TITLE:
A Detection Method of Earthquake Precursory Anomalies Using the Four-Component Borehole Strainmeter
AUTHORS:
Xiangyang Kong, Kaizhi Su, Fujinawa Yukio, Noda Yoichi
KEYWORDS:
Borehole Strainmeter, Earthquake Observation Technology, Pre-Seismic Anomalies, Data Filtering
JOURNAL NAME:
Open Journal of Earthquake Research,
Vol.7 No.2,
May
31,
2018
ABSTRACT:
Strainmeters have been used to detect earthquake precursory anomalies in many
countries. An innovated four-component strainmeter with four sensing units set
at 45 degrees intervals, named SKZ strainmeter, was developed and used in China.
The design, with a few unique features, allows high-sensitivity monitoring of
the regime of the crustal strain field, as well as the self-consistencies of the instrument.
One of the most difficult problems in the earthquake precursory investigation
is to efficiently detect anomalies from large amount of data. Pattern recognition
of waveforms is widely used, but it is time-consuming and relies more
or less investigator’s experience and decision. In this study, the consistency factors
of the paired components were firstly shown to be utilized to detect anomalies
possibly related with imminent earthquakes. Here, rather than using the consistency
factors, the correlation coefficients of the two orthogonal strain data
were used to detect. SKZ strainmeters have been installed at more than ten sites
in China, exhibited high efficiency and reliability in precursory monitoring since.
Anomalous variations from a few stations during two recent earthquakes in
south China were analyzed. During normal stages, diurnal earth tides could be
clearly observed with very little urban noises. Though the consistency factors
may have near constant bias, their correlation coefficients remain near 1.0,
greater than 0.99. During the imminent preparatory stage of earthquake occurrence,
non-planar strain may appear and the correlation coefficients drop noticeably.
The analysis showed that the correlation coefficient between the two orthogonal
components is a useful parameter in post-processing of the strain data
to detect precursory anomalies. The resultant resolving power is shown to be
some one-order larger compared with previous methods.