Detecting Earthquake-Related Anomalies of a Borehole Strain Network Based on Multi-Channel Singular Spectrum Analysis

Abstract

To investigate the nonlinear spatio-temporal behavior of earthquakes, a complex network has been built using borehole strain data from the southwestern endpoint of the Longmenshan fault zone, Sichuan-Yunnan region of China, and the topological structural properties of the network have been investigated based on data from 2011–2014. Herein, six observation sites were defined as nodes and their edges as the connections between them. We introduced Multi-channel Singular Spectrum Analysis (MSSA) to analyze periodic oscillations, earthquake-related strain, and noise in multi-site observations, and then defined the edges of the network by calculating the correlations between sites. The results of the daily degree centrality of the borehole strain network indicated that the strain network anomalies were correlatable with local seismicity associate with the earthquake energy in the strain network. Further investigation showed that strain network anomalies were more likely to appear before major earthquakes rather than after them, particularly within 30 days before an event. Anomaly acceleration rates were also found to be related to earthquake energy. This study has revealed the self-organizing pre-earthquake phenomena and verified the construction of borehole networks is a powerful tool for providing information on earthquake precursors and the dynamics of complex fault systems.

Extraction of Pre-earthquake Anomalies in Borehole Strain Data Using Graph WaveNet: A Case Study of the Lushan Earthquake

“…In the other segment, the number of anomalous days started to rise sharply from March 2013 to June after the earthquake, after which the increase in anomalous days gradually leveled off. Qiu et al (An et al, 2013;Jiang et al, 2013;Yu et al, 2020;Qiu et al, 2013;Zhu et al, 2018) conducted research on short-term impending earthquake anomalies pre-ceding the Lushan earthquake and suggested that these anomalies occurred within a few days to one month before the earthquake. Our study yielded similar results, indicating anomalies in the one-month preearthquake period of the Lushan earthquake.…”

Eigenstate Transition of Multi-Channel Time Series Data around Earthquakes

“…Although the timescales they are focusing on are different from us, there is a possibility that they can be discussed on the basis of a common root, such as a micro model of earthquake, in the future. Another study considered multiple strain gauges installed at distant locations, that is wide area information, as a network, and captured the topological changes in the network structure before an earthquake occurs [23]. Their study considered multiple strain gauges at different locations as multi-channel and uses multi-channel anomaly spectrum analysis.…”

The Study on Anomalies of the Geomagnetic Topology Network Associated with the 2022 Ms6.8 Luding Earthquake

“…MSSA is an extension of Singular Spectrum Analysis (SSA) that incorporates the relationships between multiple time series. It is widely applied to extract periodic components, noise components, and other relevant features from multiple time series data [25,[42][43][44][45]. SSA is based on singular spectrum decomposition, a powerful technique for decomposing and reconstructing time series [46].…”

“…Therefore, we adopt a multi-station analysis approach at the data level through Multichannel Singular Spectrum Analysis (MSSA) [23]. MSSA is particularly suitable for the multi-scale decomposition of spatiotemporal data and managing multivariate time series by estimating periodic components and trends and reducing noise [24,25]. Subsequently, to address the limitations of cross-correlation, we construct a topology network to analyze the correlation of spatiotemporal features in multi-station data.…”