RETREAT: A REal-Time TREmor Analysis Tool for Seismic Arrays, With Applications for Volcano Monitoring

Smith, Patrick J.; Bean, Christopher J.

doi:10.3389/feart.2020.586955

Cited by 6 publications

(8 citation statements)

References 43 publications

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“…Given this limitation, we apply beamforming (Smith and Bean, 2020) to the vertical components of the three local stations to gain insight into where the monochromatic LP earthquakes originate at Little Sitkin. We therefore use the three stations as a tripartite array.…”

Section: Methodsmentioning

confidence: 99%

“…F-K beamforming, on the other hand, scans over a range of possible plane waves and plots the stacked power for each candidate plane wave in slowness (inverse apparent velocity) space. F-K beamforming (Smith and Bean, 2020) is better suited for analyzing the monochromatic LP earthquakes at Little Sitkin since, by virtue of their narrow frequency band, cross-correlation can lead to an ambiguous time delay for a single station pair. This issue can be understood by considering perfectly monochromatic signals: in that case, cross-correlation between two stations would result in a series of maxima with equal peak values equally spaced in time over multiples of the period.…”

Section: Methodsmentioning

confidence: 99%

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Monochromatic Long-Period Seismicity Prior to the 2012 Earthquake Swarm at Little Sitkin Volcano, Alaska

et al. 2021

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Detection of the earliest stages of unrest is one of the most challenging and yet critically needed aspects of volcano monitoring. We investigate a sequence of five unusual long-period (LP) earthquakes that occurred in the days prior to the onset of a months-long volcano-tectonic (VT) earthquake swarm beneath Little Sitkin volcano in the Aleutian Islands during late 2012. The long-period earthquakes had two distinctive characteristics: their signals were dominated by a monochromatic spectral peak at approximately 0.57 Hz and they had impulsive P and S-wave arrivals on a seismometer located on Amchitka Island 80 km to the southeast of the volcano. In each case, the monochromatic earthquakes ended with a higher-frequency event after approximately 2 min of duration. We find evidence that the five monochromatic LP earthquakes resulted from the resonance of a tabular magma body at middle crustal depths (15 km) on the western side of Little Sitkin. Based on the resonant frequency and quality factor of the monochromatic LP earthquakes, we infer the magma body to have a lateral extent of 500 m and a thickness of 9 m. We interpret that a magmatic intrusion excited the monochromatic LP earthquakes and subsequently increased the stress beneath the volcano, leading to the onset of the shallow (<10 km depth) VT swarm five days later.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Monochromatic Long-Period Seismicity Prior to the 2012 Earthquake Swarm at Little Sitkin Volcano, Alaska

et al. 2021

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“…Joint research on sub-surface processes involved developing tools for automatic real-time processing of pre-eruptive seismic signals, RETREAT [Smith and Bean, 2020], correlation of seismo-acoustic signals [Ripepe et al, 2018] and near-real time processing of geodetic signals with the GBIS and LiCSAR software [Lazecký et al, 2020].…”

Section: 22 Joint Research Activitiesmentioning

confidence: 99%

The integrated multidisciplinary European volcano infrastructure: from the conception to the implementation

Puglisi

Reitano

Spampinato

et al. 2022

Annals of Geophysics

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Recent decades have highlighted the increasing need to connect and strengthen the volcanology community at European level. Indeed, research in the volcanology field is highly qualified in Europe and the volcano monitoring infrastructures have achieved valuable know-how, becoming the state-of-the-art in the world. However, the lack of common good practices in sciences and technologies, missing standards, as well as a significant fragmentation of the community requires coordination to move forward and guarantee a trans-national harmonisation. The European Plate Observing System (EPOS) represented the first opportunity to initiate this process of coordination by encouraging the creation of a European volcanological scientific infrastructure for data and service sharing. During the preparation and the design of EPOS, the volcanology community identified the objectives and the needs of the community building, the services to be provided and the work plan to implement the infrastructure. To achieve this aim, the contribution from three European projects FUTUREVOLC, MED-SUV and EUROVOLC was essential. This paper presents the main steps performed during the last years for building the community and implementing the infrastructure. This paper also describes the strategic choices and actions taken to realise the infrastructure such as the establishment of the Volcano Observation Thematic Core Service (TCS), whose structure and activity are described.

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“…However, with the growing amount of data continuously acquired by dense monitoring seismic networks, manual inspection of signals needs to be integrated with automatic and/or machine learning (ML) tools. As a result, recent research has focused on the implementation of automatic tools for real-time tremor analysis with seismic array techniques (Smith & Bean, 2020) and/or in the application of both supervised and unsupervised machine learning • New insights on the emission tremor would help to monitor the CO 2 degassing at the Mefite d'Ansanto and its temporal evolution approaches for tremor characterization and classification (Curilem et al, 2017;Malfante et al, 2018;Masotti et al, 2008;Permana et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Automated Detection and Machine Learning‐Based Classification of Seismic Tremors Associated With a Non‐Volcanic Gas Emission (Mefite d’Ansanto, Southern Italy)

Panebianco,

Satriano,

Vivone

et al. 2024

Geochem Geophys Geosyst

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A major aim in the study of crustal fluids is the development of automatic methodologies for monitoring deep‐source, non‐volcanic gas emissions’ spatio‐temporal evolution. Crustal fluids play a significant role in the generation of large earthquakes and the characterization of their emissions on the surface can be essential for better understanding crustal processes generating earthquakes. We investigate seismic tremors recorded over 4 days in 2019 at the Mefite d’Ansanto (southern Apennines, Italy) that is located at the northern end of the fault system that generated the Mw 6.9 1980 Irpinia Earthquake. The Mefite d’Ansanto is hypothesized to be the largest natural, non‐volcanic, CO2‐rich gas emission on Earth. The seismic tremor is studied by employing a dense temporary seismic network and an automated detection algorithm based on non‐parametric statistics of the recorded signal amplitudes. We extracted signal characteristics (RMS amplitude and statistical moments of amplitudes both in time and frequency domains) for use in the subsequent supervised machine‐learning classification of the target tremor and accidently detected anthropogenic and background noise. The data set is used for the training and optimization of station‐based KNN (k‐Nearest‐Neighbors) binary classifiers obtaining good classification performances with a median overall accuracy across all stations of 92.8%. The classified tremor displayed common features at all stations: variable duration (16 s to 30–40 min), broad peak frequency (4–20 Hz) with varying amplitudes, and two types of signals: (a) long‐duration, high‐amplitude tremor and (b) pulsating tremor. Higher tremor amplitudes recorded at stations closer to local bubbling and pressurized vents suggest multiple local tremor sources.

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RETREAT: A REal-Time TREmor Analysis Tool for Seismic Arrays, With Applications for Volcano Monitoring

Cited by 6 publications

References 43 publications

Monochromatic Long-Period Seismicity Prior to the 2012 Earthquake Swarm at Little Sitkin Volcano, Alaska

Monochromatic Long-Period Seismicity Prior to the 2012 Earthquake Swarm at Little Sitkin Volcano, Alaska

The integrated multidisciplinary European volcano infrastructure: from the conception to the implementation

Automated Detection and Machine Learning‐Based Classification of Seismic Tremors Associated With a Non‐Volcanic Gas Emission (Mefite d’Ansanto, Southern Italy)

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