An all-in-one seismic phase picking, location, and association network for multi-task multi-station earthquake monitoring

DOI number:10.1038/s43247-023-01188-4

Affiliation of Author(s):中国科学技术大学地球和空间科学学院

Journal:Communications Earth & Environment

Place of Publication:英国

Abstract:Earthquake monitoring is vital for understanding the physics of earthquakes and assessing seismic hazards. A standard monitoring workflow includes the interrelated and interdependent tasks of phase picking, association, and location. Although deep learning methods have been successfully applied to earthquake monitoring, they mostly address the tasks separately and ignore the geographic relationships among stations. Here, we propose a graph neural network that operates directly on multi-station seismic data and achieves simultaneous phase picking, association, and location. Particularly, the in

First Author:Xu Si

Co-author:Xinming Wu,Zefeng Li, Shenghou Wang, Jun Zhu

Indexed by:Journal paper

Correspondence Author:Xinming Wu,Zefeng Li

Document Code:30

Discipline:Natural Science

First-Level Discipline:Geophysics

Document Type:SCI

Volume:5

Issue:1

Page Number:22

ISSN No.:2662-4435

Translation or Not:no

Date of Publication:2024-01-06

Links to published journals:https://doi.org/10.1038/s43247-023-01188-4