Carlo optimization is proposed as a good initial guess for starting the local search with the SIRT tomography. The performance of this two-step optimization scheme has been tested on synthetic data. After that, the first-arrival times picked from two orthogonal lines recorded at the Caldeira of S. Sebastio in theAzores Islands are used. The velocities in the region undergo lateral and vertical changes, and the new technique images successfully these variations with reduced a priori information.
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