SM3.1 | Ambient Seismic Noise and Seismic Interferometry

SM3.1

Interferometric techniques turn seismic networks into continuous observation devices for (time-varying) Earth structure, volcanic and hydrologic processes, ocean - solid Earth interactions and many more phenomena. Increasingly, seismic interferometry is applied to signals beyond ocean microseismic noise, such as earthquake coda and anthropogenic seismic signals.

Great strides have been taken in obtaining high-resolution images of seismic velocity and other properties, in observing and quantifying the sources of various ambient noise wave types, and in inferring seismic property variations. Current challenges include the interpretation of signals from opportunistic sources, e.g. in the context of traffic noise interferometry or ambient noise body waves from localized storms; the interpretation of ambient noise amplitudes for elastic effects and anelastic attenuation; and the spatial localization of seismic property changes.

This session offers a broad space for discussing recent advances in ambient noise seismology and seismic interferometry. We invite abstracts on theoretical and numerical developments as well as novel applications. Topics may include, but are not limited to, studies of ambient seismic sources; ocean wave quantification through ambient noise; urban seismic noise; interferometric imaging; monitoring subsurface properties and quantifying the response of seismic velocity to various stresses and strains; studies of the spatial sensitivity for imaging and monitoring under various source conditions; quantification of site effects, amplification and attenuation; improvements in processing and retrieval of high-quality interferometry observations, and interdisciplinary applications of seismic interferometry.

Convener: Sven SchippkusECSECS | Co-conveners: Yesim Cubuk SabuncuECSECS, Yang LuECSECS, Peter MakusECSECS, Qing-Yu WangECSECS
Orals
| Wed, 26 Apr, 08:30–10:15 (CEST), 10:45–12:30 (CEST)
 
Room -2.91
Posters on site
| Attendance Wed, 26 Apr, 14:00–15:45 (CEST)
 
Hall X2
Posters virtual
| Attendance Wed, 26 Apr, 14:00–15:45 (CEST)
 
vHall GMPV/G/GD/SM
Orals |
Wed, 08:30
Wed, 14:00
Wed, 14:00

Session assets

Orals: Wed, 26 Apr | Room -2.91

The oral presentations are given in a hybrid format supported by a Zoom meeting featuring on-site and virtual presentations. The button to access the Zoom meeting appears just before the time block starts.
Chairpersons: Sven Schippkus, Yang Lu
08:30–08:35
Interferometry
08:35–09:05
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EGU23-8654
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ECS
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solicited
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Highlight
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On-site presentation
Hugo D. Ortiz and Robin S. Matoza

We develop a framework for retrieving time-varying atmospheric properties using a single infrasound sensor following an autocorrelation interferometry method. We compare relative velocity (effective sound speed) changes inferred from infrasound autocorrelations with independently measured air temperature and velocity variations. For the propagation geometry of the infrasound source (a waterfall) and receivers at El Reventador (Ecuador) we infer that effects from wind velocity can be assumed negligible and provide a mathematical model to derive temperatures from relative velocity changes. We further demonstrate that the autocorrelation method can be used to study the Martian atmosphere; specifically, we show that relative velocity changes derived from the pressure sensor on board the Interior Exploration using Seismic Investigations, Geodesy and Heat Transport lander can track variations of the effective speed of sound. These results also suggest the presence of continuous background infrasound on Mars.

References:

  • Ortiz, H. D., Matoza, R. S., Johnson, J. B., Hernandez, S., Anzieta, J. C., and Ruiz, M. C. (2021). Autocorrelation infrasound interferometry. Journal of Geophysical Research: Solid Earth. https://doi.org/10.1029/2020JB020513
  • Ortiz, H. D., Matoza, R. S., and Tanimoto, T. (2022).  Autocorrelation infrasound interferometry on Mars. Geophysical Research Letters. https://doi.org/10.1029/2021GL096225

How to cite: Ortiz, H. D. and Matoza, R. S.: Autocorrelation infrasound interferometry for atmospheric sensing on Earth and Mars, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8654, https://doi.org/10.5194/egusphere-egu23-8654, 2023.

09:05–09:15
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EGU23-5725
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ECS
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On-site presentation
Ali Riahi, Alexandre Kazantsev, Jean-Philippe Metaxian, Eleonore Stutzmann, Martin Schimmel, and Jean-Paul Montagner

We reconstruct the body and surface waves from the seismic ambient wave field, recorded by a dense seismic array deployment in the Paris Basin, France, with a final objective of performing a 3D seismic tomography by inversion of the retrieved P-phase arrivals. The array was installed in November 2010 and consists of around 100 stations. The stations were shifted to different locations every day, yielding around 580 recording locations with an interstation distance of about 400 m. Each station has continuously recorded around 3-4 days of the seismic ambient wavefield. We calculate the cross-coherency between each station couple in the frequency band of 1.0-4.5 Hz and estimate the empirical Green’s functions. We use the polarization properties of the cross-correlation tensors to separate the P- and Rayleigh wavefields. The results show the reconstruction of the fundamental and higher modes of Rayleigh and Love waves, as well as of diving P- waves. We observe the apparent group velocity of the fundamental and first higher mode of the Rayleigh wave around 0.5 and 1.5 km/s, respectively, and the apparent group velocity of around 0.8 km/s for the fundamental mode of the Love wave. The extraction of the P waves is challenging because of a high amplitude coherent artefact that can cause misinterpretation of the P- wave moveout. We propose a new approach to filter out the extracted P- wave in presence of this artifact and reconstruct the P-wave with a correct apparent velocity of around 2-3 km/s, validated against available active seismic data. This approach is based on template-matching and can be regarded as the most crucial step in P-wave retrieval from our dataset. Future steps will consist of using the extracted P-wave arrival time for a 3D tomography of the anticline structure located beneath the array.

How to cite: Riahi, A., Kazantsev, A., Metaxian, J.-P., Stutzmann, E., Schimmel, M., and Montagner, J.-P.: Extraction of diving body waves from a dense network of seismometers at kilometric offsets: a case study from the Paris Basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5725, https://doi.org/10.5194/egusphere-egu23-5725, 2023.

Sources
09:15–09:25
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EGU23-3193
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ECS
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Highlight
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On-site presentation
Alfio Marco Borzì, Vittorio Minio, Flavio Cannavò, Angelo Cavallaro, Sebastiano D'Amico, Raphael De Plaen, Adam Gauci, Thomas Lecocq, Gabriele Nardone, Arianna Orasi, Marco Picone, and Andrea Cannata

Microseism is the most continuous and ubiquitous seismic signal on the Earth and is caused by the interaction between the atmosphere, the hydrosphere and the Solid Earth. In literature, there are several studies that deal with the relationship between microseism and cyclonic activity considering in particular hurricanes, tropical cyclones and typhoons. However, the relationships between microseism and the small-scale tropical cyclones that occur in the Mediterranean Sea, called Medicanes, have never been analysed. For this reason, we considered the Medicane Apollo, which developed in the Ionian Sea and impacted the eastern part of Sicily during the period 25th October to 5th November 2021 causing heavy rainfall (> 400 mm/48h), strong wind gusts (104 km/h) and violent sea waves (significant wave height > 3.5 m). Furthermore, the heavy rainfall induced by the presence of Apollo, caused damage to infrastructure and agriculture forcing the Sicilian regional government to declare a state of emergency for 32 municipalities (in the provinces of Catania, Messina, Siracusa and Ragusa) that were mostly affected by the Medicane Apollo.

In this work, we analysed the microseism signal recorded by 78 seismic stations installed in South Italy, Malta and Greece coastline during the period under investigation. To obtain information about the significant wave heights, we consider the data obtained by hindcast maps and four wavemeters buoys. The spectral and amplitude analysis allowed us to obtain information about the space-time variations of the microseism amplitude and in addition, we were able both to differentiate the seismic stations that perceive Apollo (stations installed close to the Ionian Sea), the seismic stations that do not perceive the medicane (stations installed close to the Tyrrhenian sea) and the microseism bands influenced by the presence of the Medicane Apollo. Moreover, we tracked the position of the Apollo by using two different methods: i) grid search method based on the seismic amplitude decay using the 78 seismic stations first mentioned and ii) array technique by 15 seismic stations installed on Etna which may be considered an array thanks to their spatial distribution and geometry. We obtain a good match between the real positions of the Medicane Apollo derived from satellite images and the positions computed by the two analysis methods. This work shows that it is possible to extract information about the Mediterranean extreme meteo-marine events from microseism, a seismic signal that until not long ago was considered as noise, both for monitoring and research purposes.

How to cite: Borzì, A. M., Minio, V., Cannavò, F., Cavallaro, A., D'Amico, S., De Plaen, R., Gauci, A., Lecocq, T., Nardone, G., Orasi, A., Picone, M., and Cannata, A.: Microseism and Medicane Apollo: a new approach to investigate the Mediterranean extreme weather events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3193, https://doi.org/10.5194/egusphere-egu23-3193, 2023.

09:25–09:35
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EGU23-7289
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ECS
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Highlight
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On-site presentation
Théo Rebert, Thibaut Allemand, Thomas Bardainne, Caifang Cai, and Hervé Chauris

Train traffic is a powerful source of seismic vibrations. Recent studies have shown that trains illuminate geological structures both at the crustal and the geotechnical scale. Existing works have been able to reconstruct approximately the spectral characteristics of the wavefield emitted by a passing train. In this work, we show that we can recover information on the train itself with high accuracy by looking only at the seismic recordings.

We record passing trains with seismic accelerometers less than 2 meters away from the track. We can isolate the signal emitted by each wheel, and thus reconstruct the trajectory of the train. This trajectory reconstruction is performed using a non-linear waveform inversion algorithm involving the varying train speed, the spacing between the wheels and an apparent wavelet emitted when the wheel hits close to the seismic sensor. After low-pass filtering the data below 15 Hz for passenger trains passing at around 100 km/h, we obtain harmonious waveforms suitable for our inversion technique. Especially, we are able to pick each wheel from the raw trace, which allows for a robust initial model avoiding local minima trapping during the non-linear inversion. The estimated parameters are minimally influenced by seismic wave propagation speeds, because the closest sleeper dominates the signal in this frequency band.

These results suggest that train traffic is a repeatable seismic source that can be can be characterized with good accuracy.  By having a better information about the source process, it might be possible to extract more information from the noise recordings, and thus gain in resolution in the imaging of the near surface. Especially, we expect enhanced repeatability of Rayleigh velocities measurements which is important for subsurface monitoring. Further, this also allows for railway traffic monitoring as trains can be identified and their speed measured as they cross seismic arrays.

How to cite: Rebert, T., Allemand, T., Bardainne, T., Cai, C., and Chauris, H.: Seismic emissions from a passing train: turning ambient noise into a controlled source, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7289, https://doi.org/10.5194/egusphere-egu23-7289, 2023.

09:35–09:45
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EGU23-5670
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ECS
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Virtual presentation
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Katrin Löer, Claudia Finger, Ebitimi Obiri, and Heather Kennedy

We give an overview of a new toolbox for easy and fast beamforming analysis of three-component ambient seismic noise and discuss examples from different seismic arrays to solve different application challenges. From only a couple of hours of array recordings, the beamformer provides estimates of surface wave dispersion curves, surface wave azimuthal anisotropy, frequency-dependent wavefield composition including surface and body waves, and the direction of arrival for different wave types and frequencies. The beamformer can be used with three-component arrays from the lab to the field scale, provided ambient noise is available in the corresponding frequency range. Compared to standard (single-component) beamforming analysis, our approach integrates all three components recorded at every seismometer. Considering the phase shifts across the components, it identifies wave-specific particle motion and hence discriminates different wave types on account of their polarisation. The new implementation of the beamformer does not use the cross-spectral density matrix of the data explicitly (as done, for example, by the MUSIC algorithm and Capon beamformer), which reduces computation times significantly and makes it feasible to compute beam responses for a full day of data recorded on 100s of stations on a standard laptop PC. The toolbox will be available on github for both MATLAB and Python.

In an example from Los Humeros geothermal field (Mexico) we show Rayleigh wave azimuthal anisotropy as a function of frequency, corresponding to varying fast directions as a function of depth. A good agreement between the observed anisotropy and stress data from well logs as well as geological information indicates that fast directions correlate with the orientation of major faults and dykes. Anisotropy analysis thus provides a means to assess fault properties at depth, giving information about potential secondary permeability – a vital parameter in deep geothermal plays. Beamforming analysis of noise recordings in the Groningen area (Netherlands) reveals dominant prograde motion in both fundamental and 1st higher mode Rayleigh waves. This behaviour is indicative of a large impedance contrast between the very low shear-velocities in sedimentary basins and the underlying bedrock. The resolution of particle motion as a function of frequency allows us to observe the osculation frequency where fundamental and 1st higher mode Rayleigh waves approach each other and both modes change particle motion from prograde to retrograde and vice versa. The osculation frequency can be used to estimate the depth of the major impedance contrast, that is, the depth of the sedimentary basin. While body wave observations must be interpreted with care, considering the resolution capabilities of the array with respect to the expected (larger) wavelengths, the examples show that body waves contribute to the ambient noise wavefield with varying degree as a function of frequency, challenging the assumption of surface wave dominance common in ambient noise studies. Overall, we demonstrate that our beamforming toolbox provides direct information about structural features as well as fundamental a-priori information on wavefield composition and source characteristics, valuable for further ambient noise methods.

How to cite: Löer, K., Finger, C., Obiri, E., and Kennedy, H.: A comprehensive beamforming toolbox to characterise surface and body waves in three-component ambient noise wavefields, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5670, https://doi.org/10.5194/egusphere-egu23-5670, 2023.

09:45–09:55
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EGU23-1932
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On-site presentation
T. Dylan Mikesell and Zongbo Xu

Ambient seismic sources (e.g. ocean waves) generate ambient seismic waves, and thus in turn, one can use these waves to infer the source distribution and study the source properties. Many studies focus on the source distribution estimation result, but few discuss the uncertainty of the estimation result, even though the uncertainty is significant and should be taken into account in the interpretation. We propose to compute the uncertainty of the estimated source distribution using singular value decomposition. We focus on two commonly used estimation methods: matched field processing and full waveform inversion. We demonstrate the uncertainty of the two methods by assessing the associated point spread functions. We determine that the full-waveform inversion method possesses higher resolution than matched field processing given enough independent data.

How to cite: Mikesell, T. D. and Xu, Z.: Assessing the uncertainty of ambient-seismic-source-distribution estimation with matched field processing and full waveform inversion, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1932, https://doi.org/10.5194/egusphere-egu23-1932, 2023.

09:55–10:15
Coffee break
Chairpersons: Qing-Yu Wang, Peter Makus
Monitoring
10:45–10:55
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EGU23-15580
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ECS
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On-site presentation
Eldert Fokker, Elmer Ruigrok, and Jeannot Trampert

Subsurface temperature measurements are key to optimizing geothermal power plants and monitoring heat-storage systems. Previous studies showed that time-lapse variations in temperature can be correlated to variations in seismic velocity. Therefore, temperature monitoring through seismic velocity changes should be feasible. In this study, we provide a physical background for the correlation between temperature and seismic velocity changes. We model how temperature changes can disturb the equilibrium between stress and strain, and for specific boundary conditions, we can make a connection to changes in seismic velocity. Ultimately, we can construct a physics-based model of seismic velocity changes due to temperature variations.

How to cite: Fokker, E., Ruigrok, E., and Trampert, J.: Temperature-induced disturbances of the stress-strain equilibrium and their effects on seismic velocities, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15580, https://doi.org/10.5194/egusphere-egu23-15580, 2023.

10:55–11:05
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EGU23-12396
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ECS
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Virtual presentation
Claudia Finger and Katrin Löer

Surface wave dispersion curves derived from ambient noise recordings are frequently used to invert for subsurface velocity information. Rayleigh wave ellipticities and phase velocities are exploited, and sometimes jointly inverted, for the velocity structure beneath seismic arrays. Wavelengths of surface waves become large at low frequencies and are, thus, sensitive to great depths, but provide only very smooth velocity profiles. However, sudden velocity increases in the subsurface are of particular interest to delineate the extent of reservoirs, i.e., by sub-horizontal faults or detachments, or estimate the depth of sedimentary basins.

Here, we report a new approach to estimate sudden velocity increases in vertical velocity profiles using Rayleigh wave ellipticities and phase velocities. Using Kepler’s law of motion on elliptical orbits, we can theoretically delineate the frequency-dependent half-height and half-width of the energy ellipse described by Rayleigh waves.

In the presence of sudden velocity increases, fundamental and first higher mode Rayleigh waves have similar phase velocities at the so-called osculation frequency. This often leads to mode misidentification that biases inversion results. We show that this osculation frequency is close to the frequency where the Rayleigh ellipticity of the fundamental mode is one, i.e., motion is circular, and the ellipticity of the first higher mode has its maximum. At this frequency, our derived relation only requires the phase velocity of the first higher mode to estimate the half-height of the ellipse, which is a very good approximation of the depth of the sudden velocity increase.

To derive phase velocities and ellipticities of Rayleigh waves for synthetic three-component waveforms and real-world datasets from three sites (Weisweiler in Germany, FORGE in Utah, USA and Groningen, the Netherlands), we use three-component beamforming, which provides velocity and polarization parameters of recorded waves in short ambient noise time windows and thus can distinguish wave types and modes. From identified Rayleigh waves, we pick the phase velocity of the first higher mode at the osculation frequency directly in the beamformer plots and estimate the depth of sudden velocity increases using our new relation. No inversion scheme is needed for this approach.

This approach provides more accurate depth estimates of velocity jumps than other ambient noise methods. The depth sensitivity is only limited by the inter-station distances in the array configuration and the useable frequency range. The derived depths of sudden velocity increases can be used to constrain inversion schemes for more accurate velocity models or can be used directly to map structural changes in the subsurface.

How to cite: Finger, C. and Löer, K.: Depth of sudden velocity increases from multi-mode Rayleigh waves derived with three-component ambient noise beamforming, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12396, https://doi.org/10.5194/egusphere-egu23-12396, 2023.

11:05–11:15
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EGU23-13055
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ECS
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On-site presentation
Estelle Delouche and Laurent Stehly

Velocity variations related to water movements in aquifers are relatively unknown, thus, we propose to study the temporal changes of velocity variations of several aquifers in Greece. To this end, the stretching method is applied to the early coda of the autocorrelation functions of 90 permanent stations. These results, complemented by GPS and precipitation studies, indicate that the record of seasonal variations on seismic velocities may originate from two mechanisms: 1) a natural mechanism associated with the filling of the aquifer by precipitation and 2) an anthropogenic mechanism related to groundwater pumping.

Between 1-3s of period, velocity variations can either vary as a function of water supply to the aquifer: increased water leads to a decrease in wave velocity; or record contraction/relaxation of the rocks beneath the aquifer that vary as a function of its recharge.

 

Thus, the investigation conducted in this study allows us to explain all the seasonal variations observed on the dv/vs in Greece between 1-3s of period.

 

 

How to cite: Delouche, E. and Stehly, L.: Seasonal velocity variations in Greece associated with aquifers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13055, https://doi.org/10.5194/egusphere-egu23-13055, 2023.

11:15–11:25
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EGU23-14308
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ECS
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On-site presentation
Alexander Yates, Corentin Caudron, Philippe Lesage, Aurélien Mordret, and Virginie Pinel

Passive seismic interferometry has become a popular technique for monitoring volcanoes over the past two decades. Despite this, volcanoes still represent challenging locations to apply the methodology due to the presence of volcano seismicity. Volcanic tremor, in particular, can significantly alter the character of cross-correlation functions. This leads to the possibility of mis-interpreting changes in phase or waveform shape as due to real subsurface processes.

Mount Ruapehu is one such volcano where volcanic tremor is regularly recorded above 1 Hz. Thus, a previous study applying passive interferometry at the volcano during its most recent eruptive period (2006–07) focused on lower frequencies to reduce the risk of contamination. In this work, we target the higher frequencies that include volcanic tremor (1–4 Hz) during approximately the same period (2005–2009), thus providing an opportunity to monitor changes at shallower depths within the volcanic system. To assess the suitability of the tremor as a repeatable seismic source, we first apply an unsupervised machine learning technique in the form of agglomerative hierarchical clustering of cross-correlation functions. Doing so allows us to form groups of data that share similar characteristics and, unlike commonly used similarity measures, does not require a defined reference period. Through this, we find that cross-correlation functions at higher frequencies are both relatively consistent in time and dominated by seasonal processes (with alternating summer and winter clusters clearly identified).

Applying the wavelet method to compute travel-time changes in the time-frequency domain reveals snow loading to be the most likely process influencing seismic velocities on the volcano. Amplitudes of +/- 0.5% are recorded at the seismic station closest to the summit, with peak velocites occurring at the same time as maximum snow thickness. In contrast, the seasonal trends recorded at seismic stations with minimal snow cover are of lower amplitude (+/- 0.1%), opposite in sign, and are best fit using a model based on fluid pressure changes in response to precipitation. No obvious short-term changes are detected prior to phreatic eruptions in 2006 and 2007. It is of interest, however, that both eruptions occur approximately one year apart following the initial decrease of velocities in response to snow unloading/melt, suggesting a causal relationship may exist.

How to cite: Yates, A., Caudron, C., Lesage, P., Mordret, A., and Pinel, V.: Seismic velocity changes in response to snow loading at Mount Ruapehu volcano, New Zealand, using passive seismic interferometry, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14308, https://doi.org/10.5194/egusphere-egu23-14308, 2023.

Other Applications
11:25–11:35
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EGU23-5057
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ECS
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Highlight
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On-site presentation
Yongki Andita Aiman, Andrew Delorey, Yang Lu, and Götz Bokelmann

Major faults such as the Periadriatic Fault and the Giudicarie Fault have been active in the past, and they have even been central features of the larger-scale deformation in the Alps. It seems that these faults are not active anymore though and we investigate why this is so by inspecting the orientation of the regional stress field which loads the faults mechanically. The orientation of maximum horizontal compressive stress (SHmax) is commonly estimated from in-situ borehole breakouts and earthquake focal mechanisms. Borehole measurements are expensive, and therefore sparse, and earthquake measurements can only be made in regions with many well-characterized earthquakes. Here we derive the stress-field orientation using stress-induced anisotropy in nonlinear elasticity. In this method, we measure the strain derivative of velocity as a function of azimuth. We use a natural pump-probe approach which consists of measuring elastic wave speed using empirical Green’s functions (probe) at different points of the earth tidal strain cycle (pump). The approach is validated using a larger data set in the Northern Alpine Foreland region where the orientation of SHmax is known from borehole breakouts and drilling-induced fractures. The technique resolves NNW-SSW to N-S directed SHmax which is in good agreement with conventional methods and the recent crustal stress model. The technique is then applied to the Southern Alps to understand the contemporary stress pattern associated with the ongoing deformation due to the counterclockwise rotation of the Adriatic plate with respect to the European plate. Our results explain why the two major faults in Northeastern Italy, the Giudicarie Fault and the Periadriatic Line (Pustertal-Gailtal Fault) are currently inactive, while the currently acting stress field allows faults in Slovenia to deform actively. We have demonstrated that the pump-probe method has the potential to fill in the measurement gap left by conventional approaches, both in terms of regional coverage and depth. 

How to cite: Aiman, Y. A., Delorey, A., Lu, Y., and Bokelmann, G.: Why are some faults in the Alps active, and others not? Answers from stress-induced anisotropy of nonlinear elasticity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5057, https://doi.org/10.5194/egusphere-egu23-5057, 2023.

11:35–11:45
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EGU23-5475
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ECS
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On-site presentation
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Hari Ram Thapa, Surya Pachhai, Abdelkrim Aoudia, Daniel Manu-Marfo, Keith Priestley, and Supriyo Mitra

Nepal is an actively deforming region due to its tectonic setting that hosts many destructive earthquakes including the most recent 2015 Gorkha earthquake of magnitude 7.8. To better understand the physics of earthquakes and their precise location as well as monitoring of seismicity and real-time seismic hazard in the region, a highly resolved 3-D structure of the crust is essential. This study presents a new 3-D shear S -wave velocity structure of the crust using group and phase velocity dispersions obtained from ambient noise tomography. This study further constrains the discontinuities beneath Himalaya Nepal using teleseismic compressional P-wave coda autocorrelation. Our results show significant variation in the crustal structure within the region and correlate well with known geological and tectonic features present there. The results from the P-wave coda autocorrelation identify major seismic discontinuities in the crust including the Main Himalayan Thrust (MHT). The MHT with two ramps correlates well with a low S-wave velocity layer obtained from the ambient noise tomography. The first ramp agrees with the duplex structure in the MHT beneath Lesser Himalaya while the second ramp connects flat low velocity beneath High Himalaya to a broad low-velocity zone beneath South Tibet. Moreover, the High Himalaya low-velocity layer is located where the GPS data show creeping north of the coseismic rupture of the 2015 Gorkha earthquake. The lateral variation of S-wave velocity on the MHT surface provides the details of lateral transitions that might have potentially controlled the rupture pattern of the 2015 Gorkha earthquake.

The geometry and extent of the High Himalaya low-velocity layer mimics the decollement coupling zone inferred from GPS data with widths of 50 to 70 km north of the nucleation of the 2015 Mw 7.8 Gorkha earthquake and 90 to 100 km north of the source of the Mw 8.4 1934 earthquake. The occurrence of millenary Mw>9.0 earthquakes in Central and Eastern Nepal would require either a wider coupling low velocity zone compared to the ones identified in this work or the involvement of southernmost Tibet low velocity decoupling zone so to store enough elastic energy.

How to cite: Thapa, H. R., Pachhai, S., Aoudia, A., Manu-Marfo, D., Priestley, K., and Mitra, S.: The Main Himalayan Thrust beneath Nepal and Southern Tibet illuminated by seismic ambient noise and teleseismic P wave coda autocorrelation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5475, https://doi.org/10.5194/egusphere-egu23-5475, 2023.

11:45–11:55
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EGU23-6237
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ECS
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Virtual presentation
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Hongrui Peng and Jiangtao Li

In the last decade, Empirical Green’s functions (EGFs) derived from ambient noise cross-correlation have been widely and successfully applied to measure seismic velocity and its temporal variation. However, it is still pending whether the amplitude of EGFs is reliable and whether it could be utilized in attenuation tomography. From our perspective, to develop a noise interferometry-based attenuation tomography method, it is necessary to overcome difficulties from two significant aspects. Firstly, in preprocessing, the relative amplitudes between different station pairs should be preserved, which precludes standard techniques, including one-bit/running-absolute-mean normalization and spectral whitening. Secondly, in addition to the intrinsic attenuation, amplitudes are also affected by other factors, such as noise source distribution, geometric spreading, instrument response, site effect, focusing and defocusing effect, etc. To obtain precise attenuation, it is necessary to separate all those factors carefully before or during inversion.

 

In this research, we develop a new workflow to perform attenuation tomography with ambient noise data. In preprocessing, we apply the asynchronous temporal flattening (ATF) normalization method (Zhou et al., 2020) to remove earthquake and abnormal signals in records while keeping relative amplitudes. Then we use the SNR and the symmetry of arrival times to select high-quality EGFs. Accounting focusing and defocusing effect of elastic heterogeneity, we predict it through finite-frequency theory (Zhou et al., 2004; Bao et al., 2016) and remove the effect from measured amplitudes. Finally, following the theory in (Weaver, 2013), we invert for attenuation, site effect, and wave field intensity of different incoming directions through a linear inversion. This workflow is feasible for both 1D and 2D arrays. It also delivers good results in the real data test of the Yellowstone national park region, with apparent high-attenuation anomaly beneath the Yellowstone Caldera.

 

References:

[1]L. Zhou, X. Song, and R. L. Weaver, ‘Retrieval of amplitude and attenuation from ambient seismic noise: synthetic data and practical considerations’, Geophysical Journal International, vol. 222, no. 1, pp. 544–559, Jul. 2020, doi: 10.1093/gji/ggaa194.

[2]Y. Zhou, F. A. Dahlen, and G. Nolet, ‘Three-dimensional sensitivity kernels for surface wave observables’, Geophysical Journal International, vol. 158, no. 1, pp. 142–168, Jul. 2004, doi: 10.1111/j.1365-246X.2004.02324.x.

[3]X. Bao, C. A. Dalton, and J. Ritsema, ‘Effects of elastic focusing on global models of Rayleigh wave attenuation’, Geophysical Journal International, vol. 207, no. 2, pp. 1062–1079, Nov. 2016, doi: 10.1093/gji/ggw322.

[4]R. L. Weaver, ‘On the retrieval of attenuation and site amplifications from ambient noise on linear arrays: further numerical simulations’, Geophysical Journal International, vol. 193, no. 3, pp. 1644–1657, Jun. 2013, doi: 10.1093/gji/ggt063.

How to cite: Peng, H. and Li, J.: An improved attenuation tomography method based on ambient noise cross-correlation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6237, https://doi.org/10.5194/egusphere-egu23-6237, 2023.

11:55–12:05
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EGU23-9477
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ECS
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On-site presentation
Jozef Müller, Tom Eulenfeld, and Ulrich Wegler

Solid Earth is subjected to nanostrain tidal deformations caused by gravitational attraction of the Moon and Sun. This causes periodic deformations of imperceptible fractures in the shallow rock that likely result into subtle variations of seismic velocities. It is possible to theoretically model the gravitational tidal deformations while the seismic velocities can be estimated, e.g., using ambient noise recordings processed with passive image interferometry. Combining these two pieces of information could allow for in-situ assessment of bedrock properties beneath seismic stations. In this study, we tried to accomplish this task using 18 standalone seismic stations (i.e., no array) from a network of the Integrated Plate Boundary Observatory Chile, complemented by several others in Europe and North America. The velocity changes were mostly estimated for frequencies of 1-4 and 4-7 Hz, using hourly Green's functions acquired after temporal stacking. Analysed coda lapse time windows of the Green's functions were 1-6, 5-10 and 8-13 seconds. Tide-related velocity changes were observed (mostly the M2 component). However, our results show that observability of such tide-related velocity variations seems to be strongly related to the station proximity to oceanic coastlines. This raises reasonable doubt about the required solid Earth tides origin of the observed tidal signals.

How to cite: Müller, J., Eulenfeld, T., and Wegler, U.: Turning standalone seismometers into strainmeters using tidal strain and ambient noise ‒ a feasibility study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9477, https://doi.org/10.5194/egusphere-egu23-9477, 2023.

12:05–12:30

Posters on site: Wed, 26 Apr, 14:00–15:45 | Hall X2

The posters scheduled for on-site presentation are only visible in the poster hall in Vienna. If authors uploaded their presentation files, these files are linked from the abstracts below, but only on the day of the poster session.
Chairpersons: Yesim Cubuk Sabuncu, Peter Makus, Qing-Yu Wang
Interferometry
X2.86
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EGU23-4166
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ECS
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On-site presentation
Bo Yang, Haoran Meng, Ning Gu, Xin Liu, and Xiaofei Chen

The cross-correlation of ambient seismic noise data can be utilized to image subsurface geological structures from ambient noise fields at local, regional, and global scales by extracting Green's functions between seismograph pairs. Precise extraction of empirical Green's functions from the cross-correlations of noise records requires that the seismic wavefield be fully diffuse. This requires the coefficients of the eigenfunction expansion of the seismic records to satisfy the statistical characteristics derived by Weaver and Lobkis (2004) in the time domain. Due to the complexities of the Earth media and noise sources, it is not feasible to obtain accurate eigenfunctions with the corresponding coefficients and adopt these statistical characteristics to evaluate actual seismic data. To resolve this issue, we derive the equivalent expressions in the frequency domain with dimensionless evaluation criteria without requiring the eigenfunctions. The evaluation of random noise, wind-induced vibrations, car- and air-traffic-excited ground motions, earthquakes, and continuous ambient seismic noise records confirms the validity of our evaluation method. We further apply the method to the widely used preprocessing procedures of ambient noise imaging techniques by examining time-domain normalization and spectral whitening operations of earthquake waveforms, thus quantitatively demonstrating how these procedures down-weight the non-diffuse component and improve the degree of waveform diffuseness (as shown in Figure 1). As an application, we select the coda wave signals generated by road traffic and earthquakes that satisfy the diffuse wavefield characteristics and extract the higher-order surface wave dispersion curves from 20-100 s seismic recordings without performing preprocessing procedures. Compared with the traditional surface wave processing process, our method is highly efficient, does not require long recording time and preprocessing such as normalization and whitening, and can be widely used in evaluating diffuse wavefield, imaging subsurface velocity and attenuation structures, and monitoring the temporal changes with high temporal resolution.

How to cite: Yang, B., Meng, H., Gu, N., Liu, X., and Chen, X.: Evaluating diffuse wavefield and its applications in seismic imaging, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4166, https://doi.org/10.5194/egusphere-egu23-4166, 2023.

X2.87
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EGU23-8517
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On-site presentation
Florian Le Pape, Christopher J. Bean, Athira Vijayan, and Mathias Fink

The ambient seismic noise is dominated by surface waves associated with ocean microseisms that are defined by a strong acoustic/seismic coupling at the seafloor. The understanding of microseism sources not only benefits seismic passive imaging and monitoring, but can also help track ocean storms using seismic signals recorded on land. Numerical simulations show that heterogeneous seafloor morphologies and structures can significantly affect the propagation of microseism’s surface waves and therefore the accuracy in locating their origin using traditional methods, such as array beamforming. Here, we aim to investigate how the use of time-reversal imaging can help overcome those limitations. The technique has mainly been developed for acoustics but has been applied successfully in seismology for earthquake localisation. Time-reversal imaging consists on back-propagating, through a realistic model, the signal measured at a network of receivers so that it eventually refocuses back at its origin. For this study, simulations are performed using the code SPECFEM3D and a regional 3D acoustic/elastic model of the Irish offshore, with seismic receivers homogeneously distributed along the coast of Ireland. First, methodologies and stations layout are tested with synthetic data generated from forward modelling using different source distributions. Processing approaches for the time-reversed simulation results are investigated in order to optimize the recovery of the original sources. Following those tests, real time windows of seismic noise “events” are then back-propagated into the model with the aim to map the microseism sources associated with local storms in the model area. The results are compared with microseism sources derived from global ocean wave models. Overall, the use of time-reversal imaging for microseism sources localisation looks promising. Although challenging due to the diffuse distribution of sources, there is good potential for developing further our understanding of microseism sources and monitor dominant microseism generation areas in the North Atlantic region with the implementation of a larger model.

How to cite: Le Pape, F., Bean, C. J., Vijayan, A., and Fink, M.: On localising North Atlantic’s microseism sources using time reversal imaging, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8517, https://doi.org/10.5194/egusphere-egu23-8517, 2023.

X2.88
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EGU23-124
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ECS
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On-site presentation
Sven Schippkus, Roel Snieder, Mahsa Safarkhani, and Céline Hadziioannou

Seismic interferometry gives rise to a correlation wavefield that is closely related to the Green’s function under the condition of uniformly distributed noise sources. Asymmetric correlation wavefields result from the violation of this condition and are commonly observed in field data. In the presence of an additional isolated noise source a second contribution to the correlation wavefield is introduced that emerges from the isolated source location at negative lapse time. The two wavefield contributions interfere, resulting in biased surface wave dispersion measurements. Isolated noise sources that act continuously, such as machinery or ocean microseisms, further have significant impact on the coda of the correlation wavefield. The coda can be dominated by direct waves propagating from the isolated noise source, not by multiply scattered waves originating from the master station. This fundamentally challenges the current understanding of how velocity changes detected in the coda can be measured and interpreted.

How to cite: Schippkus, S., Snieder, R., Safarkhani, M., and Hadziioannou, C.: The impact of isolated noise sources on correlation wavefields, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-124, https://doi.org/10.5194/egusphere-egu23-124, 2023.

Sources
X2.89
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EGU23-7003
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ECS
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On-site presentation
Mahsa Safarkhani, Sven Schippkus, and Céline Hadziioannou

Over the past two decades, the ambient seismic noise correlation method has revolutionized our ability to investigate the Earth's subsurface structure. Perfect reconstruction of the cross correlation wavefields towards Green's function demands some strong hypotheses about uncorrelated and spatially uniform seismic source distributions. In reality, violation of this assumption impacts the accuracy of the Green’s function estimate, which may bias applications in further studies. As this technique has become a standard method for subsurface imaging and monitoring, a methodology that identifies the effect of seismic source distributions plays an essential role in removing their contribution to achieve less-biased signals. Seismic array beamforming is commonly applied in estimating the direction of seismic waves crossing the array.

In this study, we use a new strategy based on beamforming of noise correlation signals. We consider several seismic stations surrounding the Gräfenberg array throughout Europe as virtual sources. We process two years of vertical component continuous noise recording from the Gräfenberg array in Germany and virtual sources in Poland, Italy, Portugal, France and Finland. Using the noise correlation-based beamforming method, we detect source directions for direct and coda waves for the primary (0.05-0.1 Hz) and secondary (0.1-0.4 Hz) microseism frequency bands. The source directions for the direct waves correspond to the converging and diverging part of the correlation wavefield. Throughout the coda, however, we detect the dominant noise source directions, i.e., surface waves generated by ocean microseisms in the Northern Atlantic during winter months and body waves from the Southern Pacific during summer months. This suggests that the coda of the correlation functions contains repeating direct waves from the dominant source regions, which may lead to incorrect estimates and interpretation of velocity variations if not accounted for. Knowledge of the ambient noise source origins and their spatiotemporal distribution is required to correctly interpret velocity variations.

How to cite: Safarkhani, M., Schippkus, S., and Hadziioannou, C.: Array beamforming on ambient seismic noise correlations reveals repeating direct waves in the coda, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7003, https://doi.org/10.5194/egusphere-egu23-7003, 2023.

X2.90
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EGU23-4258
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On-site presentation
Maximilien Lehujeur, Amin Kahrizi, Odile Abraham, Loic Michel, Thomas Bardainne, Antoine Lescoat, Lila Vivin, Julien Blanchais, Christopher Boulay, Thibaud Devie, Sérgio Palma-Lopes, Olivier Durand, and Gautier Gugole

Protection against sea submersion is a key point for the management of coastal areas. Operators need tools to monitor the aging of the sea dikes in order to reduce the risk of catastrophic events such as the Xynthia storm that occurred in 2010 (west of France). Long-term monitoring of these structures can be done using the ambient seismic noise produced by a combination of natural sources (e.g. the impact of swell on the structure, water currents, the wind force on ground-anchored constructions, etc.) and/or nearby anthropogenic sources (e.g. road/pedestrian traffic, coastal activities, etc.).

Continuous ambient noise recordings can be used for monitoring structures by detecting small variations in seismic velocities related to localized degradations that cannot be detected visually. However, this monitoring technique requires sufficient energy in the proper frequency range for the intended application (typically at wavelengths of the order of the size of the structure or less). Additionally, the distribution of the sources must be relatively stable over time in order to interpret the velocity variations explicitly. The case of sea dikes is particularly challenging as the seismic noise is highly variable due various factors, like the water height variations during the tidal cycle, the variations in tidal intensity during the year, or the effects of the climatic conditions on the direction and intensity of the swell.

This study is conducted in the framework of the SEEWALL project, which aims to develop a system for monitoring sea dikes using ambient seismic sources. A dike located on the Noirmoutier Island (France) has been instrumented with permanent accelerometers along with several geophysical and meteorological probes which have been recording continuously for about one year. This contribution focuses on the identification of the essential properties of the ambient seismic noise recorded in this setting and seeks to evaluate how these properties affect our ability to measure temporal variations of the seismic waves velocity. In other words, our objective is to identify the noise sources that contribute most favorably to the approximated empirical Green’s functions and/or that are highly repeatable over time, in order to develop methods that can be applied to various dikes and to optimize the type and amount of seismic data required to monitor such structures.

How to cite: Lehujeur, M., Kahrizi, A., Abraham, O., Michel, L., Bardainne, T., Lescoat, A., Vivin, L., Blanchais, J., Boulay, C., Devie, T., Palma-Lopes, S., Durand, O., and Gugole, G.: Characterization of ambient seismic noise sources for long term monitoring of a sea dike: preliminary results of the SEEWALL project., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4258, https://doi.org/10.5194/egusphere-egu23-4258, 2023.

X2.91
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EGU23-16780
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ECS
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On-site presentation
Xuping Feng and Xiaofei Chen

Ambient noise tomography is a revolutionary technique in past twenty years, and has many far-reaching applications from exploration, regional and continental to global scales. Recently, surface wave overtones have been efficiently extracted from ambient noise cross-correlations by the frequency-Bessel (F-J) transform method. The excitations of overtones from noise cross-correlations, however, have not be investigated well. Here we collect 16-day continuous seismic data recorded by a seismic array installed in Mongolia during two super typhoons in 2011. Utilizing the F-J transform, we extract daily multimodal dispersion curves with high signal-to-noise ratios from vertical-vertical (Z-Z) component cross-correlations and transverse-transverse (T-T) component cross-correlations. For both the fundamental mode and overtones, our results show that the cross-coefficients between the wind speeds and the Z-Z dispersion amplitudes over 0.1Hz are over 0.6 in typhoon track regions, which suggests that these two typhoons excite Rayleigh waves over 0.1Hz.  For T-T surface waves, however, typhoons only excite the fundament mode over 0.1Hz, and overtones do not relate to typhoons. Our results indicate that energetic typhoons can efficiently excite multimodal Rayleigh waves while Love waves during this period may not come from the microseisms excited by typhoons, which may help us to deepen our understanding of the coupling system among the atmosphere, oceans and the solid earth.

How to cite: Feng, X. and Chen, X.: Multimodal surface waves during energetic typhoons, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16780, https://doi.org/10.5194/egusphere-egu23-16780, 2023.

Monitoring
X2.92
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EGU23-13164
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ECS
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On-site presentation
Jinwu Li, Anne Obermann, Sin-mei Wu, Pilar Sánchez-Pastor, and Xiaodong Song

The 2008 M7.9 Wenchuan Earthquake is the most devastating event in the last two decades in China. Here, we analyze 8 years (2007–2014) of seismic records to track the normal background level of the media properties, as well as the transient changes associated with tectonic activities (e.g., earthquakes). Understanding the long-term background pattern contributes to identifying transient changes. Temporal velocity variations of the surface waves show clear seasonal fluctuations and a co-seismic velocity drop after the Wenchuan mainshock in the 2-10 s period band. A comparison with meteoric data allows us to conclude that the main mechanism of the seasonal variation is the loading due to precipitation. The seasonal velocity changes exhibit spatial characteristics, where the amplitudes of the seasonal velocity changes are larger in the Tibet Plateau and smaller in the Sichuan basin. The spatial pattern is consistent with that of the tectonic deformation. The deformation is strong in the Tibet Plateau, while the Sichuan basin is relatively stable. Furthermore, there is a higher density of cracks in the Tibet Plateau than that in the basin.

Moreover, we increased the time resolution of the noise cross-correlations to twenty days to investigate changes in media associated with the 2008 mainshock by analyzing 1.5 years of data from mid 2007 to 2008 for the surface wave at 2-10 s period band. Compared with the waveforms from seismically quiet time, we observe that the waveform similarity of surface waves decreased significantly about 10 days prior to the mainshock and persisted low until the end of September 2008. To exclude that our observation is related to a changing source pattern, we analyzed the seismic activity in the Sichuan region and the frequency spectrum of the ambient noise field in the corresponding time. Our results suggest that the decorrelation may indeed indicate a regional change in the scattering properties starting 10 days prior to the Wenchuan earthquake.

How to cite: Li, J., Obermann, A., Wu, S., Sánchez-Pastor, P., and Song, X.: Temporal changes in velocity and scattering properties in the Sichuan region, China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13164, https://doi.org/10.5194/egusphere-egu23-13164, 2023.

X2.93
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EGU23-10372
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ECS
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On-site presentation
Pratul Ranjan, Laurent Stehly, and Estelle Delouche

Ambient noise cross-correlations or auto-correlations provide near real-time information about subsurface properties. Changes in the Green’s function obtained from auto-correlations/cross-correlations inform us about velocity changes in the medium (dv/v). Numerous studies have found good correlation between dv/v and medium changes related to a large earthquake, volcanic activity, or even seasonal changes at shallow depths. Another seismic parameter which helps estimate such medium changes is the rate of decay of coda waves or the coda Quality factor (Qc). Low Qc estimates from earthquake data has been shown to represent cracks/fracture as well as fluid migration. Application of ambient noise data for Qc estimation are relatively recent (past 5 years), especially in the Alps and Japan, where good correlation was found with the regional geology. Qc measurements using ambient noise data can ensure continuous monitoring unlike those from earthquakes. In this work, we evaluate the feasibility of monitoring medium changes with Qc by using ambient noise data from Greece. We perform autocorrelation of noise data from the permanent network in Greece over a period of 2010-2021. Preliminary analysis shows a seasonal pattern in Qc at several stations when considering short period bands, which is likely related to seasonal changes at shallow depths due to precipitation. Stations with clear seasonal pattern in the dv/v are correlated with the seasonal pattern in Qc, which confirms that Qc perturbations indeed represent physical changes. Stations which show weak seasonality in dv/v have a seasonality pattern in Qc with a lag of similar number of days. These results suggest than Qc based monitoring has the potential to act as a supplementary data set to dv/v and may even provide more information about the nature of medium change based on whether Qc is related to scattering or intrinsic attenuation.

 

How to cite: Ranjan, P., Stehly, L., and Delouche, E.: Exploring the feasibility of seismic monitoring using ambient noise coda Q: Experiments in the Aegean (Greece), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10372, https://doi.org/10.5194/egusphere-egu23-10372, 2023.

X2.94
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EGU23-10612
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ECS
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On-site presentation
Zhiqiang Liu

Recently, advances in the ambient noise analysis provide new ways to detect the velocity changes in the volcanic region by measuring the time delay of the daily cross-correlation functions (CCFs). Despite abundant studies on coda waves, studies examining the direct surface waves are relatively rare because of the influence of passive noise sources. However, direct surface waves have stronger energy and carry depth information, which can be obtained by the dispersion inversion. The direct surface waves' propagation direction along the great circle path is also beneficial for conducting tomography by finding a stable passive noise source, which is key to extracting depth-dependent velocity changes. Here, we used direct surface wave to detect velocity change caused by 2018 KIlauea volcano eruption and 2019 Ridgecrest earthquake. The results show that the noise-based direct surface wave is a powerful tool to study the change of earth medium caused by geological hazards, and can accurately obtain the information of the lateral position and depth position of the change.

 

How to cite: Liu, Z.: Detecting seismic velocity change by noise-based direct surface wave, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10612, https://doi.org/10.5194/egusphere-egu23-10612, 2023.

X2.95
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EGU23-7636
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ECS
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Highlight
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On-site presentation
Yang Lu, Qing-Yu Wang, and Götz Bokelmann

Soil moisture is a key metric to assess soil health. Water held in the shallow subsurface between soil particles enables various biogeochemical and hydrological processes indispensable to soil functions. Potential soil moisture deficit may raise the irrigation demands, which further exacerbates the stress on the water supply. The changes in soil moisture can impact climate, further amplifying the climatic anomalies and intensifying extreme weather events. Thus, understanding soil moisture and its dynamics over time are of broad scientifical interest and practical implications.

Despite the vital importance of soil moisture, it still lacks sufficient means to properly assess the parameter at a regional scale, which is an essential research dimension for addressing practical issues in the agricultural and environmental sectors.

Ambient noise seismology provides new possibilities to infer subsurface changes in a real-time, non-intrusive, and costless manner. In this study, we map the temporal variations in soil moisture for the great Alpine region and the Italy peninsular with ambient seismic noise. It is the first time that the seismic method has been applied to map water resources at a regional scale using an ordinary seismic network setup. The seismic method helps in bridging the resolution gap between current pointwise (e.g., tensio-, electrical- and neutron-meter) and global (e.g., satellite-based remote sensing) investigations, providing complementary information for both scientific research and public decision-making.

How to cite: Lu, Y., Wang, Q.-Y., and Bokelmann, G.: Inferring deep soil moisture variations in Central Europe using seismic method, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7636, https://doi.org/10.5194/egusphere-egu23-7636, 2023.

X2.96
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EGU23-7992
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ECS
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On-site presentation
Juan Ibarra Morales, Raphael S. M. De Plaen, Víctor Hugo Márquez Ramírez, Francisco Ramón Zúñiga Dávila-Madrid, and Raul Arámbula Mendoza

The temporal variation of seismic velocity gives us information about the crust’s stress state and the relative changes associated with magmatic, tectonic, and meteorologic activity. In the present study, we analyze the temporary seismic velocity changes under Volcan de Colima to identify its relationship with volcanic and non-volcanic sources, evaluate the seasonality of the variations and describe the impact that the meteorology has on the changes. The signals of seismic velocity variation used in this work were measured using the single-station cross-component correlation technique applied to traces registered at four stations in the period 2013 – 2017. The data was analyzed in two frequency bands: 0.1 – 1 and 1 – 2 Hz.

We validate the relationship between the velocity variations and three meteorological parameters, rain, temperature, and atmospheric pressure, using wavelet coherence analysis. After fitting a linear model, we identified the environmental factors with the most impact on the seismic velocity are: 1) the rainfall-induced pore pressure, correlated negatively with the seismic velocity and causing changes close to the order of -0.5%; 2) thermoelastic strains correlated positively with the seismic velocity and causing velocity variations between -0.5 and 0.5%. Atmospheric pressure has a smaller impact, mainly of the order of 10-3%.

How to cite: Ibarra Morales, J., De Plaen, R. S. M., Márquez Ramírez, V. H., Zúñiga Dávila-Madrid, F. R., and Arámbula Mendoza, R.: Influence of meteorology on the variations of crustal seismic velocity in Volcan de Colima, Mexico using Noise Interferometry, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7992, https://doi.org/10.5194/egusphere-egu23-7992, 2023.

Imaging and other applications
X2.97
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EGU23-1171
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ECS
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On-site presentation
Camilla Rossi, Francesco Grigoli, Paolo Gasperini, Stefano Gandolfi, Chiara Cocorullo, Timur Gukov, and Paolo Macini

To design an efficient seismic monitoring infrastructure, the characterization of the background seismic noise level of each potential seismic station installation site is one of the most important data-quality metrics used to evaluate the suitability of such sites to host the seismic network. The background seismic noise can be generated by different sources such as, ocean waves (microseisms), atmospheric turbolences (strong wind and storms), and anthropogenic activities. Such disturbances are characterized by specific frequency bands, time-occurrence (diurnal and seasonal variation), and site location (close to populated area or to the coasts). Reducing the effect of these noise sources is one of the main challenges to face for designing seismic monitoring networks and, more specifically, when selecting the hosting site of a seismic stations. A solution to attenuate the seismic noise effect is obtained by deploying seismic stations in boreholes. The noise level reduction with depth has been observed and studied by different authors, however a general law estimating the sufficient depth to gain is still missing. In this study, we analyse the continuous seismic noise level at S. Potito-Cotignola gas storage in the Po Valley (Northern Italy) recorded from January 2019 to December 2021 by a broadband (BB) seismic station at surface and a vertical array composed by 6-short period 3-components seismometers installed at depth ranging between 35 to 285 m in borehole. We aim to characterize the seismic noise by computing the amplitude noise reduction in terms of dB as a function of depth for different frequencies and the SNR by selecting three seismic events, with different epicentral distance and magnitude. Our results show that the noise level decreases with depth following a logarithmic empirical trend and the lowest magnitude event records the maximum SNR difference between the deepest sensor and the one at the surface. The estimated empirical relationships can be used to help the design microseismic monitoring networks in similar geological settings.

How to cite: Rossi, C., Grigoli, F., Gasperini, P., Gandolfi, S., Cocorullo, C., Gukov, T., and Macini, P.: Estimation of amplitude noise reduction as a function of depth recorded by a deep vertical array (Northern Italy), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1171, https://doi.org/10.5194/egusphere-egu23-1171, 2023.

X2.98
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EGU23-8432
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On-site presentation
Shubhasmita Biswal and Sushil Kumar

The Western Himalaya is one of the most complex and heterogeneous seismotectonic units of the Alpide-Himalaya seismic belt. The region has distinctive physiographic characteristics because of the way that they have changed and evolved over the course of time. The purpose of the present investigation is to understand the seismotectonic architecture beneath the study area which is seismically very active. Twenty broad-band seismic stations have been employed to record the surface wave data to study the crustal structure beneath the western Himalayas. We find phase and group velocities of Rayleigh waves for the region with periods between 4 and 30s. To obtain layered S wave velocity models, the dispersion curves are inverted. The crustal velocity structure beneath the region is found to vary significantly. The average estimated S-wave velocity is ~ 3.8 km/s down to 30 km depth. We also observed a low-velocity layer in the middle crust of the higher Himalayas section and the interpretation from the present analysis is consistent with available geological data.

 

How to cite: Biswal, S. and Kumar, S.: Crustal structure beneath the Western Himalayas from surface wave dispersion analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8432, https://doi.org/10.5194/egusphere-egu23-8432, 2023.

X2.99
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EGU23-14933
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ECS
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On-site presentation
Peter Iregbeyen, Sebastiano D'Amico, Luciano Galone, and Emanuele Colica

Pocket beaches, otherwise known as embayed beaches are beaches whose existence are traceable to human activity or natural occurrence. These beaches are found to be confined within the base of geological structures or artificially designed set up such as groin, hence, pocket beaches are always subject to various attacks via anthropogenic or natural forces. These attacks in many cases reflects in the thickness of the beach sediments and therefore determine the extent to which it can survive when hit by unfriendly environmental impact. Estimation of the sedimentary thickness of the beach is a vital tool in a successful geomorphological investigation geared towards the effective execution of coastal area management. This study aims to estimate the sedimentary thickness in several pocket beaches located in Malta using the passive seismic survey method of Horizontal-to-Vertical spectral ratio (H/V). This geophysical survey method employs seismic noise to estimate the depth or thickness of a sedimentary layer over a bedrock with higher shear wave velocity.  Although in recent years, this methodology has increased in popularity in geological investigations, however, there are few examples of the application of this approach to marine sandy beaches in the scientific literature, making this study a novel contribution to the field. The results of the study revealed clear H/V peaks on the beaches studied, with frequency variations corresponding to the expected sediment thickness variations. The latter was also computed by modelling of the H/V curves as well as the use of known data. The application of the H/V technique to the Maltese pocket beach system has demonstrated its effectiveness in providing valuable information for the effective use in the management of the coastal environments. This study has been supported by the SIPOBED project financed by the Malta Council of Science and Technology (MCST) - Space Reearch Funds

 

How to cite: Iregbeyen, P., D'Amico, S., Galone, L., and Colica, E.: Pocket beach management: the use of ambient noise to estimate beach sedimentary thickness, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14933, https://doi.org/10.5194/egusphere-egu23-14933, 2023.

X2.100
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EGU23-1284
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ECS
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On-site presentation
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Jana Klinge, Dirk Gajewski, Celine Hadziioannou, and Jan Walda

The adoption of machine learning in different sectors demonstrates a huge potential of multiple techniques applicable to learn specific features of a dataset. We aim to make use of machine learning methods to predict the development of seismic wave fields between two seismic stations and use this information to remove random noise post-measurement, considering the phase and time information of the signal. Thereby, the initial approach follows the use of an autoencoder network in a self-supervised fashion. Aiming to reconstruct its input, the form of the autoencoder corresponds to the traditional U-Net structure but expands with residual blocks for increased network capacity. To refine results, we modify the interrelated training process of encoding and reconstruction and separate it into sequential phases. To make sure that the dataset includes multiple sources and thus provides various features, we use field data gathered at a seismic exploration site in an area containing several roads, wind turbines, oil pump jacks and railway traffic. Using the well-known autoencoder network structure and applying it in the context of transfer learning enables us to automatically learn a representation of the wave field and, more importantly, predict its spatial development based on different frequency bands. The gained knowledge can be used in future directions to exclude non-relevant parts of the data in the context of denoising and to compare results to currently used methods such as the Wiener optimum filters.

How to cite: Klinge, J., Gajewski, D., Hadziioannou, C., and Walda, J.: Wave field prediction for denoising of seismic measurements using an autoencoder network, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1284, https://doi.org/10.5194/egusphere-egu23-1284, 2023.

Posters virtual: Wed, 26 Apr, 14:00–15:45 | vHall GMPV/G/GD/SM

The posters scheduled for virtual presentation are visible in Gather.Town. Attendees are asked to meet the authors during the scheduled attendance time for live video chats. If authors uploaded their presentation files, these files are also linked from the abstracts below, but only on the day of the poster session. The button to access Gather.Town appears just before the time block starts.
Chairperson: Yesim Cubuk Sabuncu
vGGGS.5
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EGU23-6840
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ECS
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Highlight
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Virtual presentation
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Gyanasmita Pradhan, Ramakrushna Reddy, and Paresh Nath Singha Roy

Ambient noises are generated due to the interaction of atmosphere with the solid Earth and the noises which occur within the time period of 2-20s are known as microseisms. As the noise generation mechanism is not very well understood in the extreme climatic condition of Antarctic continent, in this study we target to understand the microseism generation in the South Pole station situated in the Antarctic continent. We have carried out our analysis using continuous data from IRIS data management center. Our main focus is to characterize the source direction of noise and their seasonal amplitude variations. We have employed the frequency dependent polarization analysis through the Eigen decomposition of the 3×3 spectral covariance matrix.

 The source of the noise have been analyzed using the backazimuth and time period for all the three bands of microseism, SPDF (short period double frequency), LPDF (long period double frequency), and PM (primary microseism). We observed that the noise is mainly due to the strong winds of Southern Ocean and some amounts of noise are also from the Ross Sea. In southern hemisphere, winter starts from May and it ends in August and also the number of polarized signals is lower in the winter season, and it is comparatively higher in the summer season. Additionally, when we plot Power spectral density against time period we see the splitting of the double frequency microseism into SPDF and LPDF which is only observed in the summer months and not in the winter months (only one single peak is observed).  Because, in the winter month’s sea ice concentration is extremely high in the South Pole; therefore, there is no significant wind interaction with sea waves of the coastal part which generates the SPDF. In winter, the continent is completely frozen; however, the amplitude of noise is high due to the strong winds. In summer, the noise is generated due to the low pressure systems develops in Southern Ocean which leads to cyclones in the Ross Sea. Antarctic circumpolar current also plays a significant role in the generation of noise. Therefore, we can conclude that the source of noise is from the Southern Ocean and Ross Sea. Also, we noticed the seasonal variation in the splitting of the double frequency microseism due to variation in the sea ice concentration.

How to cite: Pradhan, G., Reddy, R., and Singha Roy, P. N.: Ambient noise variation in the South Pole, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6840, https://doi.org/10.5194/egusphere-egu23-6840, 2023.