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P- and S-wave velocity estimation by ensemble Kalman inversion of dispersion data for strong motion stations in California

Bas, Elif Ecem and Seylabi, Elnaz and Yong, Alan and Tehrani, Hesam and Asimaki, Domniki (2022) P- and S-wave velocity estimation by ensemble Kalman inversion of dispersion data for strong motion stations in California. Geophysical Journal International, 231 (1). pp. 536-551. ISSN 0956-540X. doi:10.1093/gji/ggac201. https://resolver.caltech.edu/CaltechAUTHORS:20220804-250008000

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Abstract

This study uses an ensemble Kalman method for near-surface seismic site characterization of 154 network earthquake monitoring stations in California to improve the resolution of S-wave velocity (V_S) and P-wave velocity (V_P) profiles—up to the resolution depth—coupled with better quantification of uncertainties compared to previous site characterization studies at this network. These stations were part of the Yong et al. site characterization project, with selected stations based on future recordings of ground motions that are expected to exceed 10 per cent peak ground acceleration in 50 yr. To estimate V_S and V_P from experimental dispersion data, Yong et al. investigated these stations using linearized (local search and iteration) routines, and Yong et al. later studied a subset of these stations using nonlinear (global search and optimization) routines. In both studies, the selection of model parameters—that is, discretization of the V_S and V_P profiles with only five fixed thickness layers—was mainly based on trial and error. In contrast, this paper uses an approximate Bayesian method to assimilate experimental dispersion data and sequentially update an ensemble of particle estimates that span the V_S and V_P parameter spaces. Doing so, we systematically determine the most probable profiles conditioned on the experimental dispersion data, the introduced noise levels, and a priori knowledge in the form of physical constraints. We consider two configurations to discretize the soil depth from the surface to half of the maximum discernible wavelength obtained from the experimental dispersion data, namely refined and coarse models, and two initial models for each configuration to study solution multiplicity. Our results suggest that using the refined model for the top surface layers improves the resolution of near-surface site characteristics and the model’s success rate in capturing dispersion data at high frequencies. All models result in similar VS but distinct VP profiles, with increasing uncertainty at deeper layers, suggesting that the fundamental mode of Rayleigh wave dispersion data is not adequate to constrain the P-wave velocity profile and the S-wave velocity close to the resolution depth.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1093/gji/ggac201DOIArticle
https://github.com/elnaz-esmaeilzadeh/GJI_dataset_2022Related ItemTabulated VS and VP profiles
ORCID:
AuthorORCID
Seylabi, Elnaz0000-0003-0718-372X
Yong, Alan0000-0003-1807-5847
Asimaki, Domniki0000-0002-3008-8088
Additional Information:© The Author(s) 2022. 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/open_access/funder_policies/chorus/standard_publication_model). Revision received: 15 August 2021. Received: 23 May 2022. Accepted: 25 May 2022. Published: 30 May 2022. Corrected and typeset: 04 July 2022. This research was supported by the U.S. Geological Survey (USGS) under award numbers G20AP00011 and G20AP00012. We are grateful for the financial support that has made this research possible. We also thank Dr David Teague for helping the second and fourth authors set up the ‘dinver’-based inversion at CI.RSB site. Elizabeth Brown and Jose Gomez produced the map in Fig. 1. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. DATA AVAILABILITY. The data underlying this article will be shared upon reasonable request to the corresponding author (Elnaz Seylabi, elnaze@unr.edu). Tabulated VS and VP profiles are available at the corresponding author’s Github account (https://github.com/elnaz-esmaeilzadeh/GJI_dataset_2022).
Group:Seismological Laboratory
Funders:
Funding AgencyGrant Number
USGSG20AP00011
USGSG20AP00012
Subject Keywords:Inverse theory, Tomography, Earthquake hazards, Site effects, Surface waves and free oscillations
Issue or Number:1
DOI:10.1093/gji/ggac201
Record Number:CaltechAUTHORS:20220804-250008000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220804-250008000
Official Citation:Elif Ecem Bas, Elnaz Seylabi, Alan Yong, Hesam Tehrani, Domniki Asimaki, P- and S-wave velocity estimation by ensemble Kalman inversion of dispersion data for strong motion stations in California, Geophysical Journal International, Volume 231, Issue 1, October 2022, Pages 536–551, https://doi.org/10.1093/gji/ggac201
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:116121
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:15 Aug 2022 14:56
Last Modified:15 Aug 2022 14:56

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