Publication Date

Spring 4-15-2017

Abstract

The national Earthquake Information Center (NEIC) reports an occurrence of about 13,000 earthquakes every year, spanning different values on the Richter scale from very mild (2) to "giant earthquakes'' (8 and above). Being able to study these earthquakes provides useful information for a wide range of applications in geophysics. In the present work we study the characteristics of an earthquake by performing seismic source inversion; a mathematical problem that, given some recorded data, produces a set of parameters that when used as input in a mathematical model for the earthquake generates synthetic data that closely resembles the measured data. There are two approaches to performing this source inversion: a deterministic and a probabilistic approach. We present an overview of both methods and implement them in order to perform different seismic source inversion experiments for recorded waveforms in one and two dimensions.

Degree Name

Mathematics

Level of Degree

Masters

Department Name

Mathematics & Statistics

First Committee Member (Chair)

Daniel Appelo

Second Committee Member

Mohammad Motamed

Third Committee Member

Gabriel Huerta

Language

English

Keywords

Seismic Source Inversion, Bayesian Inversion, Metropolis Hastings, Inverse Problems, Optimization

Document Type

Thesis

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