Automated, Efficient Detection and Location of Local and Regional Seismic Events Using Irregular Networks and Arrays

Abstract

We present results from the adaptation and application of the AELUMA method to data from single stations and arrays in the auxiliary and primary International Monitoring System (IMS) seismic networks. The report describes the code development phase which used data collected by stations in North America largely from the Transportable Array. Many subsets of the network were used to test code performance on networks that approach the sparsity of the IMS. The code was then applied to a month of data collected by IMS seismic stations in Europe, Northern Africa and Asia. Throughout this project we gauged performance of the code using ground-truthed events, such as a large mine blast in Utah, and, mainly, seismic catalogs produced by United States Geological Survey's National Earthquake Information Center (USGS-NEIC). Principal issues in the application of the method to the IMS were 1) the particularly large distances between single stations and 2) the existence of dense arrays co-mingled with the single stations. While the code is fully operational, our tests indicate it detects fewer than anticipated events. Possible key remedies include 1) focusing on either P or S detections in the event location stage, and 2) finding a better event association method.

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Document Details

Document Type
Technical Report
Publication Date
Feb 28, 2021
Accession Number
AD1145723

Entities

People

  • Catherine D. De Groot-hedlin
  • Michael A. Hedlin

Organizations

  • University of California, San Diego

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Cross Correlation
  • Data Processing
  • Databases
  • Detection
  • Detectors
  • Earthquakes
  • Frequency Bands
  • Geographic Regions
  • Grids
  • Information Science
  • North America
  • Seismic Arrays
  • Signal Detection
  • Signal Processing
  • Surface Waves
  • United States

Readers

  • Computational Modeling and Simulation
  • Seismology