Geophysical imaging of fluid flow in porous media

Generating reservoir models that can be used to predict the flow of fluids in porous media is a difficult process. In this talk we propose a new method that enables us to estimate the velocity flow-field without having to estimate other reservoir properties. This allows us to predict the flow, and provides an image of the subsurface structure.Our approach is based on combining the flow equations and the geophysical imaging into a single inverse problem where the unknowns are the initial state of the reservoir and the flow field. We discuss consistent discretization techniques, tailor specific regularizations, and use a modification of the variable projection method to solve the discrete optimization problem. We demonstrate our approach on a model problem that shows that our approach yields an improved flow estimate as well as improved imaging.