29 Apr 2024
 | 29 Apr 2024
Status: this preprint is currently under review for the journal NPG.

Fractal analysis of geomagnetic data to decipher pre-earthquake process in Andaman-Nicobar region, India

Rahul Prajapati and Kusumita Arora

Abstract. The emission of seismo-electromagnetic (EM) signatures prior to earthquake recorded in geomagnetic data has potential to reveal the pre-earthquake processes in focal zones. This study focused to analysis of vertical component of a geomagnetic field from Mar 2019 to Apr 2020 using fractal and multifractal approach to identify the EM signatures in Campbell Bay, a seismically active region of Andaman and Nicobar, subduction zone. The significant enhancements in monofractal dimension and spectrum width components of multifractal highlights the high frequency with less and more complex nature of EM signatures preceded by earthquakes respectively, which indicates that the pre-earthquake processes on West Andaman Fault (WAF) and Andaman Trench (AT) are due to micro fracturing. Moreover, the significant enhancements in holder exponents, components of multifractal highlight the less correlated, smooth, and low frequency characteristics of EM signatures preceded by earthquakes, which indicate that pre-earthquake processes on Seulimeum Strand (SS) fault are due to electrokinetic processes. Thus, the mono fractal, spectrum width, and holder exponent parameter respond differently to the earthquakes with different characteristics, causing EM signatures to be observed with an average of 10, 12, and 20 days prior to the earthquakes respectively, which are also lies in range of short -term earthquake prediction.

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Rahul Prajapati and Kusumita Arora

Status: open (until 24 Jun 2024)

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Rahul Prajapati and Kusumita Arora
Rahul Prajapati and Kusumita Arora


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Short summary
The emission of EM fields due to lithospheric deformation in the focal zone prior to the commencement of earthquakes can be used as a short-term earthquake precursor. A fractal-based analysis of vertical component geomagnetic signal is effective in identifying the EM signatures prior to the earthquake and characteristics of EM signatures to reveal the type of pre-earthquake processes such as microfracture, electrokinetic, etc.