hp-Adaptive simulation and inversion of magnetotelluric measurements
- ALVAREZ ARAMBERRI, JULEN
- David Pardo Zubiaur Director
Universitat de defensa: Universidad del País Vasco - Euskal Herriko Unibertsitatea
Fecha de defensa: 18 de de desembre de 2015
- Pilar Queralt Capdevila President/a
- Virginia Muto Foresi Secretari/ària
- Victor Péron Vocal
Tipus: Tesi
Resum
The magnetotelluric (MT) method is a passive exploration technique that aims at estimating the resistivity distribution of the Earth’s subsurface, and therefore at providing an image of it. This process is divided into two different steps. The first one consists in recording the data. In a second step, recorded measurements are analyzed by employing numerical methods. This dissertation focuses in this second task. We provide a rigorous mathematical setting in the context of the Finite Element Method (FEM) that helps to understand the MT problem and its inversion process. In order to recover a map of the subsurface based on 2D MT measurements, we employ for the first time in MTs a multigoal oriented self adaptive hp-Finite Element Method (FEM). We accurately solve both the full formulation as well as a secondary field formulation where the primary field is given by the solution of a 1D layered media. To truncate the computational domain, we design a Perfectly Matched Layer (PML) that automatically adapts to high-contrast material properties that appear within the subsurface and on the air-ground interface. For the inversion process, we develop a first step of a Dimensionally Adaptive Method (DAM) by considering the dimension of the problem as a variable in the inversion. Additionally, this dissertation supplies a rigorous numerical analysis for the forward and inverse problems. Regarding the forward modelization, we perform a frequency sensitivity analysis, we study the effect of the source, the convergence of the hp-adaptivity, or the effect of the PML in the computation of the electromagnetic fields and impedance. As far as the inversion is concerned, we study the impact of the selected variable for the inversion process, the different information that each mode provides, and the gains of the DAM approach