We present a method to reduce the computational cost of image-domain wavefield tomography. Instead of using the originally recorded data for velocity estimation, the proposed method simulates a new data set obtained using Born modeling or demigration based on the initial image and gathers. The modeling can be performed in a target-oriented fashion, and it can use arbitrary types of source functions and acquisition geometries. Hence the size of the new data set can be substantially smaller than the original one. We demonstrate with numerical examples that the new data set correctly preserves velocity information useful for velocity estimation, and that it generates wavefield-tomography gradient similar to that obtained using the original data set. We apply the proposed method to a modified version of the Sigsbee2A model, where two square anomalies below the salt have been successfully recovered in a target-oriented fashion at much lower computational cost.

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