scholarly journals Noise-based passive ballistic wave seismic monitoring on an active volcano

2019 ◽  
Vol 220 (1) ◽  
pp. 501-507 ◽  
Author(s):  
Tomoya Takano ◽  
Florent Brenguier ◽  
Michel Campillo ◽  
Aline Peltier ◽  
Takeshi Nishimura
Keyword(s):  
Seismic Velocity ◽  
Active Volcano ◽  
Seismic Monitoring ◽  
Temporal Changes ◽  
Coda Wave ◽  
P Waves ◽  
Frequency Bands ◽  
Seismic Properties ◽  
Velocity Changes ◽  
Velocity Decrease

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.

scholarly journals On the use of earthquake multiplets to study fractures and the temporal evolution of an active volcano

1996 ◽  
Vol 39 (2) ◽  
Author(s):  
G. Poupinet ◽  
A. Ratdomopurbo ◽  
O. Coutant
Keyword(s):  
Seismic Velocity ◽  
Active Volcano ◽  
Temporal Changes ◽  
Time Interval ◽  
Velocity Change ◽  
P Waves ◽  
Merapi Volcano ◽  
Arrival Times ◽  
Cross Spectrum ◽  
Window Technique

Multiplets, i.e. events with similar waveforms, are common features on active volcanoes. The seismograms of multiplets are analyzed by cross-spectrum techniques: this procedure improves by a factor of about 10 the precision of differential P-arrival times and therefore the accuracy of the relative location of earthquakes. Long period events which cannot be located because of the impossibility to pick up P-waves on individual seismograms can be located with a precision of about 10 m. Such a precision permits fault planes to be mapped inside a volcanic edifice and the azimuth and strike of fractures to be defined. Seismograms of the two events (of a doublet) that occur on different dates are analyzed by the Cross Spectrum Moving Window technique (CSMW) for measuring the time delay between waves in the coda. The pattern of the delays in the coda is a function of the temporal changes of seismic velocity that occurred inside the volcano during the time interval that separates the two events of a doublet. We illustrate the potential of the doublet technique for detecting temporal changes inside a volcano by performing computations of synthetic seismograms. The case of a dyke injected inside the volcano is considered as well as that of the replenishment of a superficial magma chamber and of a general increase in velocity in the summit of the volcano. Data from Merapi volcano (Indonesia)illustrate a possible temporal velocity change inside the volcano several months before the 1992 eruption.

Effect of snowfalls on relative seismic velocity changes measured by ambient noise correlation

2021 ◽  
Author(s):  
Antoine Guillemot ◽  
Alec Van Herwijnen ◽  
Laurent Baillet ◽  
Eric Larose
Keyword(s):  
Snow Cover ◽  
Solid Earth ◽  
Ambient Noise ◽  
Seismic Velocity ◽  
Coda Wave ◽  
Noise Correlation ◽  
Geophysical Research ◽  
Seismic Velocity Changes ◽  
Velocity Changes ◽  
Seismic Measurements

<p>Seismic noise correlation is a broadly used method to monitor the subsurface, in order to detect physical processes into the surveyed medium such changes in rigidity, fluid injection or cracking <sup>(1)</sup>. The influence of several environmental variables on measured seismic observables were studied, such as temperature, groundwater level fluctuations, and freeze-thawing cycles <sup>(2)</sup>. In mountainous, cold temperate and polar sites, the presence of a snowcover can also affect relative seismic velocity changes (dV/V), but this relation is relatively poorly documented and ambiguous <sup>(3)(4)</sup>. In this study, we analyzed raw seismic recordings from a snowy flat field site located above Davos (Switzerland), during one entire winter season (from December 2018 to June 2019). Our goal was to better understand the effect of snowfall and snowmelt events on dV/V measurements through both seismic and meteorological instrumentation.</p><p>We identified three snowfall events with a substantial response of dV/V measurements (drops of several percent between 15 and 25 Hz), suggesting a detectable change in elastic properties of the medium due to the additional fresh snow.</p><p>To better interpret the measurements, we used a physical model to compute frequency dependent changes in the Rayleigh wave velocity computed before and after the events. Elastic parameters of the ground subsurface were obtained from a seismic refraction survey, whereas snow cover properties were obtained from the snow cover model SNOWPACK. The decrease in dV/V due to a snowfall were well reproduced, with the same order of magnitude than observed values, confirming the importance of the effect of fresh and dry snow on seismic measurements.</p><p>We also observed a decrease in dV/V with snowmelt periods, but we were not able to reproduce those changes with our model. Overall, our results highlight the effect of the snowcover on seismic measurements, but more work is needed to accurately model this response, in particular for the presence of liquid water in the snowcover.</p><p> </p><p><strong>References</strong></p><ul><li>(1) Larose, E., Carrière, S., Voisin, C., Bottelin, P., Baillet, L., Guéguen, P., Walter, F., et al. (2015) Environmental seismology: What can we learn on earth surface processes with ambient noise? Journal of Applied Geophysics, <strong>116</strong>, 62–74. doi:10.1016/j.jappgeo.2015.02.001</li> <li>(2) Le Breton, M., Larose, É., Baillet, L., Bontemps, N. & Guillemot, A. (2020) Landslide Monitoring Using Seismic Ambient Noise Interferometry: Challenges and Applications. Earth-Science Reviews</li> <li>(3) Hotovec‐Ellis, A.J., Gomberg, J., Vidale, J.E. & Creager, K.C. (2014) A continuous record of intereruption velocity change at Mount St. Helens from coda wave interferometry. Journal of Geophysical Research: Solid Earth, <strong>119</strong>, 2199–2214. doi:10.1002/2013JB010742</li> <li>(4) Wang, Q.-Y., Brenguier, F., Campillo, M., Lecointre, A., Takeda, T. & Aoki, Y. (2017) Seasonal Crustal Seismic Velocity Changes Throughout Japan. Journal of Geophysical Research: Solid Earth, <strong>122</strong>, 7987–8002. doi:10.1002/2017JB014307</li> </ul>

scholarly journals Seismic monitoring in the Gugla rock glacier (Switzerland): ambient noise correlation, microseismicity and modelling

2020 ◽  
Vol 221 (3) ◽  
pp. 1719-1735
Author(s):  
Antoine Guillemot ◽  
Agnès Helmstetter ◽  
Éric Larose ◽  
Laurent Baillet ◽  
Stéphane Garambois ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Active Layer ◽  
Seismic Wave ◽  
Seasonal Variations ◽  
Ambient Noise ◽  
Seismic Velocity ◽  
Seismic Monitoring ◽  
Structural Variations ◽  
Rock Glacier ◽  
Velocity Changes

SUMMARY A network of seismometers has been installed on the Gugla rock glacier since October 2015 to estimate seismic velocity changes and detect microseismicity. These two processes are related to mechanical and structural variations occurring within the rock glacier. Seismic monitoring thus allows a better understanding of the dynamics of rock glaciers throughout the year. We observed seasonal variations in seismic wave velocity and microseismic activity over the 3 yr of the study. In the first part of our analysis, we used ambient noise correlations to compute daily changes of surface wave velocity. In winter, seismic wave velocities were higher, probably due to refreezing of the permafrost active layer and cooling of the uppermost permafrost layers, leading to increased overall rigidity of the medium. This assumption was verified using a seismic model of wave propagation that estimates the depth of P- and S-wave velocity changes from 0 down to 10 m. During melting periods, both a sudden velocity decrease and a decorrelation of the seismic responses were observed. These effects can probably be explained by the increased water content of the active layer. In the second part of our study, we focused on detecting microseismic signals generated in and around the rock glacier. This seismic activity (microquakes and rockfalls) also exhibits seasonal variations, with a maximum in spring and summer, which correlates principally with an exacerbated post-winter erosional phase of the front and a faster rock glacier displacement rate. In addition, we observed short bursts of microseismicity, both during snowfall and during rapid melting periods, probably due to pore pressure increase.

Temporal changes of seismic velocity associated with a magmatic unrest of Changbaishan volcano, northeast China

2020 ◽  
Author(s):  
Zhikun Liu
Keyword(s):  
Northeast China ◽  
Seismic Velocity ◽  
Ground Deformation ◽  
Volcanic Gas ◽  
Waveform Data ◽  
Frequency Bands ◽  
Time Frequency ◽  
Changbaishan Volcano ◽  
Velocity Changes ◽  
Domain Phase

<p>The observations of seismicity, ground deformation, and volcanic gas geochemistry indicate a magmatic unrest of the Changbaishan volcano, northeast China between July 2002 and July 2005. In this study, we collected the continuous waveform data from more than 10 stations of permanent and portable networks around Changbaishan volcano area from 2000 to 2018, and studied the temporal velocity changes beneath the volcano based on both the cross-correlation of station pairs and auto-correlation of singe station method. We adopted the time-frequency domain phase weighted technique to speed up the convergence process of the noise-based Green's function, and improved the time resolution of monitoring from several tens of days to several days. We measured the temporal seismic velocity of the Changbaishan volcano in various frequency bands. The results shown that there were obvious seasonal changes of the seismic velocity for most frequency bands, and for 0.5-1 Hz frequency band a sudden velocity drop was observed starting on June 10, 2002 and the amplitude of velocity changes was up to 0.5%. After that, the number of volcanic events increased significantly. Our results suggest that there may be a precursory velocity drop phenomenon before the magma unrest, which is of great scientific significance for the studies of magma unrest and possible volcanic eruption in the future.</p>

scholarly journals Monitoring Stress-Induced Seismic Velocity Changes At SAFOD Using Crosswell Continuous Active-Source Seismic Monitoring (CASSM)

2020 ◽  
Author(s):  
Thomas Daley ◽  
Taka'aki Taira ◽  
Fenglin Niu ◽  
Pierpaolo Marchesini ◽  
Todd Wood ◽  
...  
Keyword(s):  
Seismic Velocity ◽  
Seismic Monitoring ◽  
Active Source ◽  
Seismic Velocity Changes ◽  
Velocity Changes

Rock physics analysis and time-lapse rock imaging of geochemical effects due to the injection of CO2 into reservoir rocks

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. O23-O33 ◽  
Author(s):  
Tiziana Vanorio ◽  
Amos Nur ◽  
Yael Ebert
Keyword(s):  
Seismic Velocity ◽  
Fluid Pressure ◽  
Rock Physics ◽  
Time Lapse ◽  
Seismic Monitoring ◽  
Physical Parameters ◽  
Salt Precipitation ◽  
S Wave ◽  
Seismic Properties ◽  
Small Pore

The fundamental concept of time-lapse seismic monitoring is that changes in physical parameters—such as saturation, pore fluid pressure, temperature, and stress—affect rock and fluid properties, which in turn alter the seismic velocity and density. Increasingly, however, time-lapse seismic monitoring is called upon to quantify subsurface changes due in part to chemical reactions between injected fluids and the host rocks. This study springs from a series of laboratory experiments and high-resolution images assessing the changes in microstructure, transport, and seismic properties of fluid-saturated sandstones and carbonates injected with [Formula: see text]. Results show that injecting [Formula: see text] into a brine-rock system induces chemo-mechanical mechanisms that permanently change the rock frame. Injecting [Formula: see text] into brine-saturated-sandstones induces salt precipitation primarily at grain contacts and within small pore throats. In rocks with porosity lower than 10%, salt precipitation reduces permeability and increases P- and S-wave velocities of the dry rock frame. On the other hand, injecting [Formula: see text]-rich water into micritic carbonates induces dissolution of the microcrystalline matrix, leading to porosity enhancement and chemo-mechanical compaction under pressure. In this situation, the elastic moduli of the dry rock frame decrease. The results in these two scenarios illustrate that the time-lapse seismic response of chemically stimulated systems cannot be modeled as a pure fluid-substitution problem. A first set of empirical relationships links the time-variant effects of injection to the elastic properties of the rock frame using laboratory velocity measurements and advanced imaging.

scholarly journals Petrophysical constraints on the seismic properties of the Kaapvaal craton mantle root

2013 ◽  
Vol 5 (2) ◽  
pp. 963-1005 ◽  
Author(s):  
V. Baptiste ◽  
A. Tommasi
Keyword(s):  
Seismic Anisotropy ◽  
Seismic Velocity ◽  
Body Wave ◽  
Azimuthal Anisotropy ◽  
Mantle Xenoliths ◽  
P Wave ◽  
Kaapvaal Craton ◽  
Compositional Heterogeneity ◽  
P Waves ◽  
Seismic Properties

Abstract. We calculated the seismic properties of 47 mantle xenoliths from 9 kimberlitic pipes in the Kaapvaal craton based on their modal composition, the crystal preferred orientations (CPO) of olivine, ortho- and clinopyroxene, and garnet, the Fe content of olivine, and the pressures and temperatures at which the rocks were equilibrated. These data allow constraining the variation of seismic anisotropy and velocities with depth. The fastest P wave and fast split shear wave (S1) polarization direction is always close to olivine [100] maximum. Changes in olivine CPO symmetry result in minor variations in the seismic anisotropy patterns. Seismic anisotropy is higher for high olivine contents and stronger CPO. Maximum P waves azimuthal anisotropy (AVp) ranges between 2.5 and 10.2% and S waves polarization anisotropy (AVs) between 2.7 and 8%. Seismic properties averaged in 20 km thick intervals depth are, however, very homogeneous. Based on these data, we predict the anisotropy that would be measured by SKS, Rayleigh (SV) and Love (SH) waves for 5 end-member orientations of the foliation and lineation. Comparison to seismic anisotropy data in the Kaapvaal shows that the coherent fast directions, but low delay times imaged by SKS studies and the low azimuthal anisotropy and SH faster than SV measured using surface waves may only be consistently explained by dipping foliations and lineations. The strong compositional heterogeneity of the Kaapvaal peridotite xenoliths results in up to 3% variation in density and in up to 2.3% of variation Vp, Vs and the Vp/Vs ratio. Fe depletion by melt extraction increases Vp and Vs, but decreases the Vp/Vs ratio and density. Orthopyroxene enrichment decreases the density and Vp, but increases Vs, strongly reducing the Vp/Vs ratio. Garnet enrichment increases the density, and in a lesser manner Vp and the Vp/Vs ratio, but it has little to no effect on Vs. These compositionally-induced variations are slightly higher than the velocity perturbations imaged by body-wave tomography, but cannot explain the strong velocity anomalies reported by surface wave studies. Comparison of density and seismic velocity profiles calculated using the xenoliths' compositions and equilibrium conditions to seismological data in the Kaapvaal highlights that: (i) the thickness of the craton is underestimated in some seismic studies and reaches at least 180 km, (ii) the deep sheared peridotites represent very local modifications caused and oversampled by kimberlites, and (iii) seismological models probably underestimate the compositional heterogeneity in the Kaapvaal mantle root, which occurs at a scale much smaller than the one that may be sampled seismologically.

scholarly journals Effect of the Kaikōura Earthquake on Velocity Changes In and Around the Ruptured Region: A Noise Cross-Correlation Approach

2021 ◽  
Author(s):  
◽  
Megan Kortink
Keyword(s):  
Ambient Noise ◽  
Seismic Velocity ◽  
Earthquake Sequence ◽  
Large Magnitude ◽  
Velocity Increase ◽  
Before And After ◽  
Seismic Velocity Changes ◽  
Velocity Changes ◽  
Kaikoura Earthquake ◽  
Velocity Decrease

<p>Seismic velocity changes before and after large magnitude earthquakes carry information about damage present within the faults in the surrounding region. In this thesis, temporal velocity changes are measured before and after the 2016 Kaikōura earthquake using ambient noise interferometry between 2012 - 2018. This period contains the Mw 7.8 2016 Kaikoura earthquake as well as the 2013 Cook Strait earthquake sequence and a few deep large magnitude earthquakes in 2015 - 2016. Three primary objectives are identified: (1) investigate seismic velocity changes in the Kaikōura region and their connection to the 2016 Kaikōura earthquake to try and determine if there was a change before/after the earthquake, (2) determine how this change varied across the region, and (3) consider if ambient noise can lead to improved detection and understanding of geological hazard.   The primary approach used to measure velocity changes in the Kaikōura region involved cross correlating noise recorded by seismic stations across the region. Velocity changes are sought by averaging the best result from multiple onshore station pairs. A secondary approach was also used, in which specific station pairs were averaged to determine if there were more localised velocity changes over more specific regions. This was to determine if the velocity changes observed following the 2016 Kaikōura earthquake occurred over the entire ruptured region.   Following the 2016 Kaikōura earthquake a velocity decrease of 0.24±0.02% was observed on the average of the vertical-vertical components for eight stations. The remaining eight cross-component pairs showed a smaller seismic decrease with an average value of 0.22±0.05%. After the decrease following the Kaikōura earthquake, there is a steady velocity increase of 0.13±0.02% over a one-and-a-half-year period. This indicates that prior to the earthquake, seismic velocity was at a steady state until it was perturbed by the Kaikōura earthquake, and seismic velocities rapidly decreased over all stations. Across the region, stations with a longer interstation distance and further away from ruptured faults had a smaller decrease in velocity than station pairs with a smaller interstation distance that were closer to ruptured faults. We interpret the velocity decrease following the Kaikōura earthquake as a result of cracks opening during the earthquake. The velocity increase following the earthquake is indicative of the cracks slowly healing.   The Cook Strait earthquake sequence that occurred in 2013 did not cause any velocity changes at the stations used in this thesis. This has been interpreted to be because the changes were too small compared to the background noise or the stations were not recording during the time of the earthquake sequence. Two other decreases were also observed in the region following two deep earthquakes in April 2015 (Mw 6.2, depth = 52km) and February 2016 (Mw 5.7, depth = 48km). Both of these events resulted in a small seismic decrease of 0.1±0.02%. Although these earthquakes were close to seismic stations when they occurred, they were much deeper and had a smaller magnitude than the Kaikōura earthquake so did not cause a large velocity decrease. By understanding what causes velocity changes it is possible to have an improved understanding of the geological hazard in the region.</p>

Sign in / Sign up

Export Citation Format

Share Document