Seismic Monitoring of Permafrost in Svalbard, Arctic Norway

Author(s):  
Julie Albaric ◽  
Daniela Kühn ◽  
Matthias Ohrnberger ◽  
Nadège Langet ◽  
Dave Harris ◽  
...  

Abstract We analyze data from passive and active seismic experiments conducted in the Adventdalen valley of Svalbard in the Norwegian Arctic. Our objective is to characterize the ambient wavefield of the region and to investigate permafrost dynamics through estimates of seismic velocity variations. We are motivated by a need for early geophysical detection of potentially hazardous changes to permafrost stability. We draw upon several data sources to constrain various aspects of seismic wave propagation in Adventdalen. We use f-k analysis of five years of continuous data from the Spitsbergen seismic array (SPITS) to demonstrate that ambient seismic noise on Svalbard consists of continuously present body waves and intermittent surface waves appearing at regular intervals. A change in wavefield direction accompanies the sudden onset of surface waves when the average temperature rises above the freezing point, suggesting a cryogenic origin. This hypothesis is supported further by our analysis of records from a temporary broadband network, which indicates that the background wavefield is dominated by icequakes. Synthetic Green’s functions calculated from a 3D velocity model match well with empirical Green’s functions constructed from the recorded ambient seismic noise. We use a shallow shear-wave velocity model, obtained from active seismic measurements, to estimate the maximum depth of Rayleigh wave sensitivity to changes in shear velocity to be in the 50–100 m range. We extract seasonal variations in seismic velocities from ambient noise cross-correlation functions computed over three years of SPITS data. We attribute relative velocity variations to changes in the ice content of the shallow (2–4 m depth) permafrost, which is sensitive to seasonal temperature changes. A linear decreasing trend in seismic velocity is observed over the years, most likely due to permafrost warming.

Author(s):  
Tianshi Liu ◽  
Haiming Zhang

The cross-correlations of ambient noise or earthquake codas are massively used in seismic tomography to measure the dispersion curves of surface waves and the travel times of body waves. Such measurements are based on the assumption that these kinematic parameters in the cross-correlations of noise coincide with those in Green's functions. However, the relation between the cross-correlations of noise and Green's functions deserves to be studied more precisely. In this paper, we use the asymptotic analysis to study the dispersion relations of surface waves and the travel times of body waves, and come to the conclusion that for the spherically symmetric Earth model, when the distribution of noise sources is laterally uniform, the dispersion relations of surface waves and the travel times of SH body-wave phases in noise correlations should be exactly the same as those in Green's functions.


2016 ◽  
Vol 4 (3) ◽  
pp. SJ77-SJ85 ◽  
Author(s):  
Gerrit Olivier ◽  
Florent Brenguier

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.


Geophysics ◽  
2012 ◽  
Vol 77 (4) ◽  
pp. KS13-KS31 ◽  
Author(s):  
Alexander Goertz ◽  
Barbara Schechinger ◽  
Benjamin Witten ◽  
Matthias Koerbe ◽  
Paul Krajewski

We analyzed ambient seismic noise from a broadband passive seismic survey acquired in an urban area in Germany. Despite a high level of anthropogenic noise, we observe lateral variations in the quasi-stationary spectra that are of natural origin and indicative of the subsurface in the survey area. The best diagnostic is the ellipticity spectrum which is the spectral ratio of the vertical over the horizontal components. Deviations of the observed spectra from a pure Rayleigh-wave ellipticity allow an approximate separation of surface-wave from body-wave components in the analyzed frequency range, distinguishing shallow (upper tens of meters) from deeper (upper three kilometers) subsurface effects. We observe an increase of vertically polarized body waves between 1 and 4 Hz that is correlated to a subsurface structure that contains an oil reservoir at about 2-km depth. We located the source of the observed body wave microtremor in depth by applying an elastic wavefield back projection and imaging technique. The method includes normalization by the impulse response of the velocity model, effects of the receiver geometry, and lateral variation of incoherent noise. The source region of the low-frequency body wave microtremor is centered above the location of the oil reservoir. Two possible explanations for the deep microtremor are elastic body-wave scattering due to the impedance contrast of the structural trap, and viscoelastic scattering due to poroelastic effects in the partially saturated reservoir.


1967 ◽  
Vol 57 (1) ◽  
pp. 55-81
Author(s):  
E. J. Douze

abstract This report consists of a summary of the studies conducted on the subject of short-period (6.0-0.3 sec period) noise over a period of approximately three years. Information from deep-hole and surface arrays was used in an attempt to determine the types of waves of which the noise is composed. The theoretical behavior of higher-mode Rayleigh waves and of body waves as measured by surface and deep-hole arrays is described. Both surface and body waves are shown to exist in the noise. Surface waves generally predominate at the longer periods (of the period range discussed) while body waves appear at the shorter periods at quiet sites. Not all the data could be interpreted to define the wave types present.


Geophysics ◽  
2013 ◽  
Vol 78 (1) ◽  
pp. U1-U8 ◽  
Author(s):  
Benoit de Cacqueray ◽  
Philippe Roux ◽  
Michel Campillo ◽  
Stefan Catheline

We tested a small-scale experiment that is dedicated to the study of the wave separation algorithm and to the velocity variations monitoring problem itself. It handles the case in which velocity variations at depth are hidden by near-surface velocity fluctuations. Using an acquisition system that combines an array of sources and an array of receivers, coupled with controlled velocity variations, we tested the ability of beam-forming techniques to track velocity variations separately for body waves and surface waves. After wave separation through double beam forming, the arrival time variations of the different waves were measured through the phase difference between the extracted wavelets. Finally, a method was tested to estimate near-surface velocity variations using surface waves or shallow reflection and compute a correction to isolate target velocity variations at depth.


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