Optimization of the Match‐Filtering Method for Robust Repeating Earthquake Detection: The Multisegment Cross‐Correlation Approach

2020 ◽  
Vol 125 (7) ◽  
Author(s):  
Dawei Gao ◽  
Honn Kao
Keyword(s):  
Cross Correlation ◽  
Filtering Method ◽  
Earthquake Detection ◽  
Repeating Earthquake ◽  
Match Filtering

scholarly journals Improved earthquake detection as a probe for active fault structures in New Zealand's central Southern Alps

2021 ◽  
Author(s):  
◽  
Calum Chamberlain
Keyword(s):  
Cross Correlation ◽  
Matched Filter ◽  
Low Frequency ◽  
Southern Alps ◽  
Phase 2 ◽  
Earthquake Detection ◽  
Alpine Fault ◽  
Drill Site ◽  
Python Package ◽  
Drilling Project

<p>This thesis concerns the detection and analysis of micro-seismicity and low-frequency earthquakes in New Zealand's central Southern Alps. We make use of the 6.5 year continuous seismic dataset collected using the Southern Alps Microearthquake Borehole Array (SAMBA), alongside other temporary and permanent seismic deployments nearby. The small station spacing of this deployment allows for high resolution seismic studies near the Alpine Fault, a dextral-transpressive plate boundary fault between the Pacific and Australian plates.  Using this dataset we have documented the rst evidence of low-frequency earthquakes on or near the deep extent of the Alpine Fault. By using a network based crosscorrelation detection method we have generated a 3 year catalogue of 14 low-frequency earthquake families. These low-frequency earthquake families locate close to other indicators and models of the deep extent of the Alpine Fault, and we interpret these low-frequency earthquakes to represent shear failure on or near the deep extent of the Alpine Fault. These low-frequency earthquakes highlight a near-continuous background rate of deformation, punctuated by short periods of tremor. We also observe higher rates of low-frequency earthquake generation after large regional earthquakes. The magnitudes of our low-frequency earthquakes range from Mʟ‒0.8‒1.8, and appear to follow an exponential distribution, implying that there might be a characteristic length-scale of failure.  We have extended the catalogue of low-frequency earthquake templates using the full 6.5 year dataset and an objective synthetic detection methodology. We developed a new methodology for template detection after other methods failed, or were not feasible. This method employs simple synthetic template events, which, rather than trying to capture all of the complexities of the body waves we try to detect, approximate a simple waveform that does not correlate well with background noise. To undertake this method we have developed a multi-parallel Python package, which is highly portable (we have run this on computers ranging from dual-core, 8GB RAM laptops to a 393 node, 6349 CPU cluster computer) and distributed via an open-source model. This package was run through the 6.5 year dataset on the New Zealand E-Science PAN cluster to e fficiently (<48 hours clock-time) generate a spatially and temporally continuous catalogue of low-frequency earthquake templates. Using this method to detect an initial suite of over 25,000 detections grouped into 600 families we have generated 600 good quality, discrete stacked waveforms for use in further matched-filter detection routines. We have shown that, for templates with both P and S-phase picks, these templates locate near to our previously determined low-frequency earthquake family locations.  Using a network matched- filter detection technique we have generated a catalogue of micro-seismicity in a region of low-seismicity near the Whataroa Valley, motivated by the Deep-Fault Drilling Project; Phase-2. We detected 300 earthquakes that include a selection of near-repeating earthquakes. We find that most detected events are not similar enough to be termed repeating. For 106 earthquakes we are able to generate high-precision magnitudes calculated by singular-value decomposition of similar waveforms. We find a high b-value of 1.44 for these earthquakes, with no earthquakes above Mʟ1.6. By generating high precision cross-correlation derived picks for individual detections and employing a double-difference location methodology we show that seismicity does not delineate a single structure; rather we interpret the detected seismicity as temporally-limited earthquake sequences on small asperities adjacent to the Alpine Fault. Focal mechanisms for the best recorded events show dominantly strike-slip mechanisms, with lesser reverse and normal components.  During the drilling of the Deep-Fault Drilling Project: Phase-2 borehole we operated a real-time earthquake detection system around the drill-site. This was a multi-national effort involving 16 seismologists in three countries monitoring the automatic detections in shifts. During the 5 month real-time monitoring period we detected and located 493 earthquakes, none of which occurred within 3km of the drill-site, nor required changes to the drilling operations. We undertook this monitoring using open-source software, which employed a standard energy based detection scheme.  This thesis has contributed four complementary earthquake catalogues, a further three years of continuous seismic data from the central Southern Alps, and an opensource Python package for detection and analysis of earthquakes using cross-correlation techniques. The characteristics of these catalogues highlight deformation modes on and near one of the world's major strike-slip plate boundaries, both at depth, and at the upper extent of the seismogenic zone.</p>

Automatic Earthquake Detection and De-noising for Distributed Acoustic Sensing: Examples from On-land and Underwater Fibers

2020 ◽  
Author(s):  
Itzhak Lior ◽  
Daniel Mata ◽  
Gauthier Guerin ◽  
Diane Rivet ◽  
Anthony Sladen ◽  
...  
Keyword(s):  
Optical Fibers ◽  
Cross Correlation ◽  
Early Warning Systems ◽  
Earthquake Catalog ◽  
Ocean Bottom ◽  
Detection Scheme ◽  
Acoustic Sensing ◽  
Earthquake Detection ◽  
Waveform Similarity ◽  
Distributed Acoustic Sensing

&lt;p&gt;The use of underwater optical fibers, such as those currently traversing most of the world's oceans, for distributed acoustic sensing (DAS) holds great potential for seismic monitoring by complementing on-land seismic observations, especially near underwater faults. The analysis of underwater DAS records presents special challenges due to the noisy environment and the uneven cable-seafloor coupling. To fully exploit the potential of these records, automatically detecting and extracting seismic signals is imperative. To this end, a new automatic earthquake detection scheme is presented, based on waveform-similarity. Cross correlations between nearby records along the fiber are continuously calculated in short overlapping intervals. Earthquakes are detected as abrupt increases in cross correlation values over large segments of the cable. This procedure is applied to records of four existing fibers: one on land (Near Teil, south of France) and three underwater (one in Toulon, south of France, and two in Pylos, south-west Greece). Detected earthquakes are compared to earthquake catalogs and detection thresholds are obtained. That several of the detected earthquakes do not appear in any earthquake catalog demonstrates the proposed method's robustness. The cross correlation time shifts are then used to perform moveout corrections to the time series and phase weighted stacking (PWS) is applied to groups of neighboring traces. Unlike simple stacking approaches, PWS significantly enhances signal to noise ratios, allowing for more precise earthquake analysis and characterization. Further developing and applying such automatic techniques to ocean bottom fibers will enhance the performance of earthquake early warning systems, improving alert times for earthquakes occurring on underwater faults.&lt;/p&gt;

scholarly journals Estimation of Object Motion State Based on Adaptive Decorrelation Kalman Filtering

2019 ◽  
Vol 23 (4) ◽  
pp. 749-757
Author(s):  
Xinmei Wang ◽  
Leimin Wang ◽  
Longsheng Wei ◽  
Feng Liu ◽  
◽  
...  
Keyword(s):  
Kalman Filtering ◽  
Cross Correlation ◽  
Measurement Noise ◽  
Feature Point ◽  
Noise Variance ◽  
Filtering Method ◽  
Motion State ◽  
New Process ◽  
Object Feature ◽  
Noise Cross Correlation

To estimate the motion state of object feature point in image space, an adaptive decorrelation Kalman filtering model is proposed in this paper. The model is based on the Kalman filtering method. A first-order Markov sequence model is used to describe the colored measurement noise. To eliminate the colored noise, the measurement equation is reconstructed and then a cross-correlation between the process noise and the newly measurement noise is established. To eliminate the noise cross-correlation, a reconstructed process equation is proposed. According to the new process and measurement equations, and the noise mathematical characteristics of the standard Kalman filtering method, the parameters involved in the new process equation can be acquired. Then the noise cross-correlation can be successfully eliminated, and a decorrelation Kalman filtering model can be obtained. At the same time, for obtaining a more accurate measurement noise variance, an adaptive recursive algorithm is proposed to update the measurement noise variance based on the correlation method. It overcomes the limitations of traditional correlation methods used for noise variance estimation, thus, a relatively accurate Kalman filtering model can be obtained. The simulation shows that the proposed method improves the estimation accuracy of the motion state of object feature point.

scholarly journals Repeating Earthquake Detection and Characterisation in New Zealand: A Catalogue for the Raukumara Peninsula, Northern Hikurangi Subduction Margin

2021 ◽  
Author(s):  
◽  
Laura Hughes
Keyword(s):  
New Zealand ◽  
Cross Correlation ◽  
Active Faults ◽  
P Wave ◽  
Slow Slip ◽  
Normal Faulting ◽  
Repeating Earthquakes ◽  
Long Duration ◽  
Recurrence Intervals ◽  
Repeating Earthquake

<p>Repeating earthquakes provide a novel way of monitoring how stresses load faults between large earthquakes. In this thesis, we develop a method and composite criterion for identifying repeating earthquakes in New Zealand and present New Zealand’s first long-duration repeating earthquake catalogue. This thesis addresses three primary objectives: (1) develop a method and composite criterion for identifying repeating earthquakes; (2) build a long-duration catalogue of repeating earthquakes for the Raukumara Peninsula; and (3) apply the method and composite criterion in different tectonic settings to investigate whether it can be applied more broadly elsewhere in New Zealand. The systematic identification of repeating earthquakes in New Zealand provides the first step in being able to monitor the state of stresses of New Zealand’s active faults in situ throughout the earthquake cycle.  Studies elsewhere, particularly in Japan and California, have developed case-specific criteria for identifying repeating earthquakes. Building on these studies, we develop a method and composite criterion for identifying repeating earthquakes in New Zealand, focusing on seismicity around the Raukumara Peninsula. Our composite criterion states that for events to be identified as repeating earthquakes, two or more events must have a normalised cross-correlation of at least 0.95 at two or more seismic stations, when calculated for 75% of the earthquake coda. Sensitivity to correlation window length, filtering frequency-band and correlation threshold were tested during the development of the composite criterion. These tests indicated that small perturbations to the parameter thresholds did not affect our ability to detect repeating earthquakes using the composite criterion.  By applying our composite criterion to seismicity around the Raukumara Peninsula, we identified 62 repeating earthquake families occurring between 2003 and 2018, consisting of 160 individual earthquakes. These families have a magnitude range of MW 1.5–4.5, and have recurrence intervals and family durations of < 1–12 years. High-precision absolute and relative locations were calculated using manual phase picks and cross-correlation re-picking. Focal mechanisms for 56 of the families were also determined, using P-wave first motions, revealing predominantly strike-slip and normal faulting at shallow depths, low-angle reverse faulting along the subduction interface, and normal faulting in the subducting plate. We compared the timing of the repeating earthquakes to slow-slip events previously identified using geodetic measurements around the Raukumara Peninsula and observed that repeating earthquakes occurred during 26 of the 31 identified periods of slow-slip. We also compared the seismic moment– recurrence interval relationship of the Raukumara Peninsula repeating earthquakes to that of earthquakes near Parkfield, California, identified by Nadeau and Johnson (1998), and observed a similar functional relationship. Slip-rates of the Raukumara Peninsula repeating earthquake families were also calculated using a slip-rate–moment relationship and were found to vary from < 10mm/yr to 80mm/yr.  We applied the method and composite criterion developed for the Raukumara Peninsula to two other locations to ensure it could be applied successfully in other New Zealand regions with different seismotectonic characteristics. Using our workflow, we successfully identified four families in Marlborough, and three families around Fiordland. These families differ from those identified around the Raukumara Peninsula in that they had relatively short recurrence intervals and family durations, of 2 minutes– 15 months. The ability of the composite criterion to identify these families confirms its suitability for further studies of repeating earthquakes throughout New Zealand.</p>

EQcorrscan: Repeating and Near‐Repeating Earthquake Detection and Analysis in Python

2017 ◽  
Vol 89 (1) ◽  
pp. 173-181 ◽  
Author(s):  
Calum J. Chamberlain ◽  
Chet J. Hopp ◽  
Carolin M. Boese ◽  
Emily Warren‐Smith ◽  
Derrick Chambers ◽  
...  
Keyword(s):  
Earthquake Detection ◽  
Repeating Earthquake

scholarly journals Repeating Earthquake Detection and Characterisation in New Zealand: A Catalogue for the Raukumara Peninsula, Northern Hikurangi Subduction Margin

2021 ◽  
Author(s):  
◽  
Laura Hughes
Keyword(s):  
New Zealand ◽  
Cross Correlation ◽  
Active Faults ◽  
P Wave ◽  
Slow Slip ◽  
Normal Faulting ◽  
Repeating Earthquakes ◽  
Long Duration ◽  
Recurrence Intervals ◽  
Repeating Earthquake

<p>Repeating earthquakes provide a novel way of monitoring how stresses load faults between large earthquakes. In this thesis, we develop a method and composite criterion for identifying repeating earthquakes in New Zealand and present New Zealand’s first long-duration repeating earthquake catalogue. This thesis addresses three primary objectives: (1) develop a method and composite criterion for identifying repeating earthquakes; (2) build a long-duration catalogue of repeating earthquakes for the Raukumara Peninsula; and (3) apply the method and composite criterion in different tectonic settings to investigate whether it can be applied more broadly elsewhere in New Zealand. The systematic identification of repeating earthquakes in New Zealand provides the first step in being able to monitor the state of stresses of New Zealand’s active faults in situ throughout the earthquake cycle.  Studies elsewhere, particularly in Japan and California, have developed case-specific criteria for identifying repeating earthquakes. Building on these studies, we develop a method and composite criterion for identifying repeating earthquakes in New Zealand, focusing on seismicity around the Raukumara Peninsula. Our composite criterion states that for events to be identified as repeating earthquakes, two or more events must have a normalised cross-correlation of at least 0.95 at two or more seismic stations, when calculated for 75% of the earthquake coda. Sensitivity to correlation window length, filtering frequency-band and correlation threshold were tested during the development of the composite criterion. These tests indicated that small perturbations to the parameter thresholds did not affect our ability to detect repeating earthquakes using the composite criterion.  By applying our composite criterion to seismicity around the Raukumara Peninsula, we identified 62 repeating earthquake families occurring between 2003 and 2018, consisting of 160 individual earthquakes. These families have a magnitude range of MW 1.5–4.5, and have recurrence intervals and family durations of < 1–12 years. High-precision absolute and relative locations were calculated using manual phase picks and cross-correlation re-picking. Focal mechanisms for 56 of the families were also determined, using P-wave first motions, revealing predominantly strike-slip and normal faulting at shallow depths, low-angle reverse faulting along the subduction interface, and normal faulting in the subducting plate. We compared the timing of the repeating earthquakes to slow-slip events previously identified using geodetic measurements around the Raukumara Peninsula and observed that repeating earthquakes occurred during 26 of the 31 identified periods of slow-slip. We also compared the seismic moment– recurrence interval relationship of the Raukumara Peninsula repeating earthquakes to that of earthquakes near Parkfield, California, identified by Nadeau and Johnson (1998), and observed a similar functional relationship. Slip-rates of the Raukumara Peninsula repeating earthquake families were also calculated using a slip-rate–moment relationship and were found to vary from < 10mm/yr to 80mm/yr.  We applied the method and composite criterion developed for the Raukumara Peninsula to two other locations to ensure it could be applied successfully in other New Zealand regions with different seismotectonic characteristics. Using our workflow, we successfully identified four families in Marlborough, and three families around Fiordland. These families differ from those identified around the Raukumara Peninsula in that they had relatively short recurrence intervals and family durations, of 2 minutes– 15 months. The ability of the composite criterion to identify these families confirms its suitability for further studies of repeating earthquakes throughout New Zealand.</p>

scholarly journals Improved earthquake detection as a probe for active fault structures in New Zealand's central Southern Alps

2021 ◽  
Author(s):  
◽  
Calum Chamberlain
Keyword(s):  
Cross Correlation ◽  
Matched Filter ◽  
Low Frequency ◽  
Southern Alps ◽  
Phase 2 ◽  
Earthquake Detection ◽  
Alpine Fault ◽  
Drill Site ◽  
Python Package ◽  
Drilling Project

<p>This thesis concerns the detection and analysis of micro-seismicity and low-frequency earthquakes in New Zealand's central Southern Alps. We make use of the 6.5 year continuous seismic dataset collected using the Southern Alps Microearthquake Borehole Array (SAMBA), alongside other temporary and permanent seismic deployments nearby. The small station spacing of this deployment allows for high resolution seismic studies near the Alpine Fault, a dextral-transpressive plate boundary fault between the Pacific and Australian plates.  Using this dataset we have documented the rst evidence of low-frequency earthquakes on or near the deep extent of the Alpine Fault. By using a network based crosscorrelation detection method we have generated a 3 year catalogue of 14 low-frequency earthquake families. These low-frequency earthquake families locate close to other indicators and models of the deep extent of the Alpine Fault, and we interpret these low-frequency earthquakes to represent shear failure on or near the deep extent of the Alpine Fault. These low-frequency earthquakes highlight a near-continuous background rate of deformation, punctuated by short periods of tremor. We also observe higher rates of low-frequency earthquake generation after large regional earthquakes. The magnitudes of our low-frequency earthquakes range from Mʟ‒0.8‒1.8, and appear to follow an exponential distribution, implying that there might be a characteristic length-scale of failure.  We have extended the catalogue of low-frequency earthquake templates using the full 6.5 year dataset and an objective synthetic detection methodology. We developed a new methodology for template detection after other methods failed, or were not feasible. This method employs simple synthetic template events, which, rather than trying to capture all of the complexities of the body waves we try to detect, approximate a simple waveform that does not correlate well with background noise. To undertake this method we have developed a multi-parallel Python package, which is highly portable (we have run this on computers ranging from dual-core, 8GB RAM laptops to a 393 node, 6349 CPU cluster computer) and distributed via an open-source model. This package was run through the 6.5 year dataset on the New Zealand E-Science PAN cluster to e fficiently (<48 hours clock-time) generate a spatially and temporally continuous catalogue of low-frequency earthquake templates. Using this method to detect an initial suite of over 25,000 detections grouped into 600 families we have generated 600 good quality, discrete stacked waveforms for use in further matched-filter detection routines. We have shown that, for templates with both P and S-phase picks, these templates locate near to our previously determined low-frequency earthquake family locations.  Using a network matched- filter detection technique we have generated a catalogue of micro-seismicity in a region of low-seismicity near the Whataroa Valley, motivated by the Deep-Fault Drilling Project; Phase-2. We detected 300 earthquakes that include a selection of near-repeating earthquakes. We find that most detected events are not similar enough to be termed repeating. For 106 earthquakes we are able to generate high-precision magnitudes calculated by singular-value decomposition of similar waveforms. We find a high b-value of 1.44 for these earthquakes, with no earthquakes above Mʟ1.6. By generating high precision cross-correlation derived picks for individual detections and employing a double-difference location methodology we show that seismicity does not delineate a single structure; rather we interpret the detected seismicity as temporally-limited earthquake sequences on small asperities adjacent to the Alpine Fault. Focal mechanisms for the best recorded events show dominantly strike-slip mechanisms, with lesser reverse and normal components.  During the drilling of the Deep-Fault Drilling Project: Phase-2 borehole we operated a real-time earthquake detection system around the drill-site. This was a multi-national effort involving 16 seismologists in three countries monitoring the automatic detections in shifts. During the 5 month real-time monitoring period we detected and located 493 earthquakes, none of which occurred within 3km of the drill-site, nor required changes to the drilling operations. We undertook this monitoring using open-source software, which employed a standard energy based detection scheme.  This thesis has contributed four complementary earthquake catalogues, a further three years of continuous seismic data from the central Southern Alps, and an opensource Python package for detection and analysis of earthquakes using cross-correlation techniques. The characteristics of these catalogues highlight deformation modes on and near one of the world's major strike-slip plate boundaries, both at depth, and at the upper extent of the seismogenic zone.</p>

scholarly journals Time Evolution of Tectonic Earthquake in Ambon, Indonesia

2021 ◽  
Author(s):  
I Made Kris Adi Astra ◽  
Andreas Rietbrock ◽  
Nasim Karam Zadeh Toularoud
Keyword(s):  
Template Matching ◽  
Seismic Waves ◽  
Cross Correlation ◽  
Tectonic Earthquake ◽  
Seismic Migration ◽  
Matching Algorithm ◽  
Earthquake Detection ◽  
Mathematical Techniques ◽  
Low Amplitude ◽  
Insight Into

Abstract The advancement of earthquake seismology brings a new insight into earthquake detection. Advanced signal processing by implementing sliding-window mathematical techniques of cross-correlation into data stream are able to recognize low amplitude earthquake signals even under the presence of noise. Clear detection of the onset of low amplitude seismic waves is crucial, however they often hidden by larger amplitudes of coda waves after the generation of mainshock event. By performing template matching algorithm we found a detail temporal variation of seismicity related to Mw 6.6 Ambon earthquake. In comparison, the detection level is up to eight times from conventional method. The method also reveals a seismic migration before the main event coincide with the direction of local tectonic movement derived from previous GPS analysis. Since the method able to detect the earthquake within their family, it gives a reasonably significant improvement to virtual stress-meter analysis. Highly accumulated stress preceding the main event depicted by b-value drop are clearly mapped in a high confidence level.

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