Abstract
We extend the cross-gradients philosophy for joint inversion to three-dimensional environments and developed a solution procedure based on a statistical formulation and singular value decomposition. We apply the proposed solution to the joint 3D inversion of gravity and magnetic data where we gauge the advantages of this new formulation on comparative experiments. We found that, compared to the separate inversion of gravity and magnetic data, the ambiguities of each data set are reduced by obtaining models that enhance the structural similarities.
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