Statistics of inter-time of Strombolian explosion-quakes

Bottiglieri, M.; Martino, Salvatore; Falanga, M.; Godano, C.; Palo, M.

doi:10.1209/epl/i2005-10258-0

Cited by 22 publications

(26 citation statements)

References 10 publications

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“…Our results lead us to conclude that the basic seismic signature of steady state activity of Stromboli is the volcanic tremor. The explosion quakes are generated when there is the formation of a large bubble in the magmatic system due to the coalescence phenomenon [e.g., Bottiglieri et al , 2005]. We note that in Chouet et al [2003], among many results obtained by inverting seismic moment tensor and a single force distribution of a point source, the authors have shown that the size of the explosion quake signals can be directly associated to the slug sizes.…”

Section: Resultsmentioning

confidence: 99%

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Model for high‐frequency Strombolian tremor inferred by wavefield decomposition and reconstruction of asymptotic dynamics

et al. 2008

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[1] We study the volcanic tremor time series recorded by a broadband three-component seismic network installed at Stromboli volcano during 1997. By using decomposition methods in both frequency and time domains, we prove that Strombolian tremor can be described as a linear combination of nonlinear signals in time domain. These ''components'' are similar to those obtained for explosion quakes, with the only difference being the amplitude enhancement. We characterize each of these nonlinear signals both in terms of their wavefield properties as well as dynamic systems. Moreover, we take into account the complex processes of magma flow and turbulent degassing, looking at time and amplitude modulation of tremor on a suitable scale. The distribution of tremor amplitudes is Gaussian while the intertimes between the maxima in a suitable scale are described by a Poisson clustered process. Starting from these analyses, a first approximate model for volcanic tremor field can be deduced. The recorded signals, i.e., the elastic vibrations at a point, can be described by a nonlinear equation which gives limit cycles (different observed ''nonlinear modes''). This equation is governed by a time-dependent threshold which represents the variability of bubble flux. We take into account some inelasticity in the medium perturbing the elastic potential with a Gaussian function on a suitable scale. It acts as a radiance function modulating the frequency of the limit cycle. This proposed model is able to reproduce waveform, Fourier spectrum, and phase space dimension of one of the extracted nonlinear wave packets.

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Section: Resultsmentioning

confidence: 99%

“…During the experiment, the Strombolian activity was particularly intense. The time interval between explosions (“intertime”) was about 3 min [ Bottiglieri et al , 2005]. This implies tremor duration lasting from 30 s to 15 min.…”

Section: Data Setmentioning

confidence: 99%

Model for high‐frequency Strombolian tremor inferred by wavefield decomposition and reconstruction of asymptotic dynamics

et al. 2008

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“…These will remain trapped in the mud (at rest in the conduit) until their size reaches any critical dimension (for instance, by coalescence of diffusing particles; e.g. Bottiglieri et al, 2005), allowing their uprise. If this occurs at a relatively shallow depth and if the density of the bubbles is not large enough, coalescence is also limited and this also prevents the formation of larger bubbles or slugs.…”

Section: Discussionmentioning

confidence: 99%

Monitoring methane emission of mud volcanoes by seismic tremor measurements: a pilot study

Albarello

Palo

Martinelli

2012

Nat. Hazards Earth Syst. Sci.

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Abstract.A new approach for estimating methane emission at mud volcanoes is here proposed based on measurements of the seismic tremor on their surface. Data obtained at the Dashgil mud volcano in Azerbaijan reveal the presence of energy bursts characterized by well-determined features (i.e. waveforms, spectra and polarization properties) that can be associated with bubbling at depth. Counting such events provides a possible tool for monitoring gas production in the reservoir, thus minimizing logistic troubles and representing a cheap and effective alternative to more complex approaches. Specifically, we model the energy bursts as the effect of resonant gas bubbles at depth. This modelling allows to estimate the dimension of the bubbles and, consequently, the gas outflow from the main conduit in the assumption that all emissions from depth occur by bubble uprising. The application of this model to seismic events detected at the Dashgil mud volcano during three sessions of measurements carried out in 2006 and 2007 provides gas flux estimates that are in line with those provided by independent measurements at the same structure. This encouraging result suggests that the one here proposed could be considered a new promising, cheap and easy to apply tool for gas flux measurements in bubbling gas seepage areas.

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“…It is known as "Strombolian activity". The seismic wavefield of the Stromboli volcano has been investigated, focusing the attention on the explosion quakes (Chouet et al, 1997(Chouet et al, , 1998Del Pezzo et al, 1992;Acernese et al, 2003Acernese et al, , 2004Bottiglieri et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Statistical analysis of Stromboli VLP tremor in the band [0.1–0.5] Hz: some consequences for vibrating structures

Lauro

Martino

Falanga

et al. 2006

Nonlin. Processes Geophys.

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Abstract.We analyze time series of Strombolian volcanic tremor, focusing our attention on the frequency band [0.1-0.5] Hz (very long period (VLP) tremor). Although this frequency band is largely affected by noise, we evidence two significant components by using Independent Component Analysis with the frequencies, respectively, of ∼0.2 and ∼0.4 Hz. We show that these components display wavefield features similar to those of the high frequency Strombolian signals (>0.5 Hz). In fact, they are radially polarised and located within the crater area. This characterization is lost when an enhancement of energy appears. In this case, the presence of microseismic noise becomes relevant. Investigating the entire large data set available, we determine how microseismic noise influences the signals. We ascribe the microseismic noise source to Scirocco wind. Moreover, our analysis allows one to evidence that the Strombolian conduit vibrates like the asymmetric cavity associated with musical instruments generating self-sustained tones.

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Statistics of inter-time of Strombolian explosion-quakes

Cited by 22 publications

References 10 publications

Model for high‐frequency Strombolian tremor inferred by wavefield decomposition and reconstruction of asymptotic dynamics

Model for high‐frequency Strombolian tremor inferred by wavefield decomposition and reconstruction of asymptotic dynamics

Monitoring methane emission of mud volcanoes by seismic tremor measurements: a pilot study

Statistical analysis of Stromboli VLP tremor in the band [0.1–0.5] Hz: some consequences for vibrating structures

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