| Summary: | dissertation One of the major challenges in the interpretation of geophysical data remains the ability to jointly invert multiple geophysical datasets for self-consistent three-dimensional (3D) earth models of different physical properties. This dissertation develops a method of joint inversion of potential field and electromagnetic data using Gramian constraints. A model weighting technique was introduced to guarantee a stable and converging joint inversion process. The developed joint inversion algorithm was successfully tested in a number of model studies, where the Gramian constraints make it possible to consider both linear and nonlinear relationships between the different physical properties. This dissertation also develops a novel method of inversion of magnetic data for the magnetization vector, when remanent magnetization is present. The method is based on a new magnetic forward modeling algorithm, which uses triangular prisms of arbitrary shape in order to achieve a more accurate approximation of the topography. The inversion also includes Gramian constraints in order to obtain a robust solution of otherwise ill-posed magnetic inverse problems. Another development in this dissertation is the localized Gramian constraints, which allows one to recover multiple lithologic relationships between the different physical properties. The case study of the joint inversion of airborne magnetic and electromagnetic data in the Lac de Gras area of the Northwest Territories of Canada demonstrated how joint inversion using the localized Gramian constraints can enhance subsurface imaging of mineral targets.
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