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Stochastic optimization is key to efficient inversion in PDE-constrainedoptimization. Using 'simultaneous shots', or random superposition of sourceterms, works very well in simple acquisition geometries where all sources seeall receivers, but this rarely occurs in practice. We develop an approach thatinterpolates data to an ideal acquisition geometry while solving the inverseproblem using simultaneous shots. The approach is formulated as a joint inverseproblem, combining ideas from low-rank interpolation with full-waveforminversion. Results using synthetic experiments illustrate the flexibility andefficiency of the approach.

Simultaneous shot inversion for nonuniform geometries using fast data interpolation