Depth velocity macro-model building is an essential step of the seismic imaging workflow. Indeed, obtaining acceptable results through migration or full waveform inversion is highly dependent on the initial background velocity model. Two decades ago, stereotomography was proposed as an alternative to more conventional methods like traveltime tomography, the first relying on semi-automatic picking of locally coherent events while the latter on interpretive picking of laterally continuous events. The flexibility of stereotomography paved the way for many developments that have shown the efficiency of the method in different contexts whilst emphasizing on the importance of the dual information (slopes and traveltimes). Recent formulations of stereotomography opted for reduced data and model spaces compared to the classical approach. We propose a new parsimonious formulation that offers the chance to restrain the problem to minimizing the residual of a single data class being a slope, in search of a sole parameter being the subsurface velocity. We introduce this formulation in the framework of the slope tomography based on eikonal solvers and the adjoint-state method. We firstly benchmark our method on the complex Marmousi model and then validate it through time domain full waveform inversion.


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