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Accounting for uncertain fault geometry in earthquake source inversions – I: theory and simplified application

Ragon, Théa and Sladen, Anthony and Simons, Mark (2018) Accounting for uncertain fault geometry in earthquake source inversions – I: theory and simplified application. Geophysical Journal International, 214 (2). pp. 1174-1190. ISSN 0956-540X. http://resolver.caltech.edu/CaltechAUTHORS:20181108-132919094

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Abstract

The ill-posed nature of earthquake source estimation derives from several factors including the quality and quantity of available observations and the fidelity of our forward theory. Observational errors are usually accounted for in the inversion process. Epistemic errors, which stem from our simplified description of the forward problem, are rarely dealt with despite their potential to bias the estimate of a source model. In this study, we explore the impact of uncertainties related to the choice of a fault geometry in source inversion problems. The geometry of a fault structure is generally reduced to a set of parameters, such as position, strike and dip, for one or a few planar fault segments. While some of these parameters can be solved for, more often they are fixed to an uncertain value. We propose a practical framework to address this limitation by following a previously implemented method exploring the impact of uncertainties on the elastic properties of our models. We develop a sensitivity analysis to small perturbations of fault dip and position. The uncertainties of our fixed fault geometry are included in the inverse problem under the formulation of the misfit covariance matrix that combines both prediction and observation uncertainties. We validate this approach with the simplified case of a fault that extends infinitely along strike, using both Bayesian and optimization formulations of a static slip inversion. If epistemic errors are ignored, predictions are overconfident in the data and slip parameters are not reliably estimated. In contrast, inclusion of uncertainties in fault geometry allows us to infer a robust posterior slip model. Epistemic uncertainties can be many orders of magnitude larger than observational errors for great earthquakes (Mw > 8). Not accounting for uncertainties in fault geometry may partly explain observed shallow slip deficits for continental earthquakes. Similarly, ignoring the impact of epistemic errors can also bias estimates of near-surface slip and predictions of tsunamis induced by megathrust earthquakes.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1093/gji/ggy187DOIArticle
ORCID:
AuthorORCID
Simons, Mark0000-0003-1412-6395
Additional Information:© 2018 The Author(s). Published by Oxford University Press on behalf of The Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices). Accepted 2018 May 10. Received 2018 February 6; in original form 2017 December 6. Published: 15 May 2018. We thank Martin Mai, František Gallovič and Kaj Johnson for their thorough and constructive reviews. We thank Quentin Bletery, Baptiste Gombert, Zacharie Duputel and Romain Jolivet for helpful discussions. The Bayesian simulations were performed on the HPC-Regional Center ROMEO (https://romeo.univ-reims.fr) of the University of Reims Champagne-Ardenne (France). We thank Michael Aivazis for his meticulous help for the installation. The Classic Slip Inversion (CSI) Python library created by Romain Jolivet was used to build inputs for the Bayesian algorithm and to perform the optimization of the inverse problem. Figures were generated with the Matplotlib Python library. This study was partly supported by the French National Research Agency (ANR) EPOST project ANR-14-CE03-0002. TR is supported by a fellowship from the French Ministry of Research and Higher Education. MS was supported by U.S. National Science Foundation grant 1447107.
Group:Seismological Laboratory
Funders:
Funding AgencyGrant Number
Agence Nationale pour la Recherche (ANR)ANR-14-CE03-0002
Ministère de l'Enseignement supérieur, de la Recherche et de l'InnovationUNSPECIFIED
NSFEAR-1447107
Subject Keywords:Inverse theory; Probability distributions; Earthquake source observations
Record Number:CaltechAUTHORS:20181108-132919094
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20181108-132919094
Official Citation:Théa Ragon, Anthony Sladen, Mark Simons; Accounting for uncertain fault geometry in earthquake source inversions – I: theory and simplified application, Geophysical Journal International, Volume 214, Issue 2, 1 August 2018, Pages 1174–1190, https://doi.org/10.1093/gji/ggy187
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90759
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:09 Nov 2018 13:01
Last Modified:09 Nov 2018 13:01

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