中国科学:地球科学(英文版)2024,Vol.67Issue(5) :1698-1713.DOI:10.1007/s11430-023-1285-4

Identifying and localizing of seismogenic electromagnetic anomalies from data observed by permanent MT stations

Bing HAN Wenbao HU Guoze ZHAO Ji TANG
中国科学:地球科学(英文版)2024,Vol.67Issue(5) :1698-1713.DOI:10.1007/s11430-023-1285-4

Identifying and localizing of seismogenic electromagnetic anomalies from data observed by permanent MT stations

Bing HAN 1Wenbao HU 2Guoze ZHAO 1Ji TANG1
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作者信息

  • 1. State Key Laboratory of Earthquake Dynamics,Institute of Geology,Beijing 100029,China
  • 2. Key Laboratory of Exploration Technologies for Oil and Gas Resources of Ministry of Education,Yangtze University,Wuhan 430100,China
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Abstract

In this research,an arbitrarily oriented electric dipole at subsurface is used to simulate Seismogenic Electromagnetic(SEM)radiation emanating from a seismic zone during its gestation phase.Analytical synthesis of responses at the Lijiang magnetotelluric(MT)station has revealed that SEM radiation could induce identifiable anomalies in the electromagnetic(EM)spectrum,apparent resistivity and phase within specific frequency bands.Background variations were extracted from long-term observation data of Dali and Lijiang MT stations,enabling the identification of SEM anomalies related to the Yunlong and Yangbi earthquakes.Multiple parameters of dipole sources at subsurface were obtained by applying the Differential Ant Colony Optimization(DACO)algorithm to anomalous data of two stations with multi-frequencies and various response functions.The spatial distribution of these predicted dipoles is predominantly clustered in or around the seismogenic area,with their azimuthal orientation aligning towards the seismogenic fault in general.This study has demonstrated the potential of using subsurface electric dipole simulations for SEM radiation analysis,offering a feasible approach for the prediction and understanding of seismogenic zones.

Key words

MT responses/Identifying SEM anomaly/Vector electric dipole responses/Localizing SEM sources by inversion

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出版年

2024
中国科学:地球科学(英文版)
中国科学院

中国科学:地球科学(英文版)

影响因子:1.002
ISSN:1674-7313
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