Rapid Earthquake Association and Location

Author:

Zhang Miao12,Ellsworth William L.1,Beroza Gregory C.1

Affiliation:

1. Department of Geophysics, Stanford University, 397 Panama Mall, Stanford, California 94305 U.S.A., mzhang18@stanford.edu, wellsworth@stanford.edu, beroza@stanford.edu

2. Now at Department of Earth Sciences, Dalhousie University, 1355 Oxford Street, Halifax, Nova Scotia B3H 4J1, Canada; miao.zhang@dal.ca.

Abstract

ABSTRACT Rapid association of seismic phases and event location are crucial for real‐time seismic monitoring. We propose a new method, named rapid earthquake association and location (REAL), for associating seismic phases and locating seismic events rapidly, simultaneously, and automatically. REAL combines the advantages of both pick‐based and waveform‐based detection and location methods. It associates arrivals of different seismic phases and locates seismic events primarily through counting the number of P and S picks and secondarily from travel‐time residuals. A group of picks are associated with a particular earthquake if there are enough picks within the theoretical travel‐time windows. The location is determined to be at the grid point with the most picks, and if multiple locations have the same maximum number of picks, the grid point among them with smallest travel‐time residuals. We refine seismic locations using a least‐squares location method (VELEST) and a high‐precision relative location method (hypoDD). REAL can be used for rapid seismic characterization due to its computational efficiency. As an example application, we apply REAL to earthquakes in the 2016 central Apennines, Italy, earthquake sequence occurring during a five‐day period in October 2016, midway in time between the two largest earthquakes. We associate and locate more than three times as many events (3341) as are in Italy's National Institute of Geophysics and Volcanology routine catalog (862). The spatial distribution of these relocated earthquakes shows a similar but more concentrated pattern relative to the cataloged events. Our study demonstrates that it is possible to characterize seismicity automatically and quickly using REAL and seismic picks.

Publisher

Seismological Society of America (SSA)

Subject

Geophysics

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