We apply Gramian constraints for the joint inversion of airborne gravity gradiometry and magnetic data. The method does not require any a priori knowledge about the types of relationships between the different model parameters, but instead determines the form of these relationships in the process of the inversion. The Gramian constraints make it possible to consider both linear and nonlinear relationships between the different physical parameters of a geological model. As an illustration, we consider in this paper polynomial relationships between different model parameters. The case study includes joint inversion of airborne gravity gradiometer (AGG) and magnetic data collected by Fugro Airborne Surveys in the area of McFaulds Lake located in northwestern Ontario. This case study demonstrates how joint inversion may enhance the produced subsurface images of a deposit.
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