scholarly journals Monitoring of fields using body and surface waves reconstructed from passive seismic ambient noise

Author(s):  
Florent Brenguier ◽  
Aurélien Mordret ◽  
Richard Lynch ◽  
Roméo Courbis ◽  
Xander Campbell ◽  
...  
2019 ◽  
Author(s):  
Florent Brenguier ◽  
Aurélien Mordret ◽  
Richard Lynch ◽  
Roméo Courbis ◽  
Xander Campbell ◽  
...  

2019 ◽  
Vol 2019 (1) ◽  
pp. 1-3
Author(s):  
Richard Lynch ◽  
Dan Hollis ◽  
John McBride ◽  
Nick Arndt ◽  
Florent Brenguier ◽  
...  

2019 ◽  
Author(s):  
Richard Lynch ◽  
Dan Hollis ◽  
John McBride ◽  
Nick Arndt ◽  
Florent Brenguier ◽  
...  

2020 ◽  
Author(s):  
Miriam Kristekova ◽  
Jozef Kristek ◽  
Peter Moczo ◽  
Peter Labak

<p>Nuclear explosions are banned by the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Obviously, the CTBT needs robust and comprehensive verification tools to make sure that no nuclear explosion goes undetected. The detection of underground cavity due to nuclear explosions is a primary task for an on-site inspection (OSI) and resonance seismometry. Recently we have developed the finite-frequency-range spectral-power method that makes it possible to use seismic ambient noise recorded at the free surface above an underground cavity for localizing it. In this contribution we present results of application of the method to data recorded at a site of the Great Cavern near Felsopeteny, Hungary.</p><p>CTBTO performed several active and passive seismic measurements at the free surface above the Great Cavern in September 2019. Seismic ambient noise was recorded one week continuously at almost 50 stations with interstation distance around 50 m covering area 400 x 400 m.</p><p>The oval shaped cavern with a diameter of 28 m located 70 m below the surface was discovered within a clay mine in N-Hungary. The deep basement is composed of Triassic limestone, the cavern is in the overlying Oligocene sandstone formation. As a result of hydrothermal activity in the Pleistocene a cave formed in the limestone which may have collapsed over time. The opening of the deep part of the cave influenced the overlying sandstone formation but the collapse did not reach the surface.</p><p>We present the procedure of pre-processing and identification of a position of the cavern based on the recorded seismic ambient noise. We checked robustness of the obtained results. The results demonstrate potential of our methodology for the OSI purposes.</p>


2020 ◽  
Author(s):  
Ali Riahi ◽  
Zaher-Hossein Shomali ◽  
Anne Obermann ◽  
Ahmad Kamayestani

<p>We simultaneously extract both, direct P-waves and Rayleigh waves, from the seismic ambient noise field recorded by a dense seismic network in Iran. With synthetics, we show that the simultaneous retrieval of body and surface waves from seismic ambient noise leads to the unavoidable appearance of spurious arrivals that could lead to misinterpretations.</p><p>We work with 2 months of seismic ambient noise records from a dense deployment of 119 sensors with interstation distances of 2 km in Iran. To retrieve body and surface waves, we calculate the cross-coherency in low-frequency ranges, i.e. frequencies up to 1.2 Hz, to provide the empirical Green’s functions between each pair of stations. To separate the P and Rayleigh waves, we use the polarization method that also enhances the small amplitude body waves.</p><p>We observe both P and Rayleigh waves with an apparent velocity of 4.9±0.3 and 1.8±0.1 km/s in the studied area, respectively, as well as S or higher mode of Rayleigh waves, with an apparent velocity of 4.1±0.1 km/s. Besides these physical arrivals, we also observe two spurious arrivals with similar amplitudes before/after the P and/or Rayleigh waves that render the discrimination challenging.</p><p>To better understanding these arrivals, we perform synthetic tests. We show that simultaneously retrieving the body and surface waves from seismic ambient noise sources will unavoidably lead to the appearance of superior arrivals in the calculation of empirical Green’s functions.</p>


2021 ◽  
Author(s):  
Mehrdad Fotouhimehr ◽  
Elham Shabani

<p>Knowledge about seismic ambient noise wavefield through decomposition into different participant waves is of special importance in geophysical studies. In this study, WaveDec technique (Maranò et al., 2012) as an array statistical signal processing technique was used to decompose seismic ambient noise wavefield and to estimate wavefield parameters. In this method, the measurements from all components of stations and parameters of interest are modeled jointly which leads to significant improvement in extracting characteristics of surface waves. Considering the contribution of both Love and Rayleigh waves in the wavefield, the method estimates the desired parameters including amplitude, phase, azimuth, wave number and the ellipticity angle (for the Rayleigh wave only) based on the Maximum Likelihood Estimation method. One of the main characteristic of WaveDec is estimating the ellipticity angle of Rayleigh waves. This is very beneficial in determining retrograde and prograde particle motion and also in mode distinction.</p><p>In the WaveDec algorithm, the Truncated Newton method is used to optimize likelihood functions with respect to wavefield parameters. Furthermore, Bayesian Information Criterion (BIC) is used to select the best model and wave type determination (Rayleigh, Love, body wave or noise). Regarding a group of generated models for different wave types, the one with the smallest BIC is chosen.</p><p>We examined consistency of WaveDec algorithm by applying different numerical optimization methods; Truncated Newton, L-BFGS-B quasi-Newton and simplex-based Nelder-Mead methods. Furthermore, different model selection criteria; BIC, Akaike Information Criterion (AIC) and Hannan–Quinn Information Criterion (HQC) were examined to study the quality of generated models. They possess different penalty terms to avoid overfitting the models on data. All possible pairs of optimization methods and model selection criteria were utilized and replaced in WaveDec algorithm. In order to compare the resultant dispersion curves of surface waves and ellipticity angle curves of Rayleigh waves, SESAME model M2.1 synthetic data and some seismic ambient noise measurements in Colfiorito basin in Italy (Array B) were analyzed.</p>


2020 ◽  
Author(s):  
Ivan Granados Chavarria ◽  
Marco Calò ◽  
Ángel Figueroa Soto ◽  
Philippe Jousset

<p>In the framework of the international collaboration between Mexico and Europe for the development of geothermal energy (GEMex consortium), a seismic network of 45 seismic stations (25 broad-band and 20 short-period) was installed around the super-hot geothermal system of Los Humeros (Mexico) for more than one year. Los Humeros power plant is nested inside a quaternary caldera located in the eastern part of the Trans-Mexican Volcanic Belt that crosses the whole country from the Pacific coast to the Gulf of Mexico.</p><p>Among the several targets of the data collected by this network, an important task is to produce a seismic image of the caldera and of the geothermal reservoir. Here we present the 3D anisotropic shear wave velocity models retrieved by the seismic ambient noise tomography.</p><p>Thanks to the severe pre-processing of the whole seismic database we were able to obtain reliable and highly resolved models.</p><p>To carry out the model we applied a rigorous data quality assessment consisting in: 1) correction of the orientation of the sensors using the polarization of surface waves associated with tele-seismic and regional earthquakes, 2) assessment of the synchronization of the stations and correction of the times using daily cross-correlations functions, 3) finally to asses the quality of the stacked cross-correlations, knowed as Green’s functions (GF), we analyzed the noise sources directivity, inter-station distance and level of emergence of surface waves depending on the type of sensor used.</p><p>The processing allowed to pick clearly about 600 dispersion curves per velocity type (group and phase of R and L waves), using the NDCP code (Noisy Dispersion Curve Picking), that allows to display and select dispersion patterns both in time and frequency domain, for both causal and anti-causal part of the GF.</p><p>2D tomography maps were calculated from 0.5 to 9 s for each type of velocity. Depth inversion for the whole velocities types was carried out using surf96, allowing reconstructing the 3D anisotropic structure of the caldera for the first time.</p><p>The resulting models provides a larger view of the caldera and its anisotropic patterns down to 10 km depth. In these models, we were able to define the depth of the caldera rim, some important features of the internal part of the caldera and a low velocity body that could be associated with the hot sources feeding the reservoir. Our model are in strong agreement with those retrieved applying other geophysical methodologies (e.g. magnetotelluric, passive travel-time tomography, gravimetric, etc.).</p><p>This work is performed in the framework of the Mexican European consortium GeMex (Cooperation in Geothermal energy research Europe-Mexico, PT5.2 N: 267084 funded by CONACyT-SENER : S0019, 2015-04, and Horizon 2020, grant agreement No. 727550).</p>


2015 ◽  
Author(s):  
Rabah Bensalem* ◽  
Djamal Machane ◽  
Jean-Luc Chatelain ◽  
Mohamed Djeddi ◽  
Hakim Moulouel ◽  
...  

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