SM3.1

Coda wave interferometry is an important tool to gain insights into the dynamic evolution of the Earth. A limitation of the majority of current studies employing this technique, is the neglect of variations in scattering strength in the lithosphere. Geological observations indicate that scattering properties can strongly vary laterally, especially in complex geological settings, e.g. in the vicinity of active tectonic or volcanic areas.

In presented work we explore the implications of non-uniform distribution of scattering strength on the spatio-temporal sensitivity of coda waves. In the first part, we numerically derive 2-D coda wave sensitivity kernels based on Monte Carlo simulations of the radiative transfer process, considering lateral heterogeneity of the crust. The kernels are calculated for three different observables, namely travel-time, decorrelation and intensity. Our results illustrate that laterally varying scattering properties can have a profound impact on the sensitivities of coda waves.

In a second part, we validate the kernels. Firstly, synthetic lapse-time based travel-time changes are calculated using the kernels for non-uniform media. Using these synthetic observations, we conduct damped least-squares inversions to localise changes in space for both a fault zone and volcanic setting. We compare the accuracy of localisation of the medium changes between inversions carried out with kernels for uniform and non-uniform media. Our results demonstrate that superior localisation of the seismic anomaly is obtained when considering local scattering information by employing kernels for non-uniform media. This holds for the fault zone as well as the volcanic setting. The stability of the results is verified by conducting inversions where 10dB white noise is added to the synthetic time-shift observations.

How to cite: van Dinther, C., Wang, Q., Margerin, L., and Campillo, M.: The impact of laterally varying scattering properties on subsurface monitoring using coda wave sensitivity kernels: Application to fault zone and volcanic areas, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11414, https://doi.org/10.5194/egusphere-egu22-11414, 2022.

Seismic interferometry is a powerful and well-established technique that relies on cross-correlating seismic observations at different receiver locations to yield new seismic responses that, under certain conditions, provide a useful estimate of the Green's function between the given receiver locations, as if there was a source at one of these locations. The inter-receiver signals thus estimated allow us to monitor and remotely illuminate near-surface crustal structures.

Underpinning seismic interferometry is the principle of stationary phase, which states that non-trivial contributions to highly oscillatory integrals, such as those found in interferometry, arise from stationary points of the phase of these cross-correlations. This principle is widely invoked to make approximations in interferometry, both in theory, to derive and simplify interferometric formulations, as well as in practical applications, to justify the use of non-ideal source or receiver distributions. Further, it has been established that spatial variations in the source intensity must be smooth in order to apply this approximation.

While there have been some empirical explorations of the uncertainty introduced by this approximation, the errors have not yet been quantified analytically, and neither the effects of non-smooth variations in the sources, nor of statistical correlations between sources, have been formally considered. In this work, we apply a mathematical framework to seismic interferometry in two dimensions. This analysis yields an exact expression for the error in the interferometric estimate of the inter-receiver Green’s function. Moreover, we extend this approach to a scenario of inhomogeneous, statistically correlated sources, and illustrate the effects of source correlation and roughness on the phase and amplitude of the stationary-phase interferometric estimate. We provide statistical conditions to ensure that the stationary phase estimate is unbiased, and give an explicit bound for the error in the estimated spectrum. These error quantities are given in terms of parameters that are either known (such as the inter-receiver distance), or can be estimated from empirical data. Therefore, we expect these results to be applicable in practical interferometric studies that make use of the stationary phase approximation, as a tool to quantify error and uncertainty in empirical results.

How to cite: Ayala-Garcia, D., Branicki, M., and Curtis, A.: The stationary phase approximation in seismic interferometry: Error quantification and the effects of source correlations., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12941, https://doi.org/10.5194/egusphere-egu22-12941, 2022.

Ambient noise tomography (ANT) based on empirical Green’s functions (EGFs) retrieved from cross-correlation functions (CCFs) of ambient noise is widely used to construct shear-wave velocity structures. EGFs from ambient noise can be treated as virtual seismograms with one station working as a virtual source and the other station working as a receiver. We propose a method named two-station C² method(Rao et al., 2021), using one single station as a virtual source to obtain surface waves between a pair of asynchronous stations. This method can significantly improve ray path coverages and enhance the resolution in ANT for areas between asynchronous seismic arrays.

In our method, we select three stations, called a station triplet, which share the same great-circle path. We take one long-term station as a virtual source rather than using a number of stations as sources in the C³ method(Stehly et al., 2008; Ma and Beroza, 2012; Spica et al., 2016; Zhang et al., 2019). We use data from the USArray to demonstrate the feasibility of our method in retrieving surface waves from asynchronous stations.

Due to the harsh environment and inaccessibility of most of parts of the plateau, it is nearly impossible to deploy a large-scale synchronous seismic array across Tibet. In the past few decades, several isolated arrays have been deployed in Tibet at different periods of time. ANT has been applied to Tibet to generate phase velocity maps using these seismic arrays (e.g., Yang et al.,2012;Xie et al.,2013; Shen et al., 2016). However, due to the fact that these seismic arrays were not deployed synchronously, inter-array paths between asynchronous arrays cannot be obtained from the traditional C¹ method, resulting in low resolution in the gaps of these seismic arrays.

We applied our method to the two seismic arrays (Z4 and X4) deployed in NE Tibet. The Z4 array was deployed from July 2007 to July 2008 and X4 from September 2008 to September 2009. For these two arrays, if we follow the C¹ method, we can get at most 153 paths for Z4 array and 300 paths for X4 array. But no crossing-array paths can be obtained. Fortunately, there is a permanent Chinese National Seismic Network (Zheng et al., 2010) deployed across China. We can take the permanent stations from the Chinese National Seismic Network as source stations and obtain C² functions following our method. Here, to illustrate the application of our C² method for these two arrays, we select 153 permanent stations from the Chinese National Network as virtual sources. And, using these stations and our C² method for these two arrays, we can retrieve 413 C² functions with the source stations located within 5 degrees of the great-circle paths of receiver station pairs. The path coverage is improved by over 91%. Combining C¹ and C² paths, we can much better image the structures between these two arrays.

How to cite: Rao, H. and Luo, Y.: Extracting surface wave dispersion curves from asynchronous seismic stations in NE Tibet: A two-station C2 method, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6752, https://doi.org/10.5194/egusphere-egu22-6752, 2022.

The Vrancea Seismic Zone (VSZ), located in Romania, at the sharp bend of the southeastern Carpathians, is an anomalous intraplate seismic region releasing the largest strain in continental Europe. The seismicity is concentrated in a high-velocity focal volume down to 200 km, challenging classic earthquake mechanism theories due to its remote location and deep hypocenters in an expectedly ductile lithosphere. The last significant earthquake in Vrancea occurred in 1977 causing destruction to Romanian cities and long-term economic damage to an already struggling developing country. The seismic infrastructure was underdeveloped in Romania at that time and the earthquake was not well-recorded locally. The recent increase in seismic station coverage in Romania now provides the opportunity to systematically study seismogenic processes and apply the most novel processing methods.

We apply the recently developed algorithm of Virtual Earthquake Approach (VEA, Denolle et al., 2013) to reconstruct realistic ground motion records as if the stations operating today recorded historical earthquakes, such as the 1977 event. Predicting accurate ground motion is critical for earthquake hazard analysis, particularly in situations where sedimentary basins trap and amplify seismic waves. We gathered one year of three-component ambient noise data from 44 broadband seismic stations around the VSZ. We then construct the ambient noise Green’s tensor between pairs of stations and add the signatures of a realistic earthquake: double couple mechanism, buried source and a realistic earth model in the epicentral area.

Using the Romanian earthquake catalog (Romplus, www.infp.ro), we selected the last Mw>6.0 earthquakes since 1940 from the area and extracted the moment tensor solutions. Subsequently, we simulate the ground motion generated by these earthquakes recorded by modern seismometers decades after their occurrence. Our new results demonstrate the viability of this innovative method and provide a unique opportunity for more accurate seismic hazard analysis.

Keywords: ambient noise, historical earthquake, virtual earthquake approach.

Reference:

• A. Denolle, E. M. Dunham, G. A. Prieto, G. C. Beroza, Ground motion prediction of realistic earthquake sources using the ambient seismic field, Journal of Geophysical Research: Solid Earth, Vol. 118, 2102–2118, doi:10.1029/2012JB009603, 2013.

How to cite: Placinta, A. O., Petrescu, L., Borleanu, F., and Radulian, M.: Historical earthquake simulation using ambient seismic noise in Vrancea (Romania): preliminary results, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8290, https://doi.org/10.5194/egusphere-egu22-8290, 2022.

We show that the geometry of a seismic array affects estimates of velocity and propagation direction of ambient seismic noise wavefields measured with beamforming techniques. We demonstrate how this results in apparent anisotropy estimates and present first approaches to mitigate the effect.

Beamforming is an array technique originating from earthquake seismology that has become increasingly popular to analyse the ambient noise wavefield with the goal to characterise ambient noise sources (e.g., regions of origin of Love and Rayleigh waves) as well as subsurface structures (shear-velocity profiles, fracture orientation). Beamforming techniques estimate the dominant velocity, direction of propagation, and (in case of three-component data) the polarisation of a wavefield recorded within a limited time window at a seismic array. An important parameter in beamforming is the array response function, which shows the response of an array to a wave that is arriving directly from below. It can be thought of as the fingerprint of the array and depends on the array geometry, i.e., number of stations, station spacing, and orientation of station pairs. A biased array can lead to oversampling of certain directions and, thus, prioritising them in the beamform heatmap.

The first attempt to mitigate the influence of the array focuses on analysing the orientation of station pairs in an array and applying a weighting matrix in order to enhance contributions from orientations that are underrepresented. This approach leads to a modified array response function, that looks more regular and has the fingerprint of the array partly removed. Using synthetic data and different array geometries we demonstrate the effect on the estimated anisotropy.

The second approach is based on simulating synthetic, isotropic wavefield recordings at an array of choice and measuring their dominant velocities and propagation directions using beamforming. Comparing expected and observed values shows that the effect of the array can be significant, in particular when multiple sources act simultaneously (as is often the case for ambient noise): both measured velocities and propagation directions are affected by the design of the array, leading to erroneous anisotropy estimates. Once we have an estimate of array-induced anisotropy, however, we can subtract it from the anisotropy measured in real data and thereby reduce the effect. Examples for different array geometries are presented and compared.

How to cite: Löer, K. and Finger, C.: Mitigating array-induced bias in ambient noise beamforming, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3956, https://doi.org/10.5194/egusphere-egu22-3956, 2022.

To improve methods in full-waveform ambient noise tomography and monitoring it is important to have knowledge of the spatio-temporal variations of the noise source distribution. Without this knowledge, an uneven distribution of sources may bias observations, and a changing source distribution may be falsely interpreted as subsurface velocity changes. By combining two methods to locate noise sources and decreasing the computational cost, we are able to invert for the global noise source distribution of the secondary microseisms on a daily basis. Additionally, we present a web framework where the Seismic Ambient Noise Source (SANS) maps are made available to the public. 

Many different methods to locate ambient noise sources have been developed. Bowden et al. (2021) show how a more data-driven Matched-Field Processing (MFP) approach and a more rigorous finite-frequency sensitivity kernel method can be derived from one another.  Igel at al. (2021) implement spatially variable grids and pre-computed wavefields to make the finite-frequency inversion more efficient. This has made daily inversions on a regional to global scale feasible for secondary microseismic noise sources in a frequency range from 0.1 to 0.2 Hz. Since the inversion approach allows for prior information to be implemented, we use the more efficient MFP method to create an initial model and steer the inversion in the right direction. 

In collaboration with the Swiss National Supercomputing Centre (CSCS) we are able to run this workflow on a daily basis. The resulting noise source maps are subsequently made available to the public through our web framework SANS. A user can look through all iterations of the inversions, download all model and inversion files, and implement them in their own methods. Additionally, code is provided to help the user create plots and simplify the implementation in other studies. We are looking for collaboration with ambient noise tomography studies to investigate how the implementation of noise source maps could potentially improve the resulting structure models.

How to cite: Igel, J., Bowden, D., and Fichtner, A.: SANS: Publicly available daily seismic ambient noise source maps on a regional to global scale, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3479, https://doi.org/10.5194/egusphere-egu22-3479, 2022.

Matched Field Processing (MFP) is a technique to locate the source of a recorded wave field. It is the generalisation of beamforming, allowing for curved wavefronts. In the standard approach to MFP, simple analytical Green's functions are used as synthetic wave fields that the recorded wave fields are matched against. We introduce an advancement of MFP by utilising Green's functions computed numerically for real Earth structure as synthetic wave fields. This allows in principle to incorporate the full complexity of elastic wave propagation, and through that provide more precise estimates of the recorded wave field's origin. This approach also further emphasises the deep connection between MFP and the recently introduced interferometry-based source localisation strategy for the ambient seismic field. We explore this connection further by demonstrating that both approaches are based on the same idea: both are measuring the (mis-)match of correlation wave fields. To demonstrate the applicability and potential of our approach, we present two real data examples, one for an earthquake in Southern California, and one for secondary microseism activity in the Northeastern Atlantic and Mediterranean Sea. We provide an accompanying simple code example to illustrate the method on github.

How to cite: Schippkus, S. and Hadziioannou, C.: Matched Field processing for complex Earth structure, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-252, https://doi.org/10.5194/egusphere-egu22-252, 2022.

Seismic noise above 2 Hz band would interfere with the lower frequency output from 3rd generation gravitational wave interferometers.
Sos Enattos, Sardinia, is a potential site for the future Einstein Telescope, which will be built hundreds of meters underground. To characterise one aspect of the seismic field at this potential site, I examined trends in wind speed, direction, and seismic noise. Elevated seismic energy across a broad range of frequencies occurs when wind speeds are higher. At frequencies below 1 Hz, sources appear to be regional (ocean generated microseisms). At 1-50Hz, local sources dominate. Deeper, the effects of local wind-generated noise are reduced and masked by other noise sources.

How to cite: Ensing, J.: Wind generates seismic noise at Sos Enattos, Sardinia, potential site for the Einstein Telescope., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4434, https://doi.org/10.5194/egusphere-egu22-4434, 2022.

The mantle transition zone is delineated by seismic discontinuities at approximately 410-km and 660-km depth. The lateral variations in reflectivity and depth of the two seismic discontinuities reflect changes in mineralogy composition, thermal state, and water content, that is key to understanding the Earth’s dynamics. Traditional imaging methods based on the analysis of earthquake signals, such as seismic tomography and receiver function analysis, are often limited by earthquake occurrence and uncertainties related to the earthquake source parameters. Recent studies demonstrated the feasibility of recovering body waves from noise correlations, providing new prospects for imaging deep Earth [e.g., Poli et al., 2012; Boué et al., 2013]. 

In this study, we map the 410-km and 660-km discontinuities beneath the European Alps using reflected body waves recovered from noise correlations. To that end, we compute noise correlations using four years of continuous recordings from ∼1200 broadband stations in the greater Alpine region. To enhance the signal-to-noise ratio of the body-wave reflection phases, for each station pair, we stack daily noise correlations in selected time spans with a high level of near vertical-incident body waves and less dominant surface waves [Lu et al., 2021]. We further stack noise correlations of station pairs with common/nearby reflection points to obtain local zero-offset reflection waveforms. The retrieved P410P and P660P reflection phases clearly reveal lateral variations of both reflectivity and depth of the two discontinuities in the studied region, providing new constraints in addition to existing results from earthquake tomography and receiver function analysis. Besides, this study also sheds light on the strategies to recover deep reflection phases from noise correlations.

How to cite: Lu, Y. and Bokelmann, G.: Mapping the 410-km and 660-km discontinuities across the European Alps using noise correlations , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4747, https://doi.org/10.5194/egusphere-egu22-4747, 2022.

The spatial zero-lag amplitude distribution of correlations obtained from vertical component dense array records of diffuse seismic wave fields is characterized by a large-amplitude feature around the origin referred to as focal spot. In the context of time-reversed surface waves it can be understood as the collapse of a converging wavefront. The analogy to the SPAC method implies that the nine-component solutions that describe the spectral features can readily be applied to the time-domain focal spot shape to estimate local phase velocity, which connects this method to established elastographic medical imaging. In contrast to sparse SPAC arrays, modern dense arrays allow a properly resolved focal spot at near-field distances for an inversion-free sensor-by-sensor image compilation, with intriguing implications for vertical and lateral resolution enhancement. We demonstrate the applicability of this method on the basis of Rayleigh wave focal spots in the 60 s to 200 s period range that are obtained from ambient field correlations using USArray data between -125 and -90 degrees west. The 1000 s long noise correlations are computed using standard techniques, Gaussian filtered around the central target frequency, and the spatial zero-lag distribution fitted with the SPAC Bessel functions model to distances of 1.2 wavelengths. The effectiveness and accuracy of this approach is demonstrated by the impressive similarity between the obtained “instantaneous image” at 60 s and surface wave tomography results from the literature. The stark velocity contrast between the western and central U.S. is clearly resolved, but the similarity extends to well resolved details including the Sierra Nevada, the Snake River Plain feature, the circular low-velocity rim around the Colorado Plateau, and part of the Mississippi Embayment. Based on this benchmark result obtained with vertical-component data we explore the internal consistency of the obtained maps towards longer periods and the associated extension of dispersion measurements; we probe the limits of the near-field approach by systematically lowering the fitting distance to sub-wavelength scales; and we quantify the similarity of vertical-radial results. The zero-lag amplitude distributions in the wavenumber domain show signatures of near-vertically incident energy associated with global body wave reverberations. We mute this energy by neglecting time windows from the correlation data after global large earthquakes. Systematic tests of the window length, and again the comparison to the benchmark observations, inform about the efficiency of this approach. We conclude that time-domain dense array near-field imaging yields accurate distributions of the velocity structure. We emphasize the disadvantageous low randomization of the long period ambient field, and the sub-array shapes resulting from the rolling USArray deployment. Imaging on smaller scales should therefore work better.

How to cite: Tsarsitalidou, C., Boué, P., Hillers, G., Giammarinaro, B., Stehly, L., and Campillo, M.: Focal spot imaging on USArray records, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9440, https://doi.org/10.5194/egusphere-egu22-9440, 2022.

How to cite: Giammarinaro, B., Tsarsitalidou, C., Hillers, G., and Boué, P.: Effect of dense array shapes and directional incidence on seismic surface wave focal spot imaging results, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3653, https://doi.org/10.5194/egusphere-egu22-3653, 2022.

Six en-echelon arranged volcanic systems are aligned NE-SW along the Reykjanes Peninsula, each comprising a fissure swarm with the central area marked by a maximum volcanic production. Five out of six systems host a high-temperature geothermal field. In this study, we image the shear wave velocity structure of the entire Reykjanes Peninsula using a recently developed one-step 3D transdimensional surface wave tomography. The transdimensional tomography algorithm uses a variable model parametrization by employing Voronoi cells in conjunction with the reversible jump Markov chain Monte Carlo method. We use the frequency dependent-travel times (with a frequency range of 0.1-0.5 Hz) derived from the recorded ambient noise data to image the area. The data are recorded between April 2015 until August 2015 using seismic stations from four different seismic networks (i.e., IMAGE, ÍSOR/HS Orka, REYKJANET, and SIL). The area covered by all stations is 120 km by 70 km. Approximately 45 km by 25 km of the station areal coverage is onshore; the rest is offshore. Additionally, based on the previous studies, using a frequency range of 0.1-0.5 Hz, it is expected to resolve the shear wave velocity structure up to a maximum depth of 10 km. The results show that the algorithm successfully recovered the velocity structure below the areas sampled with sufficient ray paths coverage. The areas with fewer ray paths result in a smoother velocity structure. We observe a few low-velocity anomalies at depths around 4-6 km, which are likely to be associated with the high-temperature fields around those depths. In other words, the low-velocity anomalies appeared below the location of the known high-temperature fields, which are Reykjanes, Eldvörp, Svartsengi, and Krýsuvík.

How to cite: Rahimi Dalkhani, A., Ágústsdóttir, T., Árni Gudnason, E., Zhang, X., and Weemstra, C.: Transdimensional ambient-noise surface wave tomography of the Reykjanes Peninsula, SW Iceland, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12322, https://doi.org/10.5194/egusphere-egu22-12322, 2022.

High-enthalpy geothermal reservoirs have been exploited for electrical power generation worldwide during the last century.  Despite the different definitions of high-enthalpy reservoirs in the literature, one can consider fluid enthalpies of around 800 kJ/kg as high. In terms of temperature, geothermal systems with more than 200°C at 1 km depth can yield high fluid enthalpies. Igneous-related geothermal reservoirs are an abundant though unexploited energy resource on Earth. The thermal energy stored in those reservoirs is much higher but the risk of drilling into a molten magma pocket is very high too.

While there are numerous geophysical exploration techniques developed for the oil and gas industry, few are directed to the geothermal sector, where profitability is much smaller. In this talk, we are going to show the potential of ambient seismic noise interferometry to image high-enthalpy geothermal reservoirs. This approach has been broadly used in many different scenarios but barely in geothermal settings. In particular, we study the Hengill area, which is located in Iceland and hosts three volcanic systems, several geothermal sub-fields and two large power plants, being one of them Hellisheiði (303 MWe, 200 MWt), one of the largest power plants in the world.

We compute a 3D shear-wave tomography from seismic noise records in the Hengill area and compare the results with several geophysical observables derived from borehole measurements in the region, such as steam ratio and formation temperature. Furthermore, we compare the results with a resistivity model obtaining an excellent correlation between both observables overall. We find some discrepancies in small areas that we interpret as a lack of thermal equilibrium. We also identify a promising site for future drilling projects.

How to cite: Sánchez-Pastor, P., Obermann, A., Reinsch, T., Ágústsdóttir, Þ., Gunnarsson, G., Tómasdóttir, S., Hjörleifsdóttir, V., Hersir, G. P., Ágústsson, K., and Wiemer, S.: Imaging high-enthalpy geothermal reservoirs using seismic noise interferometry, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8281, https://doi.org/10.5194/egusphere-egu22-8281, 2022.

The Volcán de Colima is one of the most active volcanoes in North America, but it still has a poorly constrained upper crustal structure. We used ambient seismic noise tomography to generate the highest-resolution three-dimensional shear-wave velocity model of the volcano to date. We measured group velocity dispersion curves of Rayleigh and Love waves extracted from the records of two distinct networks deployed on the Colima Volcanic Complex. Those were regionalized into 2-D velocity maps and then locally inverted using a neighborhood algorithm and an anisotropic parametrization to obtain an accurate shear-velocity model down to 4 km below sea level. 

The resulting model highlights a network of deeply rooted NE-SW low-velocity zones oriented along a local fault system. This low-velocity zone also roughly aligns with the north-south trend associated with the gradual trenchward shift of the magmatic front of the quaternary Colima Volcanic Complex. An overlapping negative radial anisotropy indicates that magma follows vertically oriented structures, such as interfingered dikes, faults, or cracks with a substantial vertical component. Our results also highlight the difference between the former active system, filled with solidified dikes and sills, and the current one, associated with a network of fluid-filled dikes.

How to cite: De Plaen, R., Mordret, A., Arámbula-Mendoza, R., Vargas-Bracamontes, D., Márquez-Ramírez, V. H., and Lecocq, T.: The shallow crustal structure of the Volcàn de Colima: Evidence from ambient noise surface wave tomography, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12913, https://doi.org/10.5194/egusphere-egu22-12913, 2022.

Leeu Gamka is located within a stable continental region, in the hinterland of the Cambrian-Ordovician Cape Fold Belt, which runs parallel to the southern coast of South Africa. Following a swarm of moderate-low magnitude seismicity in the area between 2007 and 2013, documented in the ISC catalogue, researchers from the University of Cape Town deployed an array of 23 geophones between March and June 2015, for the purpose of more precisely locating further events. Although there is no evidence of a fault at the surface, microseismic epicenters aligned along a NW orientation suggest that there may be movement along a blind fault of the same orientation. The anomalous occurrence of earthquakes far removed from an active plate boundary may help improving our understanding of earthquake mechanisms and hazard, while the location of a blind fault may be useful to shale gas exploration in the area.

Potential interest in the Leeu Gamka seismicity and the prospective blind fault motivated further investigation, especially as they occur in a region which has been identified for shale gas exploration. The data used for locating earthquakes was reused to calculate Rayleigh wave group velocity maps. Although the network design was originally optimized for locating earthquakes, with a higher station-density in the centre of the network, a minimum inter-station-distance of 2 km and a maximum inter-station-distance of 60 km, usable Rayleigh wave group velocity maps were obtained.

Our preliminary findings suggest that there is an increase in Rayleigh wave group velocities southeast of a linear feature with a similar orientation and location as the previously located earthquakes. This abrupt lateral change in velocity is interpreted to be a consequence of thick quartzite formations of the Cape Supergroup, with high Rayleigh wave group velocities, having been thrust upwards during the Cape Orogeny juxtaposing them against the lower Rayleigh wave group velocity shale, siltstone, sandstone and diamictite, of the Karoo Supergroup. In this model, the measured earthquakes are most likely a reactivation of an older thrust fault which was active during the Cape Orogeny, but after the deposition of the lowermost Karoo units. This interpretation is consistent with the interpretation of Stankiewicz et al. (2007) who suggested the existence of a blind fault in the area based on the interpretation of a wide-angle seismic refraction line which passes through the study area.

This interpretation highlights the potential risk of the reactivation of blind faults associated with the Cape Orogeny if shale gas extraction and associated wastewater disposal were to proceed. Ambient noise tomography presents a low-cost way both to map the depth of the base of the Karoo Supergroup, and to identify some potentially seismogenic faults in the region, supporting both exploration and associated hazard identification and mitigation.

How to cite: Whitehead, B., Quiros, D., Janse van Rensburg, M., Kahle, B., Kahle, R., and Sloan, A.: Rayleigh wave group-velocity maps from ambient noise tomography near Leeu Gamka, Karoo, South Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8354, https://doi.org/10.5194/egusphere-egu22-8354, 2022.

The orientation of 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 pump-probe method which consists of measuring elastic wave speed using empirical Green’s functions (probe) at different points of the tidal strain cycle (pump) as in Delorey et al. (2021). The approach is applied to data from the AlpArray in the Alpine foreland region, where the orientation of maximum horizontal compressive stress is well-known from borehole breakouts and drilling-induced fractures.

Delorey, A., Bokelmann, G., Johnson, C., Johnson, P. Estimation of the orientation of stress in the Earth's crust without earthquake or borehole data. Nature Comm. Earth Environ. 2, 190 (2021). https://doi.org/10.1038/s43247-021-00244-1

How to cite: Aiman, Y. A., Delorey, A., Lu, Y., Bokelmann, G., and Group, T. A. W.: SHmax Orientation in the Northern Alpine Foreland from Stress-Induced Anisotropy in Nonlinear Elasticity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9171, https://doi.org/10.5194/egusphere-egu22-9171, 2022.

Ambient seismic noise techniques are emerging as a complimentary tool to active seismic surveys for imaging subsurface velocities. However, questions about uncertainties and best practices of different processing schemes remain.

Most often beamforming or cross-correlation techniques are only applied to the vertical component. In studies of ambient-noise surface waves, it is assumed that only the Rayleigh wave is sampled since the Love wave is not polarized in the vertical direction. Recently, horizontal-to-vertical spectral ratios (HVSR) have been integrated into the analysis of surface wave dispersion curves to better constrain the depths and velocities of shallow structures. In this context, the HVSR curves are used to estimate the Rayleigh ellipticity.

Using three-component surface wave beamforming (3CFK) provides the advantage of obtaining the polarization, and hence the wave type, of recorded waves in addition to the wave velocity over a frequency range. Thus, Rayleigh and Love waves can be identified and distinguished from body waves resulting in more accurate dispersion curves. Furthermore, from the polarization parameters, the ellipticity of the Rayleigh wave may be recovered at the same frequency resolution as the Rayleigh wave phase velocities. Thus, the frequency at which the polarization of Rayleigh wave changes from vertical to horizontal can be directly determined. This frequency is related with the commonly observed phenomenon of intersecting Rayleigh modes in dispersion curves. Determination of this so-called osculation frequency helps distinguish the fundamental and higher-mode Rayleigh waves.

In this study, a synthetic three-component realistic ambient noise wavefield has been created and the application of HVSR and 3CFK has been investigated. Uncertainties of both methods are compared with the true velocities and depths. It can be shown that the depth of the first large impedance contrast can be calculated using the osculation frequency retrieved from Rayleigh ellipticity curves and Rayleigh velocities at frequencies smaller than the osculation frequency. This method has less deviations from the true depth than the typical relation using the peak frequency of HVSR curves and a quarter of the average shear velocity above the impedance contrast.

3CFK and HVSR are applied to field data from Weisweiler, Germany, to demonstrate the applicability of the method. In Weisweiler, 15 three-component stations were recording the ambient noise wavefield for 10 days in June 2021. The stations covered a total aperture of about 200 m.

The methodology presented here is especially suited for large three-component nodal networks. The depth of the first large impedance contrast, in dependence of the array geometry, may be mapped fast and efficiently without the need for costly inversion processes, a priori assumptions or additional information from wells.

How to cite: Finger, C., Löer, K., and Saenger, E. H.: Fast near-surface imaging using Rayleigh wave ellipticities and velocities from three-component ambient noise beamforming, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6951, https://doi.org/10.5194/egusphere-egu22-6951, 2022.

Seismic interferometry (SI) is a method that retrieves new seismic traces from the cross-correlation of existing traces, where one of the receivers acts as a virtual seismic source whose response is retrieved at other receivers. When using sources only at the surface, and so-called one-sided illumination of the receivers occurs, not only desired physical reflections are retrieved, but also non-physical (ghost) reflections. These non-physical reflections are caused by internal reflections inside subsurface layers. They are thus particularly interesting to use for monitoring changes in the specific subsurface layer that causes them to appear in the SI result because they could provide valuable information about the physical properties of the subsurface.

We illustrate the potential of SI with active-source data from numerical acoustic modelling using the Groningen subsurface model. This model describes the natural gas field located in the Groningen province in the northeastern part of the Netherlands. The reservoir of the Groningen gas field is located at depths between 2600 m and 3200 m, the total thickness ranges from approximately 100 m to 300 m. The Groningen field is cut by several fault systems, subdividing the field into a large number of fault blocks, and it is a clear example of induced seismicity by gas production.

We investigate the utilization of non-physical reflections retrieved from surface active-source data using SI by cross-correlation and auto-correlation. With multi-offset gathers, besides physical reflections, we retrieve non-physical reflections as well; by muting undesired reflections, we can retrieve better target-related non-physical reflections. To illustrate the potential of the non-physical reflections for monitoring purposes, we apply velocity changes in the Groningen reservoir. With zero-offset gathers, which are retrieved from SI by auto-correlation, we show that in case of velocity changes, the non-physical reflections show a clear change; furthermore, they show a good agreement with the geometry of specific subsurface layers, specifically with the faulted structure. Thus, we can utilize non-physical reflections for imaging and monitoring in the Groningen reservoir.

How to cite: Shirmohammadi, F., Draganov, D., Ras, P., and Wapenaar, K.: Layer-specific imaging and monitoring in the Groningen subsurface using seismic interferometry, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9507, https://doi.org/10.5194/egusphere-egu22-9507, 2022.

Anthropogenic seismic signals attract more and more attention in recent years. Freight trains, among different seismic sources, are of particular interest for seismic velocity monitoring due to several advantages. Trains are persistent, powerful sources that generate seismic tremors equivalent to Mw 2 earthquakes and detectable up to 100 km distance; trains move along fixed trajectories, allowing us to properly account for the source distribution and its coupling between the structure; trains generate high-frequency body-wave energy enabling us to focus on the changes at depth with high spatial resolution. We propose a fault zone monitoring framework through a case study in southern California. Freight trains running through the Coachella Valley are used to monitor changes associated with the San Jacinto Fault. The general steps include identifying sources and constructing a train catalog, extracting body waves through seismic interferometry, measuring travel-time perturbation, and mapping seismic velocity change. We analyze the seismic data from 2010 to 2020 and discover an episode of velocity changes in early 2014, manifested on all station pairs considered. The velocity perturbation shows a complicated spatial pattern, with some station pairs exhibiting positive changes, and others negative changes. We interpret that this velocity perturbation results from an aseismic slip near the edge of the Anza seismic gap and further validate this idea using numerical simulations. We use the Coulomb software to simulate volumetric strain for velocity perturbation and full-waveform modeling to simulate correlation functions for estimating travel-time change. The proposed framework has great potentials to be applied in other settings, from wastewater injection to CO2 sequestration, using freight trains or other type of anthropogenic sources.

How to cite: Sheng, Y., Mordret, A., Sager, K., Brenguier, F., Boué, P., Rousset, B., Vernon, F., and Ben-Zion, Y.: Towards seismic velocity monitoring using anthropogenic seismic signals, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4424, https://doi.org/10.5194/egusphere-egu22-4424, 2022.

Kamchatka, a remote peninsula in eastern Russia, is home to the Kluchevskoy volcano group, one of the largest and most active clusters of subduction zone volcanoes worldwide. Regular eruptions, volcanic and tectonic earthquakes, but also strong meteorological variations leave an imprint on the regional seismic velocity structure. We quantify the temporal velocity variations by applying the method of ambient seismic noise interferometry to waveform data recorded by the temporary KISS deployment and the permanent Kamchatka network. Due to its ubiquitous nature, ambient seismic noise allows for far denser temporal sampling than, e.g., active source or earthquake coda interferometry. However, source variability related, for example, to volcanic tremor activity affects the results retrieved by this method and can lead to decreased reliability. Here, we investigate the impact of the aforementioned environmental factors on the Green’s function of the medium using SeisMIC (Seismological Monitoring using Interferometric Concepts) – a new Python software to conduct noise interferometry surveys. In addition, we discuss the impact of the frequent volcanic tremors and other local seismic events on the stability of the computed Green’s function estimations (i.e., cross-correlations).

How to cite: Makus, P., Sens-Schönfelder, C., Tilmann, F., and Walter, T. R.: Deciphering the Contributions of Volcanic and Environmental Events to Temporal Variations of the Regional Velocity Structure at the Kluchevskoy Volcano Group (Kamchatka, Russia), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-181, https://doi.org/10.5194/egusphere-egu22-181, 2022.

Ambient noise polarizes inside fault zones, yet the spatial and temporal resolution of polarized noise on gas-bearing fluids migrating through stressed volcanic systems is unknown. At Campi Flegrei caldera (Southern Italy), high polarization marks a transfer structure connecting the deforming centre of the caldera to open hydrothermal vents and extensional caldera-bounding faults during periods of low seismic release. Fluids pressurize the Campi Flegrei hydrothermal system, migrate, and increase stress before earthquakes. The loss of polarization (depolarization) of the transfer and extensional structures maps pressurized fluids, detecting fluid migrations after seismic sequences. After recent intense seismicity (December 2019-April 2020), the transfer structure appears sealed while fluids stored in the east caldera have moved further east. Our findings show that depolarized noise has the potential to monitor fluid migrations and earthquakes at stressed volcanoes quasi-instantaneously and with minimum processing.

How to cite: De Siena, L. and Petrosino, S.: Fluid migrations and volcanic earthquakes from depolarized ambient noise, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-738, https://doi.org/10.5194/egusphere-egu22-738, 2022.

How to cite: Mikhael, N., Poli, P., and Garambois, S.: Monitoring long term seismic velocity changes in the Apennines region (ITALY), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2170, https://doi.org/10.5194/egusphere-egu22-2170, 2022.

 Strong ground motion can generate a large dynamic strain in shallow materials, lead to a nonlinear response, and cause permanent damage in near-surface materials. The nonlinear behavior of soils subjected to strong vibrations leads to an increase in wave attenuation and a decrease in shear modulus. These effects lead to a decrease in the resonance frequency of the soil and a decrease in the propagation speed of S-waves. This work investigates, using deconvolution and autocorrelation methods, “in situ” seismic velocity changes and predominant ground-motion frequency evolution during the 2016 Kumamoto earthquake sequence. The Kumamoto sequence contains two major foreshocks (Mw6, Mw6.2) and a mainshock (Mw7.2) that occurred 24 hours after the last foreshock. We present results of the seismic velocity evolution during this sequence for seismological records collected by Kik-Net and K-Net stations between 2002 to 2020. The results indicate that nonlinearity response is profoundly occurring in the damaged material close to the surface. We quantify these velocity reductions occurring during the mainshock and show that the healing process lasted about three months after the mainshock. We finally quantify the relationships between velocity changes, ground-motion predominant frequency variations, and site condition characteristics (Vs30).  

How to cite: D. D. Esfahani, R., Cotton, F., and Bonilla, F.: Temporal Variations of Shallow Material Properties During the Kumamoto Earthquake Sequence, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2984, https://doi.org/10.5194/egusphere-egu22-2984, 2022.

Ground shaking induced by earthquakes often introduces transient changes in subsurface
rock's physical properties. Evidences for these changes come from estimated
seismic velocity changes that show co-seismic velocity drops, which are succeeded by a
phase of recovery (the so-called relaxation process). Because this transient behaviour may
influence hydraulic properties, friction properties in fault zones, material strength or landslide rates,
understanding the duration of the relaxation is important for post-earthquake hazard
mitigation. However, there is poor constraint on the recovery timescale, especially after
small seismic events. In this study, we present seismic interferometry results obtained
from a  seismic array at the Patache field site in Chile. Thanks to high 
averaging capabilities with this dense deployment of 13 stations, we are able to resolve relative seismic velocity
changes (3-6 Hz) at a 10-minutes resolution following a moderate seismic event (PGV ~
5 mm/s). After inferring the 1D shear velocity profile of our field site, we report a velocity
drop of ~0.4 % in the first 10 minutes after ground shaking, that precedes a recovery to
~50% of the initial pre-event value during the 48 hours following the event. We compare
this high resolution velocity change observation with a longer term, multi-annual velocity time-series that we obtained at
the same site and which exhibits the recovery induced by 2 large earthquakes (the 2007 Mw 7.7
Tocopilla and the 2014 Mw 8.2 Iquique). This combination of short and long observations allows us to
discuss the effect of ground shaking levels and earthquake sequences on the observed
relaxation timescales and highlights its key controls to possibly derive meaningful
predictive relationship for transient mechanical changes following earthquakes.

How to cite: Illien, L., Sens-Schönfelder, C., Ke, K.-Y., Turowski, J., and Hovius, N.: Relaxation timescales after small and large earthquakes: similarity and controls from seismic velocity changes estimated in Patache, Chile., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8772, https://doi.org/10.5194/egusphere-egu22-8772, 2022.

Our study presents temporal seismic velocity changes (dv/v) associated with the May 2008 Ölfus earthquakes by computing the cross-correlations of ambient noise. The 2008 Ölfus doublet (M5.8 and M5.9, with a composite magnitude of M6.1) occurred in the South Iceland Seismic Zone, which is a highly active transform zone that accommodates plate motion with major earthquake sequences (e.g., 1896, 1912, 2000). We investigate co-seismic and post-seismic response of the crust in the epicentral area, to the 2008 Ölfus doublet. For our analysis, we used three-component continuous data from three stations of the SIL national seismic network operated by the Icelandic Meteorological Office. Using the MSNoise software package (http://www.msnoise.org), we calculated single station ambient noise cross-correlations and utilized the stretching approach to quantify relative seismic velocity variations. We found the highest co-seismic velocity decrease (<1 percent) in the high-frequency band (1-3 Hz) at a seismic station located 10 km from the rupture zone. The co-seismic dv/v drop is also observed at stations 35 km away from the earthquake epicenter, though the amplitude of the variation is less, at 0.5 percent. We identify three months of post-seismic period in both the high-frequency and low-frequency calculations, indicating the recovery process at different crustal depths after the mainshocks. We compare our dv/v time series to continuous GPS observations, local seismicity, and volumetric stress changes. Our analysis suggests that the velocity changes are mainly controlled by shaking-induced damage. Our findings provide considerable insights into the time-dependent seismic velocity changes caused by the 2008 Ölfus events. This work is supported by the IS-NOISE project (https://is-noise.earth/) and the Icelandic Research Fund, Rannis (https://www.rannis.is/).

How to cite: Cubuk Sabuncu, Y., Jónsdóttir, K., Árnadóttir, Þ., Caudron, C., Lecocq, T., and Mordret, A.: Temporal Seismic Velocity Changes Associated with the Mw 6.1, 2008 Ölfus Earthquake Doublet, South Iceland, Using Ambient Noise, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10273, https://doi.org/10.5194/egusphere-egu22-10273, 2022.

Greece is the most earthquake-prone country in Europe, as it is located at the intersection of the Eurasian and African plates, as well as at the western end of the North Anatolian fault zone.

The long term goal of this study is to monitor the spatio-temporal evolution of the mechanical properties of the crust around the Gulf of Corinth in Greece that is associated with seismic swarms and large magnitude (Mw>5) earthquakes. We found that the seismic velocity changes induced by tectonic processes in the upper crust in Greece are masked by the velocity variations associated with environmental factors such as seasonal changes of temperature and hydrological parameters. The aim of the present study is to quantify the seismic velocity changes in the upper crust that are due to these environmental parameters. To that end, we use 6 years (2015-2020) of continuous vertical noise recording in 142 stations and calculate daily auto-correlations. We use the stretching method to measure seismic wave velocity variations (dv/v) with a sliding window of 2 months in the [1-3]s period band corresponding to the shallow crust.  We find that in several regions, the seismic velocities exhibit strong seasonal variations in particular in karstic areas. We use data from 495 meteorological stations in order to assess if it is possible to model the observed seasonal variations of dv/v from temperature changes and rainfall. Preliminary results indicate that 1- the seasonal changes of temperature are unlikely to explain the seasonal changes of seismic velocities and 2- in several regions, the variations of the groundwater level induced by rainfalls can at least partially explain the observed velocity variations.

To complete this study, we turned to an analysis of GPS traces as an independent means of assessing modeled velocity variation and to analyze hydrologic processes within aquifers.

How to cite: Delouche, E., Stehly, L., and Campillo, M.: Seasonal variations of seismic velocities in Greece measured from seismic noise cross-correlations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12347, https://doi.org/10.5194/egusphere-egu22-12347, 2022.

Historic levels of droughts are plaguing the globe, raising a vital call for sustainable freshwater management. Urgently needed is a refined understanding about the structures and dynamics of underground aquifers. Here we present a novel approach for in-situ monitoring of groundwater fluctuations by making use of existing seismograph arrays in California. By advancing the seismic interferometry techniques, we manage to measure not only the temporal evolution but also the spatial distribution of Relative Changes in Seismic Velocity (Δv/v) in the Coastal Los Angeles Basins during 2000-2020. We find Δv/v to recover the hydraulic head, illustrating the potential of leveraging seismometers to propel the temporal and spatial density of well measurements. Images of Δv/v seasonality agree with surface deformation inferred from InSAR, but also further enable the characterization of aquifers and their hydrology at different depths. Long-term Δv/v suggest that distinct trends (decline or recovery) of groundwater storage occurred in adjacent basins, due to anthropogenic pumping practices compounding the effect of climate change. This pilot application bridges the gap between seismology and hydrology, and shows the promise of using seismometers to monitor, image and evaluate underground hydrologic processes. We anticipate Δv/v to be a unique type of 4D geodata that will bring new insights to studying various time-varying processes in Earth’s shallow subsurface.

How to cite: Mao, S., Lecointre, A., van der Hilst, R. D., and Campillo, M.: Space-Time Monitoring of Groundwater via Seismic Interferometry , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10639, https://doi.org/10.5194/egusphere-egu22-10639, 2022.

Malta, a small island nation in the centre of the Mediterranean, is deemed as the European country facing the highest stress on its water resources. Malta has a semi-arid climate with approximately 550 mm of annual rainfall over an area of ∼315 km² and a very high population density. Consequently, 80% of the water used in the Maltese agricultural sector is directly abstracted from groundwater resources via boreholes or underground galleries. To improve the groundwater monitoring in Malta, which currently depends on a network of in situ borehole readings, we analyse ambient seismic noise data recorded on the Malta Seismic Network (MSN) as part of the project SIGMA (Seismic Imaging of Groundwater for Maltese Aquifers). We investigate temporal changes in seismic velocity as an indication of the variability of water in underground rocks. Water-saturated rocks have an increased pore pressure, which, in turn, leads to the opening of cracks in the rock that reduces the contact area between different grains of rock leading to a decrease in seismic velocity.

We compiled the seismic data from each station of the MSN (Galea et al., 2021, SRL) and the FASTMIT experiment (Bozionelos et al., 2019, Xjenza) consisting of a combination of eight broadband and six short-period, three-component seismic stations for the years 2017-2020. The data was pre-processed by demeaning, tapering and merging into a 1-day long trace, which were then band-pass filtered and decimated or downsampled. Power Spectral Density (PSD) charts for the data show that most microseisms energy has a period range of 1-10s. We therefore test different filtering bands encompassing this frequency range. We perform auto and cross-correlation of noise data from 78 station pairs. We perform stacking for 1, 5 and 10 days for smoother cross-correlation functions. We then compute the time delays using the Moving-Window Cross-Spectral analysis (Clarke et al., 2011, JGI). Finally, the change in velocity (dv/v) is determined from the calculated time delays. The algorithm was run via the software package MSNoise (Lecocq et al., 2014, SRL).

We find that the changes in the dv/v time series (~±0.01%) have seasonal patterns, where a negative dv/v in the winter period and a positive dv/v in summer is observed. We compare the auto and cross-correlations with the time series of groundwater measurements from nearby boreholes (ranging from 0.25-3.3m above mean sea level) to investigate the correlation between them. We also take into consideration the NW-SE geology of the island, distinguished by an impermeable layer between the geological strata (Blue Clay) in the north. We find that long paths traversing across different geological layers show weak correlations. We present the tests performed and the results showing the extended spatial coverage for groundwater monitoring in conjunction with the borehole data for the Maltese Islands.

Project SIGMA is financed by the Energy and Water Agency under the National Strategy for Research and Innovation in Energy and Water (2021-2030).

How to cite: Laudi, L., Agius, M. R., Galea, P., D'Amico, S., Schimmel, M., and Lecocq, T.: Groundwater monitoring for the Maltese Islands from ambient seismic noise correlations , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6275, https://doi.org/10.5194/egusphere-egu22-6275, 2022.

We previously developed a physics-based model relating changes in pore pressure and vertical stress to seismic velocity variations and validated the model in a small area of Groningen gas field. Using the entire Groningen seismic network, near-surface velocity changes are estimated over a three-year period, using passive image interferometry. Using our developed model, we invert these observations of velocity change for pore pressure variations as a function of space and time, and thus we construct a 4D pore pressure model for the shallow subsurface of Groningen. Pressure-head recordings in the southeastern region of Groningen allow us to calibrate our inference tool.

How to cite: Fokker, E., Ruigrok, E., Hawkins, R., and Trampert, J.: 4D physics-based pore pressure monitoring in the shallow subsurface of Groningen, the Netherlands, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5392, https://doi.org/10.5194/egusphere-egu22-5392, 2022.

In September 2021, two jökulhlaups were released into the Skaftá river from western Vatnajökull icecap (Iceland). Such floods have been known since 1955. These jökulhlaups originate from two subglacial lakes under 1–3 km wide and 50–150 m deep depressions in the glacier surface, commonly referred to as ice cauldrons, formed by geothermal melting. The average time interval between jökulhlaups from each cauldron is ~2 a. The jökulhlaups travel ~40 km under a glacier that reaches maximum thickness of ~750 m and emerge in the Skaftá river at the terminus of Skaftárjökull outlet glacier. In addition to increased subglacial water flow and river discharge, these floods are responsible for seismicity and tremor onset, inside the cauldrons, along the subglacial channels, at the outlet where the subglacial channels meet the river, as well as on the river path.
We used seismic interferometry or cross-correlation of seismic noise to analyse data from 2015 to the end of 2021. We computed cross-correlation functions for 27 seismic stations and for frequencies between 0.5 and 8 Hz. To characterize these floods, we calculated the propagation velocities based on the cross-correlation functions and for each frequency band. We located seismic signatures both during the floods period and previous times by using a grid-search method based on the approach of Ballmer et al. 2013, which calculates theoretical differential times and provides probabilities of locations as the summed stack amplitudes of correlograms. These daily location grids allowed us to analyse the spatial evolution of probability of location during these floods as well as compare them with previous “non-flood” periods. Furthermore, based on these location grids, we were able to compute temporal series for isolated locations (pixels) such as ice cauldrons, a hydrological station located on the river path, or any other target, allowing us to analyse the temporal evolution of location probability during the floods as well as compare it with the last six years of data. The resolution of this temporal evolution ranges from monthly to hourly. By using six years of seismic data, we were also able to compare the 2021 floods with floods due to the same ice cauldrons, for example in August 2018 and September 2019.
This study provides an insight on how relevant seismic interferometry can be in the monitoring of such processes, with the purpose of being fully automatic in the near future.

How to cite: Nowé, S., Lecocq, T., Caudron, C., Jónsdóttir, K., Einarsson, B., Vanderhoof, B., and Pattyn, F.: Spatial and temporal evolution of Skaftá cauldrons floods from 2015 to 2021 through the analysis of correlograms, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12747, https://doi.org/10.5194/egusphere-egu22-12747, 2022.

Variations in strain/stress and fluid content can change seismic velocities in the subsurface. Monitoring velocity changes, e.g., using ambient seismic noise, may thus constrain these variations as well as the material elastic properties and their non-linear behaviour. We can test this capability by inspecting velocity changes from known effects, such as tides, temperature or atmospheric pressure affecting the upper crust. Here we present a workflow to use ambient seismic noise to derive the non-linear behaviour of hard rocks during the influence of tides, temperature and atmospheric pressure. We study one year of data from the GERES array in south Germany, which provides data to the Comprehensive Nuclear Test Ban Treaty Organization (CTBTO). The seismological GERES array consists of 25 high-quality stations located in concrete vaults with depths between 3 and 5 meters. The aperture is 4 km. We estimate hourly Green’s function by cross-correlating ambient seismic noise recorded at pairs of stations. A Wiener filter increases the signal-to-noise ratio and stabilizes the hourly calculation of relative seismic velocity change in the 1-4 Hz frequency band. We compare different techniques to measure seismic velocity changes with high precision in time, frequency, and wavelet domain. The results indicate short and long term variations of the seismic velocities. This study aims to compare this non-linear behaviour of hard rocks with other geological settings used in earlier investigations.

How to cite: Kramer, R., Lu, Y., Delorey, A., and Bokelmann, G.: Investigation of non-linear behavior of hard rock using relative seismic velocity changes - a case study at the GERES array in Germany , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8043, https://doi.org/10.5194/egusphere-egu22-8043, 2022.