Surface-wave relocation of remote moderate-to-large magnitude earthquakes along the Southwest Indian Ridge

Earthquake locations are essential parameters used in seismology for investigations of earthquake processes, tectonics and subsurface imaging. The parameters associated with an earthquake location provide seismologists information about its rupture processes, faulting, and interaction with the surrounding environment. Throughout the history of earthquake location, seismologists have constrained the location of an earthquake reasonably well using arrival-time measurements. Though there exist many similar waveform features, earthquakes and their characteristics are not uniform, and under the right conditions, the available data and methods used to constrain an earthquake location can significantly influence the degree of location uncertainty. Existing earthquake locations for remote, but important tectonic regions such as mid-ocean ridges (MOR), are less well constrained because of the lack of seismic stations nearby. In remote MOR environment’s location uncertainties have been reduced using full surface-waveform observations in earthquake location analyses. Surface waves generally have a better signal to noise ratio for shallow, moderate-to-large events observed at longer distances. Previous work has shown that relative surface-wave time shifts, used for relative event locations, can be measured to a precision of 1-2 seconds, suitable enough to substantially improve the relative earthquake locations in remote regions such as MORs. We use surface-wave relative time shifts to estimate relative locations for moderate-to-large earthquake events along the Southwest Indian Ridge from 1990-2021. We employ a machine learning tool to assign quality ratings to the waveform data to speed the analysis and use the results to explore processes driving slow and ultra-slow spreading ridges.

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Work Title Surface-wave relocation of remote moderate-to-large magnitude earthquakes along the Southwest Indian Ridge
Access
Open Access
Creators
  1. Chanel Deane
  2. Charles Ammon
  3. Chengping Chai
License In Copyright (Rights Reserved)
Work Type Poster
Publication Date December 2021
Source
  1. Presented at AGU Fall Meeting Online 13-17 December, 2021
Deposited August 31, 2022

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  • Created
  • Updated
  • Added Creator Chanel Deane
  • Added Deane_AGU_2021.pdf
  • Updated Description, License Show Changes
    Description
    • Earthquake locations are essential parameters used in seismology for investigations of earthquake processes, tectonics and subsurface imaging. The parameters associated with an earthquake location provide seismologists information about its rupture processes, faulting, and interaction with the surrounding environment. Throughout the history of earthquake location, seismologists have constrained the location of an earthquake reasonably well using arrival-time measurements. Though there exist many similar waveform features, earthquakes and their characteristics are not uniform, and under the right conditions, the available data and methods used to constrain an earthquake location can significantly influence the degree of location uncertainty. Existing earthquake locations for remote, but important tectonic regions such as mid-ocean ridges (MOR), are less well constrained because of the lack of seismic stations nearby. In remote MOR environment’s location uncertainties have been reduced using full surface-waveform observations in earthquake location analyses. Surface waves generally have a better signal to noise ratio for shallow, moderate-to-large events observed at longer distances. Previous work has shown that relative surface-wave time shifts, used for relative event locations, can be measured to a precision of 1-2 seconds, suitable enough to substantially improve the relative earthquake locations in remote regions such as MORs. We use surface-wave relative time shifts to estimate relative locations for moderate-to-large earthquake events along the Southwest Indian Ridge from 1990-2021. We employ a machine learning tool to assign quality ratings to the waveform data to speed the analysis and use the results to explore processes driving slow and ultra-slow spreading ridges.
    License
    • https://rightsstatements.org/page/InC/1.0/
  • Published
  • Updated Source Show Changes
    Source
    • Presented at AGU Fall Meeting Online 13-17 December, 2021
  • Added Creator Charles Ammon
  • Added Creator Chengping Chai