Joint multinary inversion of gravity and magnetic data using Gramian constraints

Abstract

This paper proposes a novel approach to the joint inversion of gravity and magnetic data based on multinary transformation of the model parameters and Gramian constraints. The concept of multinary transformation is a generalization of the binary density inversion for models described by any number of discrete model parameters, while the Gramian constraint enforces the linear relationships between the different model parameters and their attributes or transforms. By combining these two concepts, the joint multinary inversion using Gramian constraints not onlymakes it possible to explicitly exploit the sharp contrasts of the density and magnetic susceptibility between the host media and anomalous targets in the inversion of gravity and magnetic data, but also provides uniform spatial boundaries of the anomalous targets in the distributions of density and magnetic susceptibility. The novel joint multinary inversion algorithm is demonstrated to be effective in determining the shapes, locations and physical properties of the anomalous targets. We show that this method can be effectively applied to the joint inversion of the full tensor gravity gradiometry data and the total magnetic intensity data, computer simulated for 3-D synthetic models using ternary model transformation. We also tested this joint inversion algorithm in the area of the McFaulds Lake in northwestern Ontario, Canada, and the joint inversion results provide a reasonable geological model with high resolution for the exploration of magmatic chromite deposits.