Inverse problems in mantle convection : models, algorithms, and applications
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Mantle convection is the principal control on the thermal and geological evolution of the earth, including the motion of the tectonic plates, which in turn influences earthquakes, tsunamis, and volcanic eruptions. This system is governed by the equations for balance of mass, momentum, and energy for a viscous incompressible non-Newtonian fluid. Taking present-day temperatures as given, the time dependence can be neglected, eliminating the energy equation. In this case, the physics of the mantle are modeled by the Stokes equation with nonlinear rheology (the so-called forward problem). This dissertation focuses on solving the mantle convection inverse problem governed by the nonlinear Stokes forward problem with full nonlinear rheology, with an infinite-dimensional adjoint-based inversion method. The need for inverse methods in the study of mantle convection stems from the fact that the constitutive parameters are subject to uncertainty. Inversion for nonlinear rheology parameters presents considerable difficulties, which are explored in this dissertation. A spectral analysis of the Hessian operator is performed to investigate the ill-posedness of the inverse problem. The general form of the numerical eigenvalues is found to agree with that of the theoretically-derived ones (based on a model 1D Stokes problem), both of which collapse rapidly to zero, suggesting a high degree of ill-posedness. This motivates the use in this thesis of regularizations that are of Tikhonov type (favoring smooth viscosity) and total variation type (favoring piecewise-smooth viscosity). In addition, the eigenfunctions of the Hessian indicate that increasingly smaller length scales of viscosity are increasingly less observable, and that resolution decays with depth. The wide range of spatial scales of interest (varying from 1 km scale associated with plate boundaries to 10⁴ km global scales) prompts the use of adaptive mesh refinement in a parallel framework. The results show that both higher levels of nonlinearity and larger orders of magnitude of variation in the viscosity cause the inverse problem to be more ill-conditioned, increasing the difficulty of solving the inverse problem. Despite the severe ill-posedness of the inverse problem, stemming from the small number of observations compared to large number of degrees of freedom of the viscosity parameters, with the correct regularization weight and the right type of regularization, it is possible to reasonably infer information about the viscosity of the mantle, particularly in shallow regions. A number of 2D and 3D inversions are shown to demonstrate these capabilities.