Iterative modelling, migration and inversion (IMMI) aims to incorporate standard processing techniques into the process of full waveform inversion (FWI). IMMI proposes the use of any depth migration method to obtain the gradient, while FWI uses a two-way wave migration, commonly reverse time migration (RTM). IMMI uses well calibration to scale the gradient, instead of applying a line search to ﬁnd the scalar or an approximation of the inverse Hessian matrix. We used a phase shift plus interpolation (PSPI) migration with a deconvolution imaging condition that works as a gain correction. We show the suitability of estimating the subsurface velocity model by applying IMMI’s approach using synthetic examples with increasingly geological complexity. We found consistently low errors in the well calibration location, even in the most complex settings. This suggests that the gradient obtained by applying PSPI migration points to the correct direction to minimize the objective function, and that well calibration provides an optimal scale. This is promising in the context of reservoir characterization, where we may have many control wells. We found that IMMI satisfactorily performs in the presence of moderate lateral velocity changes. The results, for the scenario of strong lateral velocity changes, indicate that well calibration is a worthy option providing that the well is representative of the geology in the zone of interest.
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