Noise-based passive ballistic wave seismic monitoring on an active volcano
25
Citation
37
Reference
10
Related Paper
Citation Trend
Abstract:
SUMMARY Monitoring temporal changes of volcanic interiors is important to understand magma, fluid pressurization and transport leading to eruptions. Noise-based passive seismic monitoring using coda wave interferometry is a powerful tool to detect and monitor very slight changes in the mechanical properties of volcanic edifices. However, the complexity of coda waves limits our ability to properly image localized changes in seismic properties within volcanic edifices. In this work, we apply a novel passive ballistic wave seismic monitoring approach to examine the active Piton de la Fournaise volcano (La Réunion island). Using noise correlations between two distant dense seismic arrays, we find a 2.4 per cent velocity increase and −0.6 per cent velocity decrease of Rayleigh waves at frequency bands of 0.5–1 and 1–3 Hz, respectively. We also observe a −2.2 per cent velocity decrease of refracted P waves at 550 m depth at the 6–12 Hz band. We interpret the polarity differences of seismic velocity changes at different frequency bands and for different wave types as being due to strain change complexity at depth associated with subtle pressurization of the shallow magma reservoir. Our results show that velocity changes measured using ballistic waves provide complementary information to interpret temporal changes of the seismic properties within volcanic edifices.Keywords:
Coda
Seismic Noise
Rayleigh Wave
Microseism
Seismic interferometry
Ambient noise level
Dispersive body waves
Seismic array
Passive seismic
Abstract We propose a new approach for imaging the subsurface using a stochastic wavefield of interface waves present in the ambient seismic field. Unlike seismic interferometry, our technique does not rely on cross correlations to obtain the Green's function between two seismic receivers. Rather, it relies on the local measurements of phase velocity obtained directly from the ratio between second‐order temporal and spatial derivatives of the wavefield. We process 10 min of ambient seismic noise recording made using a large and dense array installed over Ekofisk. We image a subsidence‐induced geomechanical imprint on the Scholte wave phase velocities in the near surface. This resulting phase velocity pattern is verified by comparison to results from a seismic‐noise cross‐correlation tomography.
Seismic interferometry
Seismic Noise
Passive seismic
Ambient noise level
Seismic array
Phase velocity
Seismic velocity
Vertical seismic profile
Cite
Citations (36)
Abstract. Ambient noise seismology has revolutionized seismic characterization of the Earth's crust from local to global scales. The estimate of Green's function (GF) between two receivers, representing the impulse response of elastic media, can be reconstructed via cross-correlation of the ambient noise seismograms. A homogenized wave field illuminating the propagation medium in all directions is a prerequisite for obtaining an accurate GF. For seismic data recorded on glaciers, this condition imposes strong limitations on GF convergence because of minimal seismic scattering in homogeneous ice and limitations in network coverage. We address this difficulty by investigating three patterns of seismic wave fields: a favorable distribution of icequakes and noise sources recorded on a dense array of 98 sensors on Glacier d'Argentière (France), a dominant noise source constituted by a moulin within a smaller seismic array on the Greenland Ice Sheet, and crevasse-generated scattering at Gornergletscher (Switzerland). In Glacier d'Argentière, surface melt routing through englacial channels produces turbulent water flow, creating sustained ambient seismic sources and thus favorable conditions for GF estimates. Analysis of the cross-correlation functions reveals non-equally distributed noise sources outside and within the recording network. The dense sampling of sensors allows for spatial averaging and accurate GF estimates when stacked on lines of receivers. The averaged GFs contain high-frequency (>30 Hz) direct and refracted P waves in addition to the fundamental mode of dispersive Rayleigh waves above 1 Hz. From seismic velocity measurements, we invert bed properties and depth profiles and map seismic anisotropy, which is likely introduced by crevassing. In Greenland, we employ an advanced preprocessing scheme which includes match-field processing and eigenspectral equalization of the cross spectra to remove the moulin source signature and reduce the effect of inhomogeneous wave fields on the GFs. At Gornergletscher, cross-correlations of icequake coda waves show evidence for homogenized incident directions of the scattered wave field. Optimization of coda correlation windows via a Bayesian inversion based on the GF cross coherency and symmetry further promotes the GF estimate convergence. This study presents new processing schemes on suitable array geometries for passive seismic imaging and monitoring of glaciers and ice sheets.
Seismic interferometry
Passive seismic
Seismic Noise
Ambient noise level
Seismic array
Rayleigh Wave
Cross-correlation
Cite
Citations (44)
A small scale field trial of a buried receiver array is used to generate passive recordings during a period of minimal human activity at the site of the array. We carefully analyse the data to reveal a number of valuable insights. In particular, we find that shallow burial of the geophones improves noise levels significantly and in a strongly frequency dependent manner. By isolating ambient seismic noise, which is a significant noise contribution in the frequency range from 3Hz to 30Hz, we show it is possible to utilize this seismic energy for the purpose of deep imaging. We successfully use advanced techniques of seismic interferometry to produce images to reservoir depth (~2km) and below, which show very good agreement with 3D seismic images taken on site.
Geophone
Ambient noise level
Passive seismic
Seismic interferometry
Seismic Noise
Seismic array
Cite
Citations (1)
We introduce the single-station cross-correlation (SC) technique of processing ambient seismic noise and compare its results with the established cross-correlation (CC) and autocorrelation (AC) techniques. While CC is the correlation of the signals of two seismic stations with each other and AC is the correlation of a signal with itself, SC is the correlation of two different components of a single three-component seismic sensor. The comparison of the three different correlation techniques shows that CCs give the best results at frequencies below 0.5 Hz and that SCs give the best results at higher frequencies. In all three processing techniques, ambient seismic noise is correlated in order to reconstruct the Green's function describing the wave propagation between the first and the second sensor. By relating the coda parts of the daily Green's functions with the long-term reference Green's functions, shear wave velocity changes are determined. Here, we apply this technique to the data of 20 seismic stations in the surroundings of the fault zone of the Iwate-Miyagi Nairiku earthquake (MW = 6.9), which occurred on 2008 June 13, UTC (2008 June 14, Japan Standard Time) in the northern part of the Japanese island Honshu. The data range from 2008 January to 2011 June and therefore include the Tohoku earthquake (MW = 9.0), which occurred on 2011 March 11, off the coast of northern Honshu. The data are analysed in five different frequency ranges between 0.125 and 4.0 Hz. The data show coseismic velocity changes for both earthquakes followed by a post-seismic velocity recovery. In general, the coseismic velocity changes increase with frequency. For the Iwate-Miyagi Nairiku earthquake, the strongest velocity changes occur close to the fault zone. Quickly recovering coseismic velocity changes can be separated from changes not recovering during the study period. For the Tohoku earthquake, the complete area is affected by coseismic velocity changes. A modelling of the depth of the coseismic velocity changes indicates that the Iwate-Miyagi Nairiku earthquake can be explained either by large shallow velocity changes or by small, but deep changes. For one station, the observations can only be explained by assuming deeper changes. For the Tohoku earthquake, the modelling shows that different parts of the study area are affected in different ways, some showing shallow changes, others deeper changes. Furthermore, seasonal velocity variations occur, which are compatible for the different stations above 0.5 Hz, with velocity maxima in autumn.
Seismic Noise
Cross-correlation
Seismic interferometry
Ambient noise level
Passive seismic
Seismometer
Coda
Seismic array
Cite
Citations (78)
Coda-wave interferometry is a technique to detect small seismic velocity changes using phase changes in similar waveforms from repeating natural or artificial sources. Seismic interferometry is another technique for detecting seismic velocity changes from cross-correlation functions of ambient seismic noise. We simultaneously use these two techniques to clarify seismic velocity changes at Sakurajima volcano, one of the most active volcanoes in Japan, examining the two methods. We apply coda-wave interferometry to the records of repeated active seismic experiments conducted once a year from 2011 to 2014, and seismic interferometry to the ambient seismic noise data. We directly compare seismic velocity changes from these two techniques. In coda-wave interferometry analyses, we detect significant seismic velocity increases between 2011 and 2013, and seismic velocity decreases between 2013 and 2014 at the northern and eastern flanks of the volcano. The absolute values are at a maximum 0.47 ± 0.06% for 2–4 Hz, 0.24 ± 0.03% for 4–8 Hz, and 0.15 ± 0.03% for 8–16 Hz, respectively. In seismic interferometry analyses, vertical–vertical cross-correlations in 1–2, 2–4, and 4–8 Hz bands indicate seismic velocity increases and decreases during 3 years of 2012–2014 with the maximum amplitudes of velocity change of ±0.3% for 1–2 Hz, ±0.4% for 2–4 Hz, and ±0.2% for 4–8 Hz, respectively. Relative velocity changes indicate the almost annual change. These periodical changes are well matched with volcano deformation detected by GNSS receivers deployed around the volcano. We compare the results from coda-wave interferometry with those from seismic interferometry on the shot days and find that most of them are consistent. This study illustrates that the combined use of coda-wave interferometry and seismic interferometry is useful to obtain accurate and continuous measurements of seismic velocity changes.
Coda
Seismic interferometry
Seismic Noise
Ambient noise level
Seismic velocity
Passive seismic
Seismic array
Vertical seismic profile
Cite
Citations (17)
A critical consideration in the design of next generation gravitational wave detectors is the understanding of the seismic environment that can introduce coherent and incoherent noise of seismic origin at different frequencies. We present detailed low-frequency ambient seismic noise characterization (0.1--10~Hz) at the Gingin site in Western Australia. Unlike the microseism band (0.06--1~Hz) for which the power shows strong correlations with nearby buoy measurements in the Indian Ocean, the seismic spectrum above 1~Hz is a complex superposition of wind induced seismic noise and anthropogenic seismic noise which can be characterized using beamforming to distinguish between the effects of coherent and incoherent wind induced seismic noise combined with temporal variations in the spatio-spectral properties of seismic noise. This also helps characterizing the anthropogenic seismic noise. We show that wind induced seismic noise can either increase or decrease the coherency of background seismic noise for wind speeds above 6~m/s due to the interaction of wind with various surface objects. In comparison to the seismic noise at the Virgo site, the secondary microseism (0.2~Hz) noise level is higher in Gingin, but the seismic noise level between 1 and 10~Hz is lower due to the sparse population and absence of nearby road traffic.
Seismic Noise
Microseism
Ambient noise level
Passive seismic
Dispersive body waves
Seismic array
Vertical seismic profile
Cite
Citations (0)
Abstract In traditional surface wave tomography based on seismic noise, 2D phase or group velocity distribution is obtained by performing pure‐path inversion after extracting interstation velocities based on the noise cross‐correlation function. In this paper, we show that 2D surface wave phase velocity maps of adequate quality can be obtained directly, without interferometry, by beamforming the ambient noise recorded at array of stations. This method does not require a good azimuthal distribution of the noise sources. The 2D surface wave phase velocity map is obtained by moving the subarrays within a larger dense network of stations. The method is illustrated with seismic noise recorded by over 600 stations of the ChinArray (Phase II). We obtain 2D Rayleigh wave phase velocity maps between 7 and 35 s in Northeastern (NE) Tibetan Plateau and adjacent regions that compare well with results obtained with other methods. The shear wave velocity model is then derived by inverting the phase velocity with depth. The model correlates well with geology and tectonics in NE Tibet. Two clear mid‐to‐low crustal low‐velocity zones are observed at 15‐ to 35‐km depth beneath the Songpan‐Ganzi terrane and Northwestern Qilian Orogen, possibly facilitating lower crustal flow in this key region for the tectonic evolution of NE Tibet.
Seismic Noise
Rayleigh Wave
Passive seismic
Seismic interferometry
Seismic Tomography
Seismic array
Phase velocity
Ambient noise level
Cite
Citations (31)
Passive seismic interferometry is a new promising methodology for seismic exploration. Interferometry allows information about the subsurface structure to be extracted from ambient seismic noise. In this study, we apply the cross-correlation technique to approximately 25 hr of recordings of ambient seismic noise at the Ketzin experimental CO2 storage site, Germany. Common source gathers were generated from the ambient noise for all available receivers along two seismic lines by cross-correlation of noise records. This methodology isolates the interstation Green's functions that can be directly compared to active source gathers. We show that the retrieved response includes surface waves, refracted waves and reflected waves. We use the dispersive behaviour of the retrieved surface waves to infer geological properties in the shallow subsurface and perform passive seismic imaging of the subsurface structure by processing the retrieved reflected waves.
Seismic interferometry
Seismic Noise
Ambient noise level
Passive seismic
Vertical seismic profile
Cross-correlation
Cite
Citations (54)
SUMMARY We present a new processing scheme that uses passive seismic interferometry (PSI) followed by multichannel analysis of surface waves (MASW), which we call the 2-D PSI-MASW method, to obtain Rayleigh wave phase velocity dispersion (PVD) information. In this scheme, we first use the principles of PSI to form multidirectional cross-correlations (CCs) then project the CCs onto a 1-D virtual array and apply the phase-shift transform as in MASW processing. We compare PVD information obtained by this method with those of the conventional beam-power based frequency–wavenumber decomposition (CVFK) method using ambient seismic noise (ASN) data collected by local-scale 2-D arrays deployed at three selected sites in Bursa, Turkey. By analysing the ASN data from these sites, we show that similar multimodal PVD curves can be obtained with the two methods over a broad frequency range (∼2–23 Hz) within the wavenumber resolution and aliasing limits. However, in one of our sites where the 2-D array configuration has a considerable antisymmetry, we show that the 1-D virtual array used in the 2-D PSI-MASW method has a better array response function in terms of wavenumber resolution and suppression of side-lobes leading to superior mode resolution and separation than that of the CVFK method, which shows strong directional variations. Furthermore, unlike the CVFK method, the 2-D PSI-MASW method takes advantage of temporal stacking of CCs ensuring weak but coherent Rayleigh wave signals present in the ASN wavefield to be strengthened and has the potential for better extraction of PVD information. We conclude that by using a 2-D array with spatial coverage providing a wide range of directions and distances, reliable PVD information can be obtained even if the ASN sources are not concentrated in the stationary phase zones. Thus, we suggest that the 2-D PSI-MASW method is highly advantageous for the extraction of reliable PVD information owing to the multidirectional CCs provided by the 2-D array configurations. We also report that using only a single receiver line in the interferometric approach results in biased and/or incomplete PVD information due to the non-isotropic ASN source distribution at all three sites we analysed. In conclusion, our results clearly indicate that the 2-D PSI-MASW method can be used as complementary or alternative to the CVFK method to extract multimodal Rayleigh wave PVD information in local-scale seismological studies.
Wavenumber
Passive seismic
Seismic interferometry
Seismic Noise
Ambient noise level
Rayleigh Wave
Seismogram
Seismic array
Aliasing
Cite
Citations (1)
Abstract Application of distributed acoustic sensing (DAS) in seismic studies has benefited from its high-density acquisition, environmental adaptation, and low-cost deployment. Nevertheless, the great potential of such observations in seismic research across scales is far from explicit. To test the feasibility of DAS for small-scale seismic monitoring in the urban city, we conducted a one-week field experiment with three ∼72 m long fiber-optic cables, and eight seismometers at the campus of southern marine science and engineering Guangdong laboratory (Guangzhou). Stable high-frequency (2–8 Hz) noise correlation functions (NCFs) were successfully retrieved between DAS channels from continuous in situ noise recording. The observed NCFs are highly asymmetrical, indicating the nonuniform distribution of the noise sources. Beamforming analysis of the seismic data demonstrates that the noise sources are stable daily with consistent direction and slowness. Temporal variation of the NCFs shows that the observed stable signals emerge simultaneously with the machinery operating time of the campus. NCF modeling with spatially varying source spectra reveals that a localized source in the nearby office building fitted the observations well. Accordingly, ground vibration of operating machinery is suggested to account for the temporal and spatial features retrieved from the observed NCFs. Our study demonstrates that DAS has great potential in high-resolution source localization and characterization, as well as temporal monitoring (∼hours) using urban anthropogenic seismic sources.
Slowness
Seismometer
Seismic Noise
Seismic interferometry
Passive seismic
Ambient noise level
Geophone
Distributed Acoustic Sensing
Seismic array
Cite
Citations (4)