Generalized joint inversion of multimodal geophysical data using Gramian constraints

Abstract

We introduce a new approach to the joint inversion of multimodal geophysical data using Gramian spaces of model parameters and Gramian constraints, computed as determinants of the corresponding Gram matrices of the multimodal model parameters and/or their attributes. We demonstrate that this new approach is a generalized technique that can be applied to the simultaneous joint inversion of any number and combination of geophysical datasets. Our approach includes as special cases those extant methods based on correlations and/or structural constraints of the multimodal model parameters. As an illustration of this new approach, we present a model study relevant to exploration under cover for iron oxide copper‐gold (IOCG) deposits, and demonstrate how joint inversion of gravity and magnetic data is able to recover alteration associated with IOCG mineralization.