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    • IsabelleF

      F. Brenguier, R. Courbis, A. Mordret, X. Campman, P. Boué, M. Chmiel, T. Takano, T. Lecocq, W. Van...

      Brief description :

      Noise-based ballistic wave passive seismic monitoring. Part 1: body waves

      Unveiling the mechanisms of earthquake and volcanic eruption preparation requires improving our ability to monitor the rock mass response to transient stress perturbations at depth. The standard passive monitoring seismic interferometry technique based on coda waves is robust but recovering accurate and properly localized P- and S-wave velocity temporal anomalies at depth is intrinsically limited by the complexity of scattered, diffracted waves. In order to mitigate this limitation, we propose a complementary, novel, passive seismic monitoring approach based on detecting weak temporal changes of velocities of ballistic waves recovered from seismic noise correlations. This new technique requires dense arrays of seismic sensors in order to circumvent the bias linked to the intrinsic high sensitivity of ballistic waves recovered from noise correlations to changes in the noise source properties. In this work we use a dense network of 417 seismometers in the Groningen area of the Netherlands, one of Europe's largest gas fields. Over the course of 1 month our results show a 1.5 per cent apparent velocity increase of the P wave refracted at the basement of the 700-m-thick sedimentary cover. We interpret this unexpected high value of velocity increase for the refracted wave as being induced by a loading effect associated with rainfall activity and possibly canal drainage at surface. We also observe a 0.25 per cent velocity decrease for the direct P-wave travelling in the near-surface sediments and conclude that it might be partially biased by changes in time in the noise source properties even though it appears to be consistent with complementary results based on ballistic surface waves presented in a companion paper and interpreted as a pore pressure diffusion effect following a strong rainfall episode. The perspective of applying this new technique to detect continuous localized variations of seismic velocity perturbations at a few kilometres depth paves the way for improved in situ earthquake, volcano and producing reservoir monitoring.

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      • IsabelleF

        Aurélien Mordret, Roméo Courbis, Florent Brenguier, Małgorzata Chmiel, Stéphane Garambois, Shujuan...

        Brief description :

        Noise-based ballistic wave passive seismic monitoring – Part 2: surface waves

        We develop a new method to monitor and locate seismic velocity changes in the subsurface using seismic noise interferometry. Contrary to most ambient noise monitoring techniques, we use the ballistic Rayleigh waves computed from 30 d records on a dense nodal array located above the Groningen gas field (the Netherlands), instead of their coda waves. We infer the daily relative phase velocity dispersion changes as a function of frequency and propagation distance with a cross-wavelet transform processing. Assuming a 1-D velocity change within the medium, the induced ballistic Rayleigh wave phase shift exhibits a linear trend as a function of the propagation distance. Measuring this trend for the fundamental mode and the first overtone of the Rayleigh waves for frequencies between 0.5 and 1.1 Hz enables us to invert for shear wave daily velocity changes in the first 1.5 km of the subsurface. The observed deep velocity changes (±1.5 per cent) are difficult to interpret given the environmental factors information available. Most of the observed shallow changes seem associated with effective pressure variations. We observe a reduction of shear wave velocity (–0.2 per cent) at the time of a large rain event accompanied by a strong decrease in atmospheric pressure loading, followed by a migration at depth of the velocity decrease. Combined with P-wave velocity changes observations from a companion paper, we interpret the changes as caused by the diffusion of effective pressure variations at depth. As a new method, noise-based ballistic wave passive monitoring could be used on several dynamic (hydro-)geological targets and in particular, it could be used to estimate hydrological parameters such as the hydraulic conductivity and diffusivity.

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        • IsabelleF

          Philippe Dales, Laura Pinzon‐Ricon, Florent Brenguier, Pierre Boué, Nick Arndt, John McBride,...

          Brief description :

          Virtual Sources of Body Waves from Noise Correlations in a Mineral Exploration Context.

          The extraction of body waves from passive seismic recordings has great potential for monitoring and imaging applications. The low environmental impact, low cost, and high accessibility of passive techniques makes them especially attractive as replacement or complementary techniques to active‐source exploration. There still, however, remain many challenges with body‐wave extraction, mainly the strong dependence on local seismic sources necessary to create high‐frequency body‐wave energy. Here, we present the Marathon dataset collected in September 2018, which consists of 30 days of continuous recordings from a dense surface array of 1020 single vertical‐component geophones deployed over a mineral exploration block. First, we use a cross‐correlation beamforming technique to evaluate the wavefield each minute and discover that the local highway and railroad traffic are the primary sources of high‐frequency body‐wave energy. Next, we demonstrate how selective stacking of cross‐correlation functions during periods where vehicles and trains are passing near the array reveals strong body‐wave arrivals. Based on source station geometry and the estimated geologic structure, we interpret these arrivals as virtual refractions due to their high velocity and linear moveout. Finally, we demonstrate how the apparent velocity of these arrivals along the array contains information about the local geologic structure, mainly the major dipping layer. Although vehicle sources illuminating array in a narrow azimuth may not seem ideal for passive reflection imaging, we expect this case will be commonly encountered and should serve as a good dataset for the development of new techniques in this domain.

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          • IsabelleF

            François Lavoué, Olivier Coutant, Pierre Boué, Laura Pinzon‐Rincon, Florent Brenguier, Romain...

            Brief description :

            Understanding Seismic Waves Generated by Train Traffic via Modeling: Implications for Seismic Imaging and Monitoring.

            Trains are now recognized as powerful sources for seismic interferometry based on noise correlation, but the optimal use of these signals still requires a better understanding of their source mechanisms. Here, we present a simple approach for modeling train‐generated signals inspired by early work in the engineering community, assuming that seismic waves are emitted by sleepers regularly spaced along the railway and excited by passing train wheels. Our modeling reproduces well seismological observations of tremor‐like emergent signals and of their harmonic spectra. We illustrate how these spectra are modulated by wheel spacing, and how their high‐frequency content is controlled by the distribution of axle loads over the rail, which mainly depends on ground stiffness beneath the railway. This is summarized as a simple rule of thumb that predicts the frequency bands in which most of train‐radiated energy is expected, as a function of train speed and of axle distance within bogies. Furthermore, we identify two end‐member mechanisms—single stationary source versus single moving load—that explain two types of documented observations, characterized by different spectral signatures related to train speed and either wagon length or sleeper spacing. In view of using train‐generated signals for seismic applications, an important conclusion is that the frequency content of the signals is dominated by high‐frequency harmonics and not by fundamental modes of vibrations. Consequently, most train traffic worldwide is expected to generate signals with a significant high‐frequency content, in particular in the case of trains traveling at variable speeds that produce truly broadband signals. Proposing a framework for predicting train‐generated seismic wavefields over meters to kilometers distance from railways, this work paves the way for high‐resolution passive seismic imaging and monitoring at different scales with applications to near‐surface surveys (aquifers, civil engineering), natural resources exploration, and natural hazard studies (landslides, earthquakes, and volcanoes).

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            • IsabelleF

              Diako Hariri Naghadeh, Christopher J Bean, Florent Brenguier, Patrick J Smith, Retrieving...

              Brief description :

              Retrieving reflection arrivals from passive seismic data using Radon correlation

              Since explosive and impulsive seismic sources such as dynamite, air guns, gas guns or even vibroseis can have a big impact on the environment, some companies have decided to record ambient seismic noise and use it to estimate the physical properties of the subsurface. Big challenges arise when the aim is extracting body waves from recorded passive signals, especially in the presence of strong surface waves. In passive seismic signals, such body waves are usually weak in comparison to surface waves that are much more prominent. To understand the characteristics of passive signals and the effect of natural source locations, three simple synthetic models were created. To extract body waves from simulated passive signals we propose and test a Radon-correlation method. This is a time-spatial correlation of amplitudes with a train of time-shifted Dirac delta functions through different hyperbolic paths. It is tested on a two-layer horizontal model, a three-layer model that includes a dipping layer (with and without lateral heterogeneity) and also on synthetic Marmousi model data sets. Synthetic tests show that the introduced method is able to reconstruct reflection events at the correct time-offset positions that are hidden in results obtained by the general cross-correlation method. Also, a depth migrated section shows a good match between imaged horizons and the true model. It is possible to generate off-end virtual gathers by applying the method to a linear array of receivers and to construct a velocity model by semblance velocity analysis of individually extracted gathers.

              Type of information :
              • IsabelleF

                PACIFIC on Research Gate

                Brief description :

                Check out our project log on Research Gate: https://www.researchgate.net/project/PACIFIC-H2020 

                 
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                • IsabelleF

                  PACIFIC poster

                  Brief description :

                  Download PACIFIC poster presented at the American Geophysical Union (AGU) in Washington DC (10-14 December 2018)

                  https://www.pacific-h2020.eu/wp-content/uploads/PACIFIC-poster.pdf 

                   
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