Abstract

Migrationbased traveltime MBTT formulation provides algorithms for automatically determining background velocities from fullwaveform surface seismic reflection data using local optimization methods. In particular, it addresses the difficulty of the nonconvexity of the leastsquares data misfit function. The method consists of parameterizing the reflectivity in the time domain through a migration step and providing a multiscale representation for the smooth background velocity. We present an implementation of the MBTT approach for a 2-D finitedifference FD fullwave acoustic model. Numerical analysis on a 2-D synthetic example shows the ability of the method to find much more reliable estimates of both long and short wavelengths of the velocity than the classical leastsquares approach, even when starting from very poor initial guesses. This enlargement of the domain of attraction for the global minima of the leastsquares misfit has a price: each evaluation of the new objective function requires, besides the usual FD fullwave forward modeling, an additional fullwave prestack migration. Hence, the FD implementation of the MBTT approach presented in this paper is expected to provide a useful tool for the inversion of data sets of moderate size.