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Unveiling Informational Properties of the Chen-Ouillon-Sornette Seismo-Electrical Model.
Chen, Hong-Jia; Telesca, Luciano; Lovallo, Michele; Chen, Chien-Chih.
Afiliação
  • Chen HJ; Department of Earth Sciences, National Central University, Taoyuan 32001, Taiwan.
  • Telesca L; Institute of Methodologies for Environmental Analysis, National Research Council, 85050 Tito (PZ), Italy.
  • Lovallo M; Agenzia Regionale per la Protezione dell' Ambiente di Basilicata (ARPAB), 85100 Potenza, Italy.
  • Chen CC; Department of Earth Sciences, National Central University, Taoyuan 32001, Taiwan.
Entropy (Basel) ; 23(3)2021 Mar 12.
Article em En | MEDLINE | ID: mdl-33809156
The seismo-electrical coupling is critical to understand the mechanism of geoelectrical precursors to earthquakes. A novel seismo-electrical model, called Chen-Ouillon-Sornette (COS) model, has been developed by combining the Burridge-Knopoff spring-block system with the mechanisms of stress-activated charge carriers (i.e., electrons and holes) and pressure-stimulated currents. Such a model, thus, can simulate fracture-induced electrical signals at a laboratory scale or earthquake-related geoelectrical signals at a geological scale. In this study, by using information measures of time series analysis, we attempt to understand the influence of diverse electrical conditions on the characteristics of the simulated electrical signals with the COS model. We employ the Fisher-Shannon method to investigate the temporal dynamics of the COS model. The result showed that the electrical parameters of the COS model, particularly for the capacitance and inductance, affect the levels of the order/disorder in the electrical time series. Compared to the field observations, we infer that the underground electrical condition has become larger capacitance or smaller inductance in seismogenic processes. Accordingly, this study may provide a better understanding of the mechanical-electrical coupling of the earth's crust.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Entropy (Basel) Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Entropy (Basel) Ano de publicação: 2021 Tipo de documento: Article