This work presents a traveltime inversion method that uses parametric functions to represent 2-D anomaly structures. These functions are described by a small set of unknown parameters which in turn are obtained after solving a highly nonlinear optimization problem via simulated annealing (SA). The procedure favors neither smooth nor high contrasting anomalies and keeps the number of unknowns very small so as to make the problem tractable using SA. Yet the strategy allows one to accommodate a large class of velocity models. Results indicate that this new approach typically yields better images than a standard linearized inversion based on a cell parameterization scheme.

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