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Weis, John M.

University of British Columbia

Geophysical magnetic surveys utilize the remote signals generated by magnetic properties of earth materials to facilitate the imaging of the subsurface. These magnetic properties can generally be characterized by their magnetic susceptibility and remanent magnetization. Magnetic susceptibility describes how the material becomes magnetized in response to an applied field. These induced magnetization effects are complicated by self-demagnetization at high values of susceptibility, and many algorithms to model and recover susceptibility distributions do not account for these complications. Remanent magnetization describes an effectively permanent magnetization that is unaffected by applied fields. While modeling the effects of remanent magnetization has become commonplace, recovering subsurface distributions of magnetization continues to be challenging. In this thesis, I introduce a general finite-volume framework for forward modeling and inversion of magnetic data using the differential form of Maxwell’s equations. The framework is capable of simulating the effects of induced magnetization when highly susceptible materials are present while simultaneously including the response of remanently magnetized materials. I then focus on improving methods for inverting magnetic data to recover subsurface distributions of magnetization and high susceptibility separately. I introduce improvements to magnetic vector inversion in Cartesian coordinates to facilitate the recovery of uniformly magnetized and compact targets. I also show that the developed partial differential equation based formulation drastically improves speed and storage requirements for very large scale problems as compared to commonly used integral methods. To recover distributions of high susceptibility, I introduce an inversion methodology that utilizes sparse regularization with bound constraints. I also introduce a hybrid-parametric sparse inversion approach for targets with more extreme geometries and very high susceptibilities. I validate the improvements to magnetic vector inversion and inversion for highly susceptible material using data sets collected in the Mount Isa Inlier located in Queensland, Australia.

Text

2024-07-06

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/88583

Geophysics

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/