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In this paper, we present a practical algorithm based on sparsityregularization to effectively solve nonlinear dynamic inverse problems that areencountered in subsurface model calibration. We use an iteratively reweightedalgorithm that is widely used to solve linear inverse problems with sparsityconstraint known as compressed sensing to estimate permeability fields fromnonlinear dynamic flow data.

An Iteratively Reweighted Algorithm for Sparse Reconstruction of Subsurface Flow Properties from Nonlinear Dynamic Data