Migration-based traveltime (MBTT) formulation provides algorithms for autom
atically determining background velocities from full-waveform surface seism
ic reflection data using local optimization methods. In particular, it addr
esses the difficulty of the nonconvexity of the least-squares data misfit f
unction. 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 MBT
T approach for a 2-D finite-difference (FD) full-wave acoustic model. Numer
ical 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 th
e velocity than the classical least-squares approach, even when starting fr
om very poor initial guesses. This enlargement of the domain of attraction
for the global minima of the least-squares misfit has a price: each evaluat
ion of the new objective function requires, besides the usual FD full-wave
forward modeling, an additional full-wave 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.