A land VSP dataset acquired in a walkaway configuration was pre-processed for FWI purposes. Two different deconvolution approaches were studied. First, a deterministic deconvolution was applied to remove source-related effects. Even though this process partially accounts for changes in the wavelet with depth, a single operator is used for all the events recorded on a given trace. For this reason, we also applied a Gabor deconvolution to more completely account for non-stationarity in the source signature. The elastic FWI performed on the data deconvolved with deterministic operators converged toward a solution that was closer to the well log data. The FWI results using the data without deconvolution and the Gabor-deconvolved data did not converge toward a reasonable solution. A closer examination revealed that the deterministic deconvolution attenuated most of the multiples energy present in the data. This resulted in a dataset that is easier to explain by an initial smooth velocity model. Also, the deterministic deconvolution resurfaced some downgoing S-wave events that were not evident before. Providing data with less complexity and enhancing critical events resulted in a more robust initialization of the inversion problem.


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