Reservoir surveillance is becoming increasingly important as the need to maximize field productivity rises. An important problem is determining the subsurface flow in a reservoir. One option is to estimate the flow from a time series of geophysical imaging data. In this paper, we present a novel method that simultaneously reconstructs the distribution the flow field, which is caused by injection and extraction, from borehole seismic tomography data. The method involves discretization of the flow equations, and combining this with the geophysical monitoring experiment to form a multi-variable inverse problem. The minimizers of this optimization problem are the flow field and the initial state of the reservoir. These approximations are then used to march the initial state in time, showing the motion of fluid in the subsurface, and providing the ability to predict the spatial evolution of the flow.

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