PACIFIC PUBLICATIONS

Y Xu, S Lebedev, T Meier, R Bonadio, C J Bean, Optimized workflows for high-frequency seismic interferometry using dense arrays, Geophysical Journal International, Volume 227, Issue 2, November 2021, Pages 875–897, https://doi.org/10.1093/gji/ggab260

Abstract

High-frequency seismic surface waves sample the top few tens of meters to the top few kilometres of the subsurface. They can be used to determine 3-D distributions of shear-wave velocities and to map the depths of discontinuities (interfaces) within the crust. Passive seismic imaging, using ambient noise as the source of signal, can thus be an effective tool of exploration for mineral, geothermal and other resources, provided that sufficient high-frequency signal is available in the ambient noise wavefield and that accurate, high-frequency measurements can be performed on this signal. Ambient noise imaging using the ocean-generated noise at 5–30 s periods is now a standard method, but less signal is available at frequencies high enough for deposit-scale imaging (0.2–30 Hz), and few studies have reported successful measurements in broad frequency bands. Here, we develop a workflow for the measurement of high-frequency, surface wave phase velocities in very broad frequency ranges. Our workflow comprises (1) a new noise cross-correlation procedure that accounts for the non-stationary properties of the high-frequency noise sources, removes bandpass filtering, replaces temporal normalization with short time window stacking, and drops the explicit spectral normalization by adopting cross-coherence; (2) a new phase-velocity measurement method that extends the bandwidth of reliable measurements by exploiting the (resolved) 2π ambiguity of phase- velocity measurements and (3) interstation-distance-dependent quality control that uses the similarity of subgroups of dispersion curves to reject outliers and identify the frequency ranges with accurate measurements. The workflow is highly automated and applicable to large arrays. Applying our method to data from a large-N array that operated for one month near Marathon, Ontario, Canada, we use rectangular subarrays with 150-m station spacing and, typically, 1 hr of data and obtain Rayleigh-wave phase-velocity measurements in a 0.5–30 Hz frequency range, spanning over 5.9 octaves, twice the typical frequency range of 1.5–3 octaves in previous studies. Phase-velocity maps and the subregion-average 1-D velocity models they constrain show a high-velocity anomaly consistent with the known, west-dipping gabbro intrusions beneath the area. The new structural information can improve our understanding of the geometry of the gabbro intrusions, hosting the Cu-PGE Marathon deposit.

doi: https://doi.org/10.1093/gji/ggab260

 

Teodor, D., Beard, C., Pinzon-Rincon, L. A., Mordret, A., Lavoué, F., Beaupretre, S., Boué, P., and Brenguier, F.: High-frequency ambient noise surface wave tomography at the Marathon PGE-Cu deposit (Ontario, Canada), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13152, https://doi.org/10.5194/egusphere-egu21-13152

Abstract

Ambient noise surface wave tomography (ANSWT) is an environmentally friendly and cost-effective technique for subsurface imaging. In this study, we used natural (low-frequency) and anthropogenic (high-frequency) noise sources to map the velocity structure of the Marathon Cu-PGE deposit (Ontario, Canada) to a depth of 1 km. The Marathon deposit is a circular (ø = 25 km) alkaline intrusion comprising gabbros at the rim and an overlying series of syenites in the centre. Cu-PGE mineralisation is hosted by gabbros close to the inward-dipping footwall of the intrusion. The country rocks are Archaean volcanic breccias that are seismically slower than the gabbros, and similar in velocity to the syenites. We used ANSWT to image the footwall contact that controls the location of the mineralisation.

An array of 1024 vertical-component receivers were deployed for 30 days to record ambient noise required for surface wave analysis. Two overlapping grids were used: a 200 m x 6040 m dense array with node spacing of 50 m, and a 2500 m x 4000 m sparse array with node spacing of 150 m. The signal was down-sampled to 50 Hz, divided into segments of 30 minutes, cross-correlated and stacked. Surface wave analysis was conducted over the dense array and the sparse array data. We considered the fundamental mode of Rayleigh wave propagation for our frequency-wavenumber (F-K) analysis and focused on the phase velocity variation in the high-frequency ambient noise signal (up to 22 Hz). We reconstructed the shallow structure with progressively increased resolution using surface wave dispersion curves extracted from receiver arrays divided into segments of variable lengths. Several average dispersion curves were computed from individual dispersion curves belonging to different seismic lines. Each average dispersion curve was inverted to obtain S-wave velocity models using an McMC transdimensional Bayesian approach.

The tomographic images reveal a shallow high-velocity anomaly, which we interpret as being related to the gabbro intrusion that hosts the mineralization. The large-wavelength structures in the S-wave velocity models are relatively consistent with the geological structures inferred from surface mapping and drill core data. These results show that the ANSWT, focused on the high-frequency signal provided by anthropogenic noise sources, is an efficient technique for imaging “shallow” (1 km depth) geological structures in a mineral exploration context.

doi: https://doi.org/10.5194/egusphere-egu21-13152

 

D. Hariri Naghadeh, C. J Bean, F. Brenguier, P. J Smith, Retrieving reflection arrivals from passive seismic data using Radon correlation, Journal of Geophysics and Engineering, Vol. 18, Issue 2, April 2021, Pages 1-15

Abstract

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.

doi: https://doi.org/10.1093/jge/gxab004

 

L. Pinzon‐Rincon; F. Lavoué; A. Mordret; P. Boué; F.Brenguier; P.Dales; Y. Ben‐Zion; F. Vernon; C. J. Bean; D. Hollis. Humming Trains in Seismology: An Opportune Source for Probing the Shallow Crust. Seismological Research Letters (2021)

Abstract

Seismologists are eagerly seeking new and preferably low‐cost ways to map and track changes in the complex structure of the top few kilometers of the crust. By understanding it better, they can build on what is known regarding important, practical issues. These include telling us whether imminent earthquakes and volcanic eruptions are generating telltale underground signs of hazard, about mitigation of induced seismicity such as from deep injection of wastewater, how the Earth and its atmosphere couple, and where accessible natural resources are. Passive seismic imaging usually relies on blind correlations within extended recordings of Earth’s ceaseless “hum” or coda of well‐mixed, small vibrations. In this article, we propose a complementary approach. It is seismic interferometry using opportune sources—specifically ones not stationary in time and moving in a well‐understood configuration. Its interpretation relies on an accurate understanding of how these sources radiate seismic waves, precise timing, careful placement of pairs of listening stations, and seismic phase differentiation (surface and body waves). Massive freight trains were only recently recognized as such a persistent, powerful cultural (human activity‐caused) seismic source. One train passage may generate a tremor with an energy output of a magnitude 1 earthquake and be detectable for up to 100 km from the track. We discuss the source mechanisms of train tremors and review the basic theory on sources. Finally, we present case studies of body‐ and surface‐wave retrieval as an aid to mineral exploration in Canada and to monitoring of a southern California fault zone. We believe noise recovery from this new signal source, together with dense data acquisition technologies such as nodes or distributed acoustic sensing, will deeply transform our ability to monitor activity in the shallow crust at sharpened resolution in time and space.

doi: https://doi.org/10.1785/0220200248

 

F. Lavoué, O. Coutant, P. Boué, L. Pinzon‐Rincon, F.Brenguier, R. Brossier, P. Dales, M. Rezaeifar, C. J. Bean; Understanding Seismic Waves Generated by Train Traffic via Modeling: Implications for Seismic Imaging and Monitoring. Seismological Research Letters (2020)

 Abstract

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).

doi: https://doi.org/10.1785/0220200133

Link to the accepted version and supplementary material archived on the PACIFIC knowledge base platform

 

P. Dales, L. Pinzon-Ricon, F. Brenguier, et al. . Virtual Sources of Body Waves from Noise Correlations in a Mineral Exploration Context. Seismological Research Letters. Seismological Research Letters (2020) 91 (4): 2278–2286.

Abstract

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.

https://doi.org/10.1785/0220200023

 

A. Mordret, R. Courbis, F. Brenguier, M. Chmiel, S. Garambois, S. Mao, P. Boué, X. Campman, T. Lecocq, W. Van der Veen, D. Hollis (2020). Noise-based ballistic wave passive seismic monitoring. Part 2: surface waves. Geophysical Journal International, Volume 221, Issue 1, April 2020, Pages 692–705

Abstract
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.

https://doi.org/10.1093/gji/ggaa016

F. Brenguier, R. Courbis, A. Mordret, X. Campman, P. Boué, M. Chmiel, T. Takano, T. Lecocq, W. Van der Veen, S. Postif, D. Hollis (2020). Noise-based ballistic wave passive seismic monitoring. Part 1: body waves. Geophysical Journal International, Volume 221, Issue 1, April 2020, Pages 683–691,1,

Abstract
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.

https://doi.org/10.1093/gji/ggz440

T. Takano, F. Brenguier, M. Campillo, A. Peltier, T. Nishimura (2020); Noise-based passive ballistic wave seismic monitoring on an active volcano, Geophysical Journal International, Volume 220, Issue 1, January 2020, Pages 501–507

Abstract
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.

https://doi.org/10.1093/gji/ggz466

F. Brenguier, A. Mordret, R. Lynch, R. Courbis, X. Campbell, P. Boué, M. Chmiel, S. Mao, S. Mao, T. Takano, T. Lecocq, W. van der Veen, S. Postif, D. Hollis (2019) Monitoring of fields using body and surface waves reconstructed from passive seismic ambient noise (2019), oral presentation, SEG Technical Program Expanded Abstracts 2019

Abstract
There are important economic, environmental and societal reasons for monitoring production from oil, gas and geothermal fields. Unfortunately, standard microseismic monitoring is often not useful due to low levels of microseismicity. We propose to use body and surface waves reconstructed from ambient seismic noise for such monitoring. In this work, we use seismic data recorded from a dense sensor array at the Groningen gas field in northern Holland and show how direct P-waves can be extracted from the ambient noise cross correlations and then used to monitor seismic velocity variations over time. This approach has advantages over the use of coda wave interferometry due to the ability to localise such changes in the subsurface. We show how both direct and refracted (head) P-waves as well as Rayleigh surface waves can be used for such field monitoring, with changes of ∼1% being resolved. Both fundamental and first overtone Rayleigh waves are used to localise such changes, which correspond nicely to known geology to within 100 m.

https://doi.org/10.1190/segam2019-3216217.1

Brenguier, F., Boué, P., Ben‐Zion, Y., Vernon, F., Johnson, C. W., Mordret, A., et al. ( 2019). Train traffic as a powerful noise source for monitoring active faults with seismic interferometry. Geophysical Research Letters, 46.

Abstract
Laboratory experiments report that detectable seismic velocity changes should occur in the vicinity of fault zones prior to earthquakes. However, operating permanent active seismic sources to monitor natural faults at seismogenic depth is found to be nearly impossible to achieve. We show that seismic noise generated by vehicle traffic, and especially heavy freight trains, can be turned into a powerful repetitive seismic source to continuously probe the Earth’s crust at a few kilometers depth. Results of an exploratory seismic experiment in Southern California demonstrate that correlations of train‐generated seismic signals allow daily reconstruction of direct P body waves probing the San Jacinto Fault down to 4‐km depth. This new approach may facilitate monitoring most of the San Andreas Fault system using the railway and highway network of California.

https://doi.org/10.1029/2019GL083438 and available as PDF here

Chmiel, M., Mordret, A. , Boué, P., Brenguier, F., Lecocq, T., Courbis, R., Hollis, D, Campman, X., Romijn, R. and Van der Veen, W. (2019). Ambient noise multimode Rayleigh and Love wave tomography to determine the shear velocity structure above the Groningen gas field, Geophys. J. Int.
Summary 

The Groningen gas field is one of the largest gas fields in Europe. The continuous gas extraction led to an induced seismic activity in the area. In order to monitor the seismic activity and study the gas field many permanent and temporary seismic arrays were deployed. In particular, the extraction of the shear wave velocity model is crucial in seismic hazard assessment. Local S-wave velocity-depth profiles allow us the estimation of a potential amplification due to soft sediments.

Ambient seismic noise tomography is an interesting alternative to traditional methods that were used in modelling the S-wave velocity. The ambient noise field consists mostly of surface waves, which are sensitive to the Swave and if inverted, they reveal the corresponding S-wave structures.

In this study, we present results of a depth inversion of surface waves obtained from the cross-correlation of 1 month of ambient noise data from four flexible networks located in the Groningen area. Each block consisted of about 400 3-C stations. We compute group velocity maps of Rayleigh and Love waves using a straight-ray surface wave tomography. We also extract clear higher modes of Love and Rayleigh waves.

The S-wave velocity model is obtained with a joint inversion of Love and Rayleigh waves using the Neighbourhood Algorithm. In order to improve the depth inversion, we use the mean phase velocity curves and the higher modes of Rayleigh and Love waves. Moreover, we use the depth of the base of the North Sea formation as a hard constraint. This information provides an additional constraint for depth inversion, which reduces the S-wave velocity uncertainties.

The final S-wave velocity models reflect the geological structures up to 1 km depth and in perspective can be used in seismic risk modelling.

https://doi.org/10.1093/gji/ggz237

D. Hariri Naghadeh, C. J Bean, F. Brenguier, P. J Smith, Retrieving reflection arrivals from passive seismic data using Radon correlation, Journal of Geophysics and Engineering, Vol. 18, Issue 2, April 2021, Pages 1-15

Abstract

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.

doi: https://doi.org/10.1093/jge/gxab004

 

L. Pinzon‐Rincon; F. Lavoué; A. Mordret; P. Boué; F.Brenguier; P.Dales; Y. Ben‐Zion; F. Vernon; C. J. Bean; D. Hollis. Humming Trains in Seismology: An Opportune Source for Probing the Shallow Crust. Seismological Research Letters (2021)

Abstract

Seismologists are eagerly seeking new and preferably low‐cost ways to map and track changes in the complex structure of the top few kilometers of the crust. By understanding it better, they can build on what is known regarding important, practical issues. These include telling us whether imminent earthquakes and volcanic eruptions are generating telltale underground signs of hazard, about mitigation of induced seismicity such as from deep injection of wastewater, how the Earth and its atmosphere couple, and where accessible natural resources are. Passive seismic imaging usually relies on blind correlations within extended recordings of Earth’s ceaseless “hum” or coda of well‐mixed, small vibrations. In this article, we propose a complementary approach. It is seismic interferometry using opportune sources—specifically ones not stationary in time and moving in a well‐understood configuration. Its interpretation relies on an accurate understanding of how these sources radiate seismic waves, precise timing, careful placement of pairs of listening stations, and seismic phase differentiation (surface and body waves). Massive freight trains were only recently recognized as such a persistent, powerful cultural (human activity‐caused) seismic source. One train passage may generate a tremor with an energy output of a magnitude 1 earthquake and be detectable for up to 100 km from the track. We discuss the source mechanisms of train tremors and review the basic theory on sources. Finally, we present case studies of body‐ and surface‐wave retrieval as an aid to mineral exploration in Canada and to monitoring of a southern California fault zone. We believe noise recovery from this new signal source, together with dense data acquisition technologies such as nodes or distributed acoustic sensing, will deeply transform our ability to monitor activity in the shallow crust at sharpened resolution in time and space.

doi: https://doi.org/10.1785/0220200248

 

F. Lavoué, O. Coutant, P. Boué, L. Pinzon‐Rincon, F.Brenguier, R. Brossier, P. Dales, M. Rezaeifar, C. J. Bean; Understanding Seismic Waves Generated by Train Traffic via Modeling: Implications for Seismic Imaging and Monitoring. Seismological Research Letters (2020)

 Abstract

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).

doi: https://doi.org/10.1785/0220200133

Link to the accepted version and supplementary material archived on the PACIFIC knowledge base platform

 

P. Dales, L. Pinzon-Ricon, F. Brenguier, et al. . Virtual Sources of Body Waves from Noise Correlations in a Mineral Exploration Context. Seismological Research Letters. Seismological Research Letters (2020) 91 (4): 2278–2286.

Abstract

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.

https://doi.org/10.1785/0220200023

 

A. Mordret, R. Courbis, F. Brenguier, M. Chmiel, S. Garambois, S. Mao, P. Boué, X. Campman, T. Lecocq, W. Van der Veen, D. Hollis (2020). Noise-based ballistic wave passive seismic monitoring. Part 2: surface waves. Geophysical Journal International, Volume 221, Issue 1, April 2020, Pages 692–705

Abstract
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.

https://doi.org/10.1093/gji/ggaa016

F. Brenguier, R. Courbis, A. Mordret, X. Campman, P. Boué, M. Chmiel, T. Takano, T. Lecocq, W. Van der Veen, S. Postif, D. Hollis (2020). Noise-based ballistic wave passive seismic monitoring. Part 1: body waves. Geophysical Journal International, Volume 221, Issue 1, April 2020, Pages 683–691,1,

Abstract
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.

https://doi.org/10.1093/gji/ggz440

T. Takano, F. Brenguier, M. Campillo, A. Peltier, T. Nishimura (2020); Noise-based passive ballistic wave seismic monitoring on an active volcano, Geophysical Journal International, Volume 220, Issue 1, January 2020, Pages 501–507

Abstract
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.

https://doi.org/10.1093/gji/ggz466

F. Brenguier, A. Mordret, R. Lynch, R. Courbis, X. Campbell, P. Boué, M. Chmiel, S. Mao, S. Mao, T. Takano, T. Lecocq, W. van der Veen, S. Postif, D. Hollis (2019) Monitoring of fields using body and surface waves reconstructed from passive seismic ambient noise (2019), oral presentation, SEG Technical Program Expanded Abstracts 2019

Abstract
There are important economic, environmental and societal reasons for monitoring production from oil, gas and geothermal fields. Unfortunately, standard microseismic monitoring is often not useful due to low levels of microseismicity. We propose to use body and surface waves reconstructed from ambient seismic noise for such monitoring. In this work, we use seismic data recorded from a dense sensor array at the Groningen gas field in northern Holland and show how direct P-waves can be extracted from the ambient noise cross correlations and then used to monitor seismic velocity variations over time. This approach has advantages over the use of coda wave interferometry due to the ability to localise such changes in the subsurface. We show how both direct and refracted (head) P-waves as well as Rayleigh surface waves can be used for such field monitoring, with changes of ∼1% being resolved. Both fundamental and first overtone Rayleigh waves are used to localise such changes, which correspond nicely to known geology to within 100 m.

https://doi.org/10.1190/segam2019-3216217.1

Brenguier, F., Boué, P., Ben‐Zion, Y., Vernon, F., Johnson, C. W., Mordret, A., et al. ( 2019). Train traffic as a powerful noise source for monitoring active faults with seismic interferometry. Geophysical Research Letters, 46.

Abstract
Laboratory experiments report that detectable seismic velocity changes should occur in the vicinity of fault zones prior to earthquakes. However, operating permanent active seismic sources to monitor natural faults at seismogenic depth is found to be nearly impossible to achieve. We show that seismic noise generated by vehicle traffic, and especially heavy freight trains, can be turned into a powerful repetitive seismic source to continuously probe the Earth’s crust at a few kilometers depth. Results of an exploratory seismic experiment in Southern California demonstrate that correlations of train‐generated seismic signals allow daily reconstruction of direct P body waves probing the San Jacinto Fault down to 4‐km depth. This new approach may facilitate monitoring most of the San Andreas Fault system using the railway and highway network of California.

https://doi.org/10.1029/2019GL083438 and available as PDF here

Chmiel, M., Mordret, A. , Boué, P., Brenguier, F., Lecocq, T., Courbis, R., Hollis, D, Campman, X., Romijn, R. and Van der Veen, W. (2019). Ambient noise multimode Rayleigh and Love wave tomography to determine the shear velocity structure above the Groningen gas field, Geophys. J. Int.
Summary 

The Groningen gas field is one of the largest gas fields in Europe. The continuous gas extraction led to an induced seismic activity in the area. In order to monitor the seismic activity and study the gas field many permanent and temporary seismic arrays were deployed. In particular, the extraction of the shear wave velocity model is crucial in seismic hazard assessment. Local S-wave velocity-depth profiles allow us the estimation of a potential amplification due to soft sediments.

Ambient seismic noise tomography is an interesting alternative to traditional methods that were used in modelling the S-wave velocity. The ambient noise field consists mostly of surface waves, which are sensitive to the Swave and if inverted, they reveal the corresponding S-wave structures.

In this study, we present results of a depth inversion of surface waves obtained from the cross-correlation of 1 month of ambient noise data from four flexible networks located in the Groningen area. Each block consisted of about 400 3-C stations. We compute group velocity maps of Rayleigh and Love waves using a straight-ray surface wave tomography. We also extract clear higher modes of Love and Rayleigh waves.

The S-wave velocity model is obtained with a joint inversion of Love and Rayleigh waves using the Neighbourhood Algorithm. In order to improve the depth inversion, we use the mean phase velocity curves and the higher modes of Rayleigh and Love waves. Moreover, we use the depth of the base of the North Sea formation as a hard constraint. This information provides an additional constraint for depth inversion, which reduces the S-wave velocity uncertainties.

The final S-wave velocity models reflect the geological structures up to 1 km depth and in perspective can be used in seismic risk modelling.

https://doi.org/10.1093/gji/ggz237

RELATED PUBLICATIONS

Hollis D., McBride J., Good D., Arndt N., Brenguier F., and Olivier G., 2018. Use of Ambient Noise Surface Wave Tomography in Mineral Resource Exploration and Evaluation, SEG Annual Meeting 2018, Anaheim, California.

Abstract: Passive seismic imaging is a low-impact, low-cost technique that can be used to explore for and evaluate mineral deposits. […]

The technique uses ambient seismic noise from natural and anthropogenic sources for subsurface imagining and monitoring. Cross-correlation between receiver pairs is used to extract the Green function and analysis of dispersion of surface wave from the cross-correlated data generates a near-surface velocity model. This model is then used to establish the structure, lithology, and physical characteristics of materials in the subsurface. The results can be used alone or jointly with other geophysical or geological data or employed to improve imagining of active source data.

The scales of passive seismic imaging range from the entire crust and upper mantle to near-surface geotechnical or civil engineering surveys, spanning depths from 100s of kilometers to few meters. Most current applications are in the petroleum, geothermal, groundwater and geo-engineering sectors but the technique is finding increasing employment in mine security and mineral exploration.

Available here.

SISPROBE, 2018. Marathon Passive Seismic Project, Meylan, France, 18p.

Executive summary: The records for the Marathon passive seismic project are of good quality and show usable ambient seismic noise especially in the period band [0.15 1.5]s (∼ 0.7-7 Hz) used for the tomography. The microseismic noise at high frequency is mostly coming the Great Lakes. At lower frequency, the noise comes from East-North-East direction (North Atlantic Ocean). The noise cross-correlations show essentially the fundamental mode of the Rayleigh waves travelling at an average velocity of ∼3 km/s. Due to the high velocity and the long wavelengths, we only used data from station pairs more than 900 m apart. It resulted in ∼1300 dispersion curves used for the inversion. The 3D S-wave velocity model is presented together with its uncertainties. The top of the gabbro intrusive slab is clearly imaged.

Available here and at: http://www.sisprobe.com/wp-content/uploads/2018/09/2018-Final-Report-Results-of-Ambient-Noise-Surface-Wave-Tomography-Marathon-ON-Canada.pdf

SISPROBE, 2017. Detection of old mine working for future infrastructure plan and development, 79th EAGE Conference & Exhibition 2017, Paris, France

As the demand for minerals are increasing, old mining areas are being revisited with the hope of further extracting resources. Some of these areas have been abandoned more than a century ago and as a result the exact location and the extent of the old mined out regions are unknown. Accurate knowledge of the mined out areas are important in order to plan infrastructure and future development. In other circumstances, mine operators are interested to detect remnant areas amongst older workings that have been hydrofilled so that these remnant areas can be mined. Seismic imaging methods have the potential to delineate these mined out areas from intact rock but have traditionally been too expensive to be used routinely. In this paper, we attempt to use a new passive method (called ambient noise surface wave tomography) to image old workings of an old Australian gold mine. Since the method does not require the use of a costly active source, it can be implemented at a fraction of the cost of a conventional active survey. The goal of the project was to see if the ambient seismic noise method could be used to identify old mine workings, mineral deposits, faults or shears and determine the thickness of the slag-heap.

Available here

Surroundings of the Kallak deposit in Sweden

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