PARTOS - Passive and Active Ray TOmography Software: description and preliminary analysis using TOMO-ETNA experiment’s dataset

Díaz‐Moreno, Alejandro; Koulakov, Ivan; García-Yeguas, Araceli; Jakovlev, Andrey; Barberi, G.; Cocina, O.; Zuccarello, Luciano; Scarfì, L.; Patané, Domenico; Álvarez, Isaac; García, Luz; Benítez, Carmen; Prudencio, Janire; Ibáñez, Jesús M.

doi:10.4401/ag-7088

Cited by 4 publications

(4 citation statements)

References 42 publications

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“…308665), together with active seismic tomography experiment at MT. Etna -TOMO-ETNA [see in this volume: Coltelli et al 2016;Díaz-Moreno et al 2016;Ibáñez et al 2016aIbáñez et al , 2016b. We used the spatial auto-correlation method (SPAC) introduced by Aki [1957Aki [ , 1965 and later generalised by Henstridge [1979] and Cho et al [2004], to estimate dispersion curves of surface waves.…”

Section: Introductionmentioning

confidence: 99%

Shallow velocity model in the area of Pozzo Pitarrone, Mt. Etna, from single station, array methods and borehole data

Zuccarello

Paratore

Rocca

et al. 2016

Annals of Geophysics

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<p>Seismic noise recorded by a temporary array installed around Pozzo Pitarrone, NE flank of Mt. Etna, have been analysed with several techniques. Single station HVSR method and SPAC array method have been applied to stationary seismic noise to investigate the local shallow structure. The inversion of dispersion curves produced a shear wave velocity model of the area reliable down to depth of about 130 m. A comparison of such model with the stratigraphic information available for the investigated area shows a good qualitative agreement. Taking advantage of a borehole station installed at 130 m depth, we could estimate also the P-wave velocity by comparing the borehole recordings of local earthquakes with the same event recorded at surface. Further insight on the P-wave velocity in the upper 130 m layer comes from the surface reflected wave observable in some cases at the borehole station. From this analysis we obtained an average P-wave velocity of about 1.2 km/s, compatible with the shear wave velocity found from the analysis of seismic noise.</p>

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Section: Introductionmentioning

confidence: 99%

Shallow velocity model in the area of Pozzo Pitarrone, Mt. Etna, from single station, array methods and borehole data

Zuccarello

Paratore

Rocca

et al. 2016

Annals of Geophysics

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“…(2020) showed that pure compressional signals convert to shear after a few mean free paths from the signal origin. However, the first arrivals remain purely compressional (Díaz‐Moreno et al., 2016, 2018; García et al., 2016). Using a 1 s window guarantied that we obtained pure direct P waves.…”

Section: Methods and Seismic Datamentioning

confidence: 99%

“…Approximately 9700 air‐gun shots were generated in the Ionian and Tyrrhenian Seas, and the data were used in perform high‐resolution seismic tomography using the wide‐angle seismic refraction method (Díaz‐Moreno et al. 2016, 2018). The vessel‐mounted air‐gun array shoots with a power capacity of up to 5,200 cubic inches.…”

Section: Methods and Seismic Datamentioning

confidence: 99%

“…As detailed in Coltelli et al (2016), the survey was conducted from aboard the "Sarmiento de Gamboa" Spanish oceanographic vessel in June 2014. Approximately 9700 air-gun shots were generated in the Ionian and Tyrrhenian Seas, and the data were used in perform high-resolution seismic tomography using the wide-angle seismic refraction method (Díaz-Moreno et al 2016. The vessel-mounted air-gun array shoots with a power capacity of up to 5,200 cubic inches.…”

Section: Seismic Datamentioning

confidence: 99%

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Shallow Magma Storage Beneath Mt. Etna: Evidence From New Attenuation Tomography and Existing Velocity Models

et al. 2021

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Determining the location and size of potential magma reservoirs is crucial to constrain the size of future eruptions or eruptive frequency. Magma accumulation and melt migration have been the focus of extensive research at Mt. Etna volcano. Recent geophysical imaging of Mt. Etna has shown the growing importance of several geological bodies in explaining the migration of eruptive materials inside the volcano. One such body, known as the High Velocity Body (HVB), is a highly consolidated structure located below the central-southern part of the volcano. The HVB has been observed in several tomography studies (Giampiccolo et al., 2020 and references therein) and is interpreted as a massive accumulation of intrusions within the sedimentary basement. In addition, new structural elements have been identified tomographically to the west and southwest of the main volcanic edifice (e.g., Díaz-Moreno et al., 2018 and references therein). Despite not being widely discussed and interpreted in studies based on travel time tomography, these bodies have been well resolved using other techniques. In addition, recent studies (Alparone et al., 2015;Barberi et al., 2016) have found a strong association between deep seismicity beneath Mt. Etna and these geological objects, indicating the need for further study. Apparent contradictions between older and newer tomographic images possibly reflect the increased sensitivity of new tomography techniques to rock heterogeneity

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One hundred years of advances in volcano seismology and acoustics

Matoza

Roman

2022

Bull Volcanol

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Since the 1919 foundation of the International Association of Volcanology and Chemistry of the Earth’s Interior (IAVCEI), the fields of volcano seismology and acoustics have seen dramatic advances in instrumentation and techniques, and have undergone paradigm shifts in the understanding of volcanic seismo-acoustic source processes and internal volcanic structure. Some early twentieth-century volcanological studies gave equal emphasis to barograph (infrasound and acoustic-gravity wave) and seismograph observations, but volcano seismology rapidly outpaced volcano acoustics and became the standard geophysical volcano-monitoring tool. Permanent seismic networks were established on volcanoes (for example) in Japan, the Philippines, Russia, and Hawai‘i by the 1950s, and in Alaska by the 1970s. Large eruptions with societal consequences generally catalyzed the implementation of new seismic instrumentation and led to operationalization of research methodologies. Seismic data now form the backbone of most local ground-based volcano monitoring networks worldwide and play a critical role in understanding how volcanoes work. The computer revolution enabled increasingly sophisticated data processing and source modeling, and facilitated the transition to continuous digital waveform recording by about the 1990s. In the 1970s and 1980s, quantitative models emerged for long-period (LP) event and tremor sources in fluid-driven cracks and conduits. Beginning in the 1970s, early models for volcano-tectonic (VT) earthquake swarms invoking crack tip stresses expanded to involve stress transfer into the wall rocks of pressurized dikes. The first deployments of broadband seismic instrumentation and infrasound sensors on volcanoes in the 1990s led to discoveries of new signals and phenomena. Rapid advances in infrasound technology; signal processing, analysis, and inversion; and atmospheric propagation modeling have now established the role of regional (15–250 km) and remote (> 250 km) ground-based acoustic systems in volcano monitoring. Long-term records of volcano-seismic unrest through full eruptive cycles are providing insight into magma transport and eruption processes and increasingly sophisticated forecasts. Laboratory and numerical experiments are elucidating seismo-acoustic source processes in volcanic fluid systems, and are observationally constrained by increasingly dense geophysical field deployments taking advantage of low-power, compact broadband, and nodal technologies. In recent years, the fields of volcano geodesy, seismology, and acoustics (both atmospheric infrasound and ocean hydroacoustics) are increasingly merging. Despite vast progress over the past century, major questions remain regarding source processes, patterns of volcano-seismic unrest, internal volcanic structure, and the relationship between seismic unrest and volcanic processes.

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PARTOS - Passive and Active Ray TOmography Software: description and preliminary analysis using TOMO-ETNA experiment’s dataset

Cited by 4 publications

References 42 publications

Shallow velocity model in the area of Pozzo Pitarrone, Mt. Etna, from single station, array methods and borehole data

Shallow velocity model in the area of Pozzo Pitarrone, Mt. Etna, from single station, array methods and borehole data

Shallow Magma Storage Beneath Mt. Etna: Evidence From New Attenuation Tomography and Existing Velocity Models

One hundred years of advances in volcano seismology and acoustics

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