T288 Challenges in Tectonics: Fault Zone Behavior through Time, from Earth’s Surface to the Upper Mantle (Posters)
Tuesday, 24 October 2017
9:00 AM - 6:30 PM
Halls 4EF
USING MAXIMUM-LIKELIHOOD ESTIMATES AND BAYESIAN STATISTICS TO STUDY SHEAR ZONES AND RIDGE-TRANSFORM SYSTEMS
Paper number: T288-9
Program: Technical Sessions
Time: 9:00 AM – 6:30 PM
Authors
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Joshua R. DavisCarleton College, Northfield, MN
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Sarah TitusCarleton College, Northfield, MN
Abstract
We describe a statistically rigorous method that integrates numerical models and field data. The method relies on our ability to write down mathematical expressions for many different types of data. Following the classic dynamic modeling method, we choose a set of model assumptions and parameters, which gives us an approximation of the velocity field. By numerically integrating this velocity field, we are able to make predictions of structural data, which can then be compared to real field observations to build a likelihood function. Then, through maximum likelihood estimation and Bayesian Markov chain Monte Carlo simulation, we can deduce the values of the deformation parameters from the data.
In a series of numerical experiments, we have tested the method on an idealized transpressional shear zone. In some experiments, the velocity field is known analytically; in others, it is known only at discrete points in the domain, simulating output from a finite element method. Then, using a dynamic model of a ridge-transform intersection, we have applied the method to field data from a fossil ridge-transform system in the Troodos ophiolite in Cyprus.
Geological Society of America Abstracts with Programs. Vol. 49, No. 6
doi: 10.1130/abs/2017AM-299714
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