scholarly journals Detection of low-frequency earthquakes by the matched filter technique using the product of mutual information and correlation coefficient

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Ryo Kurihara ◽  
Aitaro Kato ◽  
Sumito Kurata ◽  
Hiromichi Nagao
Keyword(s):  
Mutual Information ◽  
Matched Filter ◽  
Low Frequency ◽  
Japan Meteorological Agency ◽  
Filter Method ◽  
Artificial Noise ◽  
Data Set ◽  
Seismic Stations ◽  
Filter Technique ◽  
Single Station

AbstractThe matched filter technique is often used to detect microearthquakes such as deep low-frequency (DLF) earthquakes. It compares correlation coefficients (CC) between waveforms of template earthquakes and the observed data. Conventionally, the sum of CC at multiple seismic stations is used as an index to detect the DLF earthquakes. A major disadvantage of the conventional method is drastically reduced detection accuracy when there are too few seismic stations. The new matched filter method proposed in this study can accurately detect microearthquakes using only a single station. It adopts mutual information (MI) in addition to CC to measure the similarity between the template and target waveforms. The method uses the product of MI and CC (MICC) as an index to detect DLF earthquakes. This index shows a distinct peak corresponding to an earthquake signal in a synthetic data set consisting of artificial noise and the waveform of a DLF earthquake. Application of this single-station method to field observations of Kirishima volcano, one of the most active volcanoes in Japan, detected a total of 354 events from the data in December 2010, whereas the catalog of the Japan Meteorological Agency shows only two. Of the detected events, 314 (89%) are likely DLF earthquakes and other events may be false detections. Most of the false detections correspond to surface-wave arrivals from teleseismic events. The catalog of DLF earthquakes constructed here shows similar temporal behavior to that found by the conventional matched filter method using the sum of the CC of the six stations near the volcano. These results suggest that the proposed method can greatly contribute to the accurate cataloging of DLF earthquakes using only a single seismic station. Graphical Abstract

scholarly journals Detection of low-frequency earthquakes by matched filter technique using the product of mutual information and correlation coefficient

2021 ◽  
Author(s):  
Ryo Kurihara ◽  
Aitaro Kato ◽  
Sumito Kurata ◽  
Hiromichi Nagao
Keyword(s):  
Mutual Information ◽  
Matched Filter ◽  
Low Frequency ◽  
Japan Meteorological Agency ◽  
Filter Method ◽  
Artificial Noise ◽  
Data Set ◽  
Seismic Stations ◽  
Filter Technique ◽  
Single Station

Abstract Matched filter technique is often used to detect microearthquakes such as deep low-frequency (DLF) earthquakes. It compares correlation coefficients (CC) between waveforms of template earthquakes and the observed data. Conventionally, the sum of CC at multiple seismic stations is used as an index to detect the DLF earthquakes. A major disadvantage of conventional method is drastically reduced detection accuracy when there are too few seismic stations. A new matched filter method proposed in this study can accurately detect microearthquakes using only a single station. It adopts mutual information (MI) in addition to CC to measure the similarity between the template and target waveforms. The method uses the product of MI and CC (MICC) as an index to detect DLF earthquakes. This index shows a distinct peak corresponding to an earthquake signal in a synthetic data set consisting of artificial noise and the waveform of a DLF earthquake. Application of this single-station method to field observations of Kirishima volcano, one of the most active volcanoes in Japan, detected a total of 354 DLF earthquakes from the data in December 2010, whereas the catalog of the Japan Meteorological Agency shows only two. The catalog of DLF earthquakes constructed here shows similar temporal behavior to that found by conventional matched filter method using the sum of the CC of the six stations near the volcano. The proposed method successfully identified approximately 80% of the earthquakes in the conventionally constructed catalogs. These results suggest that the proposed method can greatly contribute to the accurate cataloging of DLF earthquakes using only a single seismic station.

The Extended Integrated Particle Filter Method (IPFx) as a High-Performance Earthquake Early Warning System

2021 ◽  
Author(s):  
Masumi Yamada ◽  
Koji Tamaribuchi ◽  
Stephen Wu
Keyword(s):  
Particle Filter ◽  
Early Warning ◽  
Seismic Intensity ◽  
Earthquake Early Warning ◽  
Japan Meteorological Agency ◽  
Estimation Accuracy ◽  
Filter Method ◽  
Source Estimation ◽  
Single Station ◽  
Seismic Networks

ABSTRACT An earthquake early warning (EEW) system rapidly analyzes seismic data to report the occurrence of an earthquake before strong shaking is felt at a site. In Japan, the integrated particle filter (IPF) method, a new source-estimation algorithm, was recently incorporated into the EEW system to improve the source-estimation accuracy during active seismicity. The problem of the current IPF method is that it uses the trigger information computed at each station in a specific format as the input and is therefore applicable to only limited seismic networks. This study proposes the extended IPF (IPFx) method to deal with continuous waveforms and merge all Japanese real-time seismic networks into a single framework. The new source determination algorithm processes seismic waveforms in two stages. The first stage (single-station processing) extracts trigger and amplitude information from continuous waveforms. The second stage (network processing) accumulates information from multiple stations and estimates the location and magnitude of ongoing earthquakes based on Bayesian inference. In 10 months of continuous online experiments, the IPFx method showed good performance in detecting earthquakes with maximum seismic intensity ≥3 in the Japan Meteorological Agency (JMA) catalog. By merging multiple seismic networks into a single EEW system, the warning time of the current EEW system can be improved further. The IPFx method provides accurate shaking estimation even at the beginning of event detection and achieves seismic intensity error <0.25  s after detecting an event. This method correctly avoided two major false alarms on 5 January 2018 and 30 July 2020. The IPFx method offers the potential of expanding the JMA IPF method to global seismic networks.

scholarly journals Relative source location using coda-wave interferometry: Method, code package, and application to mining-induced earthquakes

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. F73-F84 ◽  
Author(s):  
Youqian Zhao ◽  
Andrew Curtis
Keyword(s):  
Single Channel ◽  
Source Region ◽  
Source Location ◽  
Coda Wave ◽  
Data Set ◽  
Seismic Stations ◽  
Location Method ◽  
Wide Range ◽  
Single Station ◽  
Coda Wave Interferometry

A wide range of applications requires the relative locations of sources of energy to be known accurately. Most conventional location methods are either subject to errors that depend strongly on inaccuracy in the model of propagation velocity used or demand a well-distributed network of surrounding seismic stations to produce reliable results. A new source location method based on coda-wave interferometry (CWI) is relatively insensitive to the number of seismic stations and to the source-to-station azimuthal coverage. Therefore, it opens new avenues for research, for applications in areas with unfavorable recording geometries, and for applications that require a complementary method. This method uses CWI to estimate distances between pairs of seismic events with a similar source mechanism recorded at the same station. These separation estimates are used to solve for the locations of clusters of events relative to one another within a probabilistic framework through optimization. It is even possible to find the relative locations of clusters of events with one single-channel station. Given these advantages, it is likely that one reason that the method is not used more widely is the lack of reliable code that implements this multistage method. Therefore, we have developed a well-commented MATLAB code that does so, and we evaluate examples of its applications. It can be used with seismic data from a single-station channel, and it enables data recorded by different channels and stations to be used simultaneously. It is therefore possible to combine data from permanent yet sparse networks and from temporary arrays closer to the source region. We use the code to apply the location method to a selected data set of the New Ollerton earthquakes in England to demonstrate the validity of the code. The worked example is provided within the package. A way to assess the quality of the location results is also provided.

scholarly journals Detection of Deep Low-frequency Earthquakes in the Nankai Subduction Zoneover 11 Years Usingamatched Filter Technique

2020 ◽  
Author(s):  
Aitaro Kato ◽  
Shigeki Nakagawa
Keyword(s):  
Matched Filter ◽  
Low Frequency ◽  
Slow Slip ◽  
Slow Slip Events ◽  
Filter Technique ◽  
Strike Direction ◽  
Episodic Tremor And Slip ◽  
Spatio Temporal ◽  
Episodic Tremor

Abstract To improve our understanding of the long-term behavior of low-frequency earthquakes (LFEs) along the tremor belt of the Nankai subduction zone, we applied a matched filter technique to continuous seismic data recorded by a dense and highly sensitive seismic network over an 11year window, April 2004 to August 2015. We detected a total of ~510,000 LFEs, or ~23× the number of LFEs in the JMA catalog for the same period. During long-term slow slip events (SSEs) in the Bungo Channel, a series of migrating LFEbursts intermittently occurred along the fault-strike direction, with slow hypocenter propagation. Elastic energy released by long-term SSEs appears to control the extent of LFE activity. We identify slowlymigrating fronts of LFEs during major episodic tremor and slip (ETS)events, which extend over distances of up to 100 km and follow diffusion-like patterns of spatial evolution with a diffusion coefficient of ~104 m2/s. This migration pattern closely matches the spatio-temporal evolution of tectonictremors reported by previous studies. At shorter distances, up to 15 km, we discovered rapid diffusion-like migrationof LFEs with a coefficient of ~105 m2/s. We also recognize that rapid migration of LFEs occurred intermittently in many streaks during major ETS episodes. These observations suggest that slow slip transients contain a multitude of smaller, temporally clustered fault slip events whose evolution is controlled by a diffusional process.

scholarly journals Detecting Real Earthquakes Using Artificial Earthquakes: On the Use of Synthetic Waveforms in Matched-Filter Earthquake Detection

2021 ◽  
Author(s):  
Calum Chamberlain ◽  
John Townend
Keyword(s):  
Focal Mechanism ◽  
Matched Filter ◽  
A Priori ◽  
Low Frequency ◽  
Aftershock Sequence ◽  
Filter Method ◽  
Detection Rates ◽  
Earthquake Detection ◽  
American Geophysical ◽  
American Geophysical Union

©2018. American Geophysical Union. All Rights Reserved. Matched-filters are an increasingly popular tool for earthquake detection, but their reliance on a priori knowledge of the targets of interest limits their application to regions with previously documented seismicity. We explore an extension to the matched-filter method to detect earthquakes and low-frequency earthquakes on local to regional scales. We show that it is possible to increase the number of detections compared with standard energy-based methods, with low false-detection rates, using suites of synthetic waveforms as templates. We apply this to a microearthquake swarm and an aftershock sequence, and to detect low-frequency earthquakes. We also explore the sensitivity of detections to the synthetic source's location and focal mechanism. Source-receiver geometry has a first-order control on how sensitive matched-filter detectors are to variations in source location and focal mechanism, and this likely applies to detections made using both synthetic and real templates.

scholarly journals Detection of deep low-frequency earthquakes in the Nankai subduction zone over 11 years using a matched filter technique

2020 ◽  
Author(s):  
Aitaro Kato ◽  
Shigeki Nakagawa
Keyword(s):  
Subduction Zone ◽  
Matched Filter ◽  
Low Frequency ◽  
Slow Slip ◽  
Slow Slip Events ◽  
Filter Technique ◽  
Episodic Tremor And Slip ◽  
Nankai Subduction Zone ◽  
Spatio Temporal

Abstract To improve our understanding of the long-term behavior of low-frequency earthquakes (LFEs) along the tremor belt of the Nankai subduction zone, we applied a matched filter technique to continuous seismic data recorded by a dense and highly sensitive seismic network over an 11 year window, April 2004 to August 2015. We detected a total of ~510,000 LFEs, or ~23× the number of LFEs in the JMA catalog for the same period. During long-term slow slip events (SSEs) in the Bungo Channel, a series of migrating LFE bursts intermittently occurred along the fault-strike direction, with slow hypocenter propagation. Elastic energy released by long-term SSEs appears to control the extent of LFE activity. We identify slowly migrating fronts of LFEs during major episodic tremor and slip (ETS) events, which extend over distances of up to 100 km and follow diffusion-like patterns of spatial evolution with a diffusion coefficient of ~10 4 m 2 /s. This migration pattern closely matches the spatio-temporal evolution of tectonic tremors reported by previous studies. At shorter distances, up to 15 km, we discovered rapid diffusion-like migration of LFEs with a coefficient of ~10 5 m 2 /s. We also recognize that rapid migration of LFEs occurred intermittently in many streaks during major ETS episodes. These observations suggest that slow slip transients contain a multitude of smaller, temporally clustered fault slip events whose evolution is controlled by a diffusional process.

scholarly journals Detection of deep low-frequency earthquakes in the Nankai subduction zone over 11 years using a matched filter technique

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Aitaro Kato ◽  
Shigeki Nakagawa
Keyword(s):  
Subduction Zone ◽  
Matched Filter ◽  
Low Frequency ◽  
Slow Slip ◽  
Slow Slip Events ◽  
Filter Technique ◽  
Episodic Tremor And Slip ◽  
Nankai Subduction Zone ◽  
Spatio Temporal

Abstract To improve our understanding of the long-term behavior of low-frequency earthquakes (LFEs) along the tremor belt of the Nankai subduction zone, we applied a matched filter technique to continuous seismic data recorded by a dense and highly sensitive seismic network over an 11-year window, April 2004 to August 2015. We detected a total of ~ 510,000 LFEs, or ~ 23 × the number of LFEs in the JMA catalog for the same period. During long-term slow slip events (SSEs) in the Bungo Channel, a series of migrating LFE bursts intermittently occurred along the fault-strike direction, with slow hypocenter propagation. Elastic energy released by long-term SSEs appears to control the extent of LFE activity. We identify slowly migrating fronts of LFEs during major episodic tremor and slip (ETS) events, which extend over distances of up to 100 km and follow diffusion-like patterns of spatial evolution with a diffusion coefficient of ~ 104 m2/s. This migration pattern closely matches the spatio-temporal evolution of tectonic tremors reported by previous studies. At shorter distances, up to 15 km, we discovered rapid diffusion-like migration of LFEs with a coefficient of ~ 105 m2/s. We also recognize that rapid migration of LFEs occurred intermittently in many streaks during major ETS episodes. These observations suggest that slow slip transients contain a multitude of smaller, temporally clustered fault slip events whose evolution is controlled by a diffusional process.

scholarly journals Detection of deep low-frequency earthquakes in the Nankai subduction zone over 11 years using a matched filter technique

2020 ◽  
Author(s):  
Aitaro Kato ◽  
Shigeki Nakagawa
Keyword(s):  
Subduction Zone ◽  
Matched Filter ◽  
Low Frequency ◽  
Slow Slip ◽  
Slow Slip Events ◽  
Filter Technique ◽  
Episodic Tremor And Slip ◽  
Nankai Subduction Zone ◽  
Spatio Temporal

Abstract To improve our understanding of the long-term behavior of low-frequency earthquakes (LFEs) along the tremor belt of the Nankai subduction zone, we applied a matched filter technique to continuous seismic data recorded by a dense and highly sensitive seismic network over an 11 year window, April 2004 to August 2015. We detected a total of ~510,000 LFEs, or ~23× the number of LFEs in the JMA catalog for the same period. During long-term slow slip events (SSEs) in the Bungo Channel, a series of migrating LFE bursts intermittently occurred along the fault-strike direction, with slow hypocenter propagation. Elastic energy released by long-term SSEs appears to control the extent of LFE activity. We identify slowly migrating fronts of LFEs during major episodic tremor and slip (ETS) events, which extend over distances of up to 100 km and follow diffusion-like patterns of spatial evolution with a diffusion coefficient of ~10 4 m 2 /s. This migration pattern closely matches the spatio-temporal evolution of tectonic tremors reported by previous studies. At shorter distances, up to 15 km, we discovered rapid diffusion-like migration of LFEs with a coefficient of ~10 5 m 2 /s. We also recognize that rapid migration of LFEs occurred intermittently in many streaks during major ETS episodes. These observations suggest that slow slip transients contain a multitude of smaller, temporally clustered fault slip events whose evolution is controlled by a diffusional process.

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