The quality of the subsurface images obtained using VSP data strongly depends on the velocity model used for migration. The velocity model derived from surface seismic is oftenly not accurate enough for VSP imaging and there is a need for it's improvement. We propose the method for updating of velocities using VSP data. The main idea is to use the images of the subsurface obtained using different types of waves: primary reflections and surface-related multiples. If the background velocity is correct, then these images will be similar, and they will not coincide, if the velocity model is erroneous. As a measure of similarity, we define the functional based on cross-correlation of these images. This velocity model is correct and it can be used in optimization procedure to uptade the model parameters. We studied the dependency of the functional from acquisition and frequency content of the signal. Also, we derived the gradient of the functional using adjoint-state method and demonstrated the possibility of velocity updating for simple synthetic model.


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