MSNoise, a Python Package for Monitoring Seismic Velocity Changes Using Ambient Seismic Noise

2014 ◽  
Vol 85 (3) ◽  
pp. 715-726 ◽  
Author(s):  
T. Lecocq ◽  
C. Caudron ◽  
F. Brenguier
Keyword(s):  
Seismic Noise ◽  
Seismic Velocity ◽  
Ambient Seismic Noise ◽  
Seismic Velocity Changes ◽  
Velocity Changes ◽  
Python Package

Temporal seismic velocity changes during the 2020 rapid inflation at Mt. Thorbjorn-Svartsengi, Iceland, using ambient seismic noise

2021 ◽  
Author(s):  
Yesim Cubuk Sabuncu ◽  
Kristin Jonsdottir ◽  
Corentin Caudron ◽  
Thomas Lecocq ◽  
Michelle Maree Parks ◽  
...  
Keyword(s):  
Seismic Wave ◽  
Seismic Noise ◽  
Seismic Velocity ◽  
Ambient Seismic Noise ◽  
Magmatic Activity ◽  
Volcanic Unrest ◽  
Seismic Velocity Changes ◽  
Magmatic Intrusions ◽  
Reykjanes Peninsula ◽  
Velocity Changes

<p>The Reykjanes peninsula, SW Iceland, was struck by intense earthquake swarm activity that occurred in January-July 2020 due to repeated magmatic intrusions in the Reykjanes-Svartsengi volcanic system. GPS and InSAR observations confirmed surface deformation centered near Mt. Thorbjorn, and during the unrest period, approximately ~14,000 earthquakes (-2≤M≤4.9) were reported at the Icelandic Meteorological Office (IMO). We investigate the behavior of the crust as a response to these repeated intrusions to provide insights into volcanic unrest in the Reykjanes peninsula. Our study presents temporal seismic wave velocity variations (dv/v, in percent) based on ambient noise seismic interferometry using continuous three-component waveforms collected by IMO, (http://www.vedur.is) for the period from April 2018 to November 2020. The state-of-the-art MSNoise software package (http://www.msnoise.org) is used to calculate cross-correlations of ambient seismic noise and to quantify the relative seismic velocity variations. We observe that magmatic intrusions in the vicinity of Mt. Thorbjorn-Svartsengi have considerably reduced the seismic wave velocities (dv/v, -1%) in the 1-2 Hz frequency band. Seismic velocity changes were compared with local seismicity, GPS and InSAR data recorded close to the repeated intrusions, and modelled volumetric strain changes. We found a good correlation between the dv/v variations and the available deformation data. The Rayleigh wave phase-velocity sensitivity kernels showed that the changes occurring at depths down to ~3-4 km in the crust were captured by our measurements. We interpret the relative seismic velocity decrease to be caused by crack opening induced by intrusive magmatic activity. Monitoring the Mt. Thorbjorn-Svartsengi volcanic unrest is crucial for successful early warning of volcanic hazards since the center of uplift is only 2km away from a fishing village and major infrastructure in the area, such as water supply and geothermal power. For the first time in Iceland, we have provided near-real-time dv/v variations to obtain a more complete picture of this magmatic activity. Our findings are supported by the analysis of other primary monitoring streams. We propose that this technique may be useful for early detection of future intrusions/increased magmatic activity. This study is supported by the Icelandic Research Fund, Rannis (Grant No: 185209-051).</p>

Interpreting seismic velocity changes observed with ambient seismic noise correlations

2016 ◽  
Vol 4 (3) ◽  
pp. SJ77-SJ85 ◽  
Author(s):  
Gerrit Olivier ◽  
Florent Brenguier
Keyword(s):  
Seismic Noise ◽  
Relative Velocity ◽  
Dynamic Stress ◽  
Seismic Velocity ◽  
Ambient Seismic Noise ◽  
Seismic Velocity Changes ◽  
Velocity Variations ◽  
Velocity Changes ◽  
Pressure Changes

Recent results have shown that crosscorrelating ambient seismic noise recorded in underground mines can successfully extract the seismic Green’s function between sensors. We have revisited an earlier experiment that showed that these virtual seismic sources can be used to measure changes in seismic velocity accurately enough to monitor the short- and long-term influences of a blast in an underground mine. To use this method routinely, it is important to determine the cause of velocity variations in the absence of large dynamic stress perturbations (such as blasts). It also is important to calibrate the seismic velocity changes in terms of known stress changes so the effect of mining activities can be quantified in units that can be used by geotechnical engineers. To this end, we used coda-wave interferometry to measure relative velocity variations during times where no significant blasting or microseismic activity occurred and compared it to atmospheric air pressure changes, temperature variations, and modeled tidal strain. The results indicate that atmospheric air pressure changes have a measurable influence on the long-term seismic velocity variations at depth in the absence of large dynamic stress perturbations. This influence enabled us to determine the sensitivity of the relative velocity changes to stress, where a value of [Formula: see text] was found. This calibration essentially enables us to turn each sensor pair in an underground mine into a stress meter, paving the way for geotechnical engineers to use ambient seismic noise correlations to monitor the evolution of stress and to assess seismic hazard in conjunction with conventional microseismic methods.

Seismic velocity changes in the epicentral area of the Mw 7.8 Pedernales (Ecuador) earthquake from cross-correlation of ambient seismic noise

2020 ◽  
Author(s):  
Hans Agurto-Detzel ◽  
Diane Rivet ◽  
Philippe Charvis
Keyword(s):  
Seismic Noise ◽  
Cross Correlation ◽  
Seismic Velocity ◽  
Healing Process ◽  
Ambient Seismic Noise ◽  
Crustal Material ◽  
Seismic Velocities ◽  
Epicentral Area ◽  
Seismic Velocity Changes ◽  
Velocity Changes

<p>In the last decade, correlation of ambient seismic noise has opened a window to new possibilities for the study of structural properties of the Earth. One such possibility is the monitoring of transient changes in the mechanical properties of the surrounding crustal material following an earthquake. These changes, expressed as variations in seismic velocities, are usually associated to fracture damage and release of fluids due to the earthquakes shaking, but could also be related to deformation associated with afterslip. On April 16, 2016, a Mw 7.8 earthquake struck the coast of Ecuador, rupturing a ~100 km-long segment of the megathrust interface previously identified as highly coupled. Shortly after the mainshock, we deployed a temporary seismic network to monitor the post-seismic phase, in addition to the already in-place permanent Ecuadorian network. Here we present results from cross-correlation of continuous ambient seismic noise during a ~12-months period following the mainshock. Taking advantage of the dense and extensive station network, we investigate the spatio-temporal evolution of the post-seimic seismic velocity changes. Our results show a slow but sustained increase in the average seismic velocities after the earthquake, with a decay in the rate of the increase during the last few months. Spatially, the increase is more notorious nearby the rupture area, whereas the amplitude of the increase diminishes as we move away from the epicenter. We interpret these variations in seismic velocities (steady increase) as the crust’s response to the healing process that takes place during the post-seismic phase, following the sudden coseismic decrease of seismic velocities during the mainshock. This healing process could involve the decrease of fluid-related pore pressures and the healing of fractures and cracks generated during the mainshock, both at the interface and on the overriding plate.</p>

scholarly journals Fracture detection and imaging through relative seismic velocity changes using distributed acoustic sensing and ambient seismic noise

2017 ◽  
Vol 36 (12) ◽  
pp. 1009-1017 ◽  
Author(s):  
Stephanie R. James ◽  
Hunter A. Knox ◽  
Leiph Preston ◽  
James M. Knox ◽  
Mark C. Grubelich ◽  
...  
Keyword(s):  
Seismic Noise ◽  
Seismic Velocity ◽  
Ambient Seismic Noise ◽  
Fracture Detection ◽  
Acoustic Sensing ◽  
Seismic Velocity Changes ◽  
Distributed Acoustic Sensing ◽  
Velocity Changes

scholarly journals Monitoring southwest Greenland’s ice sheet melt with ambient seismic noise

2016 ◽  
Vol 2 (5) ◽  
pp. e1501538 ◽  
Author(s):  
Aurélien Mordret ◽  
T. Dylan Mikesell ◽  
Christopher Harig ◽  
Bradley P. Lipovsky ◽  
Germán A. Prieto
Keyword(s):  
Mass Loss ◽  
Mass Balance ◽  
Sea Level ◽  
Seismic Noise ◽  
Seismic Velocity ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Sea Level Changes ◽  
Ice Sheet Mass Balance ◽  
Velocity Changes

The Greenland ice sheet presently accounts for ~70% of global ice sheet mass loss. Because this mass loss is associated with sea-level rise at a rate of 0.7 mm/year, the development of improved monitoring techniques to observe ongoing changes in ice sheet mass balance is of paramount concern. Spaceborne mass balance techniques are commonly used; however, they are inadequate for many purposes because of their low spatial and/or temporal resolution. We demonstrate that small variations in seismic wave speed in Earth’s crust, as measured with the correlation of seismic noise, may be used to infer seasonal ice sheet mass balance. Seasonal loading and unloading of glacial mass induces strain in the crust, and these strains then result in seismic velocity changes due to poroelastic processes. Our method provides a new and independent way of monitoring (in near real time) ice sheet mass balance, yielding new constraints on ice sheet evolution and its contribution to global sea-level changes. An increased number of seismic stations in the vicinity of ice sheets will enhance our ability to create detailed space-time records of ice mass variations.

Spatial Evaluation of Pore Pressure Variations Related to Rainfall from Seismic Velocity Changes

2021 ◽  
Author(s):  
Rezkia Dewi Andajani ◽  
Takeshi Tsuji ◽  
Roel Snieder ◽  
Tatsunori Ikeda
Keyword(s):  
Pore Pressure ◽  
Negative Correlation ◽  
Ambient Noise ◽  
Seismic Velocity ◽  
Diffusion Mechanism ◽  
Velocity Change ◽  
Diffusion Parameters ◽  
The Status ◽  
Seismic Velocity Changes ◽  
Velocity Changes

<p>Crustal pore pressure, which could trigger seismicity and volcanic activity, varies with fluid invasion. Various studies have discussed the potential of using seismic velocity changes from ambient noise to evaluate pore pressure conditions, especially due to rainfall perturbations. Although the influence of rainfall on seismic velocity changes has been reported, consideration of the spatial influence on rainfall towards seismic velocity and its mechanism have not been well understood. We investigated the mechanism of rainfall-induced pore pressure diffusion in southwestern Japan, using seismic velocity change (Vs) inferred from ambient noise. We modeled pore pressure changes from rainfall data based on a diffusion mechanism at the locations where infiltration is indicated. By calculating the correlation between Vs changes and the modeled pore pressure with various hydraulic diffusion parameters, the optimum hydraulic diffusion parameter was obtained. We estimated the diffusion parameters with the highest negative correlation between pore pressure and Vs change because a negative correlation indicates pore pressure increase due to diffusion induced by groundwater load. Furthermore, the spatial variation of the hydraulic diffusivity infers the heterogeneity of the rocks in different locations. This finding suggests that the response of pore pressure induced by rainfall percolation depends on location.  We show that seismic velocity monitoring can be used to evaluate the status of pore pressure at different locations, which is useful for fluid injection, CO<sub>2</sub> wellbore storage, and geothermal development.</p>

Can land subsidence be monitored with ambient seismic auto-correlations?

2021 ◽  
Author(s):  
Laura Ermert ◽  
Marine Denolle ◽  
Enrique Cabral Cano ◽  
Estelle Chaussard ◽  
Dario Solano Rojas
Keyword(s):  
Ambient Noise ◽  
Seismic Velocity ◽  
Urban Infrastructure ◽  
Temporal Correlations ◽  
Long Term Effect ◽  
Seismic Velocity Changes ◽  
Subsurface Layers ◽  
Velocity Changes ◽  
Seasonal Oscillations

<p>Mexico City has been undergoing rapid subsidence for more than 100 years due to groundwater extraction. During the 2010s, rates surpassing 30 centimeters/year were observed by satellite geodetic measurements. Not only does this subsidence pose grave challenges for buildings, urban infrastructure, and water management, but it also changes the seismic response of the affected subsurface layers and thereby alters the seismic hazard in the metropolis that has seen devastating site effects both in the 1985 Michoacan and 2017 Puebla earthquake. We use data and numerical modeling of ambient noise auto-correlations to gain a better insight into the subsidence process through ambient noise techniques.</p><p>We establish a baseline for the long-term and seasonal variations of seismic velocity near the basin from long-term recordings of the Geoscope station UNM, located at the Universidad Nacional Autónoma de México in the geotechnical hill zone. We further study temporary recordings from the MASE array (MASE (2007): Meso America Subduction Experiment. Caltech. Dataset. doi:10.7909/C3RN35SP) to see how subsidence and other factors may influence seismic velocity in the geotechnical hill, transition, and lake zones.</p><p>We find that seasonal oscillations and a strong, rapid velocity drop coincident with the 2017 Puebla earthquake overlay a multi-year increasing trend in seismic velocity. We cautiously interpret the multi-year increase as a long-term effect of subsidence. We further study the temporal correlations of seismic velocity changes with other environmental time series like precipitation, and model auto-correlations in order to improve our understanding of their composition and sensitivity.</p>

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>

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