Azimuthal Anisotropy at Valhall: the Helmholtz Equation Approach

International audienceWe used 6 hours of continuous vertical records from 2320 sensors of the Valhall Life of Fields Seismic network to compute 2 690 040 cross-correlation functions between the full set of sensor pair combinations. We applied the 'Helmholtz tomography' approach combined with the ambient noise correlation method to track the wave front across the network with every station considered as a virtual source. The gradient of the interpolated phase travel time gives us an estimate of the local phase speed and of the direction of wave propagation. By combining the individual measurements for every station, we estimated the distribution of Scholte's wave phase speeds with respect to azimuth. The observed cosine pattern indicates the presence of azimuthal anisotropy. The elliptic shape of the fast anisotropy direction is consistent with results of previous shear wave splitting studies and reflects the strong seafloor subsidence due to the hydrocarbon reservoir depletion at depth and is in good agreement with geomechanical modeling

Temporal Seismic Velocity Changes During the 2020 Rapid Inflation at Mt. Þorbjörn-Svartsengi, Iceland, Using Seismic Ambient Noise

Publisher Copyright: © 2021. The Authors.Repeated periods of inflation-deflation in the vicinity of Mt. Þorbjörn-Svartsengi, SW-Iceland, were detected in January–July, 2020. We used seismic ambient noise and interferometry to characterize temporal variations of seismic velocities (dv/v, %). This is the first time in Iceland that dv/v variations are monitored in near real-time during volcanic unrest. The seismic station closest to the inflation source center (∼1 km) showed the largest velocity drop (∼1%). Different frequency range measurements, from 0.1 to 2 Hz, show dv/v variations, which we interpret in terms of varying depth sensitivity. The dv/v correlates with deformation measurements (GPS, InSAR), over the unrest period, indicating sensitivity to similar crustal processes. We interpret the velocity drop to be caused by crack opening triggered by intrusive magmatic activity. We conclude that single-station cross-component analyses provide the most robust solutions for early detection of magmatic activity.Peer reviewe

Rapid response to the M_w 4.9 earthquake of November 11, 2019 in Le Teil, Lower Rhône Valley, France

On November 11, 2019, a Mw 4.9 earthquake hit the region close to Montelimar (lower Rhône Valley, France), on the eastern margin of the Massif Central close to the external part of the Alps. Occuring in a moderate seismicity area, this earthquake is remarkable for its very shallow focal depth (between 1 and 3 km), its magnitude, and the moderate to large damages it produced in several villages. InSAR interferograms indicated a shallow rupture about 4 km long reaching the surface and the reactivation of the ancient NE-SW La Rouviere normal fault in reverse faulting in agreement with the present-day E-W compressional tectonics. The peculiarity of this earthquake together with a poor coverage of the epicentral region by permanent seismological and geodetic stations triggered the mobilisation of the French post-seismic unit and the broad French scientific community from various institutions, with the deployment of geophysical instruments (seismological and geodesic stations), geological field surveys, and field evaluation of the intensity of the earthquake. Within 7 days after the mainshock, 47 seismological stations were deployed in the epicentral area to improve the Le Teil aftershocks locations relative to the French permanent seismological network (RESIF), monitor the temporal and spatial evolution of microearthquakes close to the fault plane and temporal evolution of the seismic response of 3 damaged historical buildings, and to study suspected site effects and their influence in the distribution of seismic damage. This seismological dataset, completed by data owned by different institutions, was integrated in a homogeneous archive and distributed through FDSN web services by the RESIF data center. This dataset, together with observations of surface rupture evidences, geologic, geodetic and satellite data, will help to unravel the causes and rupture mechanism of this earthquake, and contribute to account in seismic hazard assessment for earthquakes along the major regional Cévenne fault system in a context of present-day compressional tectonics

Rayleigh-Wave Multicomponent Cross-Correlation-Based Source Strength Distribution Inversion. Part 1: Theory and Numerical Examples

Cross-correlation-based seismic interferometry is commonly used to retrieve surface-wave Green’s functions from ambient seismic noise recordings. This approach requires that seismic sources are isotropically distributed in all directions around two receivers. However, this assumption is rarely valid in practice. Thus full-waveform inversion theory has recently been applied to seismic noise cross-correlation functions, functions that include both source and structure information. Source information (e.g. location or strength) is essential for accurate structure information estimation. In this paper, we explain physically two types of source sensitivity kernels: one derived from traveltime misfits and the other derived from waveform misfits. We use these kernels for source inversion and demonstrate the benefits of using multicomponent cross-correlations in this source estimation process

Shallow three-dimensional structure of the San Jacinto fault zone revealed from ambient noise imaging with a dense seismic array

International audienceWe use 1 month of continuous seismic waveforms from a very dense seismic network to image with unprecedented resolution the shallow damage structure of the San Jacinto fault zone across the Clark fault strand. After calculating noise correlations, high apparent velocity arrivals coming from below the array are removed using a frequency-wavenumber filter. This is followed by a double-beamforming analysis on multiple pairs of subarrays to extract phase and group velocity information across the study area. The phase and group velocity dispersion curves are regionalized into phase and group velocity maps at different frequencies, and these maps are inverted using a neighbourhood algorithm to build a 3-D shear wave velocity model around the Clark fault down to ∼500 m depth. The model reveals strong lateral variations across the fault strike with pronounced low-velocity zones corresponding to a local sedimentary basin and a fault zone trapping structure. The results complement previous earthquake- and seismic noise-based imaging of the fault zone at greater depth and clarify properties of structural features near the surface

Crustal Structure Across the West Antarctic Rift System from Multicomponent Ambient Noise Surface Wave Tomography

Approximately 2 yr (2010–2011) of continuous seismic records from a subset of the Antarctic component of the Polar Earth Observing Network (POLENET‐ANET) seismic network deployed in West Antarctica are used to compute the nine components of the correlation tensor between each pair of stations in the network. Rayleigh wave velocity information from the vertical and radial components was extracted in the form of group and phase velocity dispersion curves, whereas the transverse component provided complimentary Love wave velocity information. The multicomponent Rayleigh wave measurements (ZZ, RR, ZR, and RZ) were averaged and used to infer the measurement uncertainties. The Rayleigh and Love wave group and phase velocities were then regionalized in space using a 2D deterministic tomography. A transect that spans the West Antarctic rift system was extracted from the tomography at individual periods between 7 and 60 s for the four types of surface wave velocities (i.e., Rayleigh and Love phase and group velocities). A transdimensional Bayesian joint inversion algorithm was used to invert these four datasets for a 1D model of isotropic shear‐wave velocity versus depth at each point along the transect. In this way, surface wave dispersion curves from multicomponent noise correlations were used to build a 2D isotropic shear‐wave velocity model down to ∼55 km depth. In this model, the top of the large low‐velocity zone beneath Marie Byrd Land was imaged (up to a 5% decrease in velocity at ∼50 km depth), which provides further evidence for a mantle hot spot beneath the crust that supports the high topography in this region. We also observed a large velocity contrast in the lower crust beneath Marie Byrd Land at a depth where previous long‐period seismicity has been observed. This strong contrast occurs more shallow than in previous crustal models, which compared to our model identify a deeper Moho (∼5–10 km deeper) beneath Marie Byrd Land. This new model has implications for interpreting earthquake locations in this region and perhaps necessitates that we revisit past hypocenter estimation studies using updated velocity models for the region

Helmholtz Tomography of ambient noise surface wave data to estimate Scholte wave phase velocity at Valhall Life of the Field

International audienceWe applied the Helmholtz tomography technique to 6.5 hours of continuous seismic noise record data set of the Valhall Life of Field network. This network, that has 2320 receivers, allows us to perform a multifrequency, high-resolution, ambient-noise Scholte wave phase velocity tomography at Valhall. First, we computed crosscorrelations between all possible pairs of receivers to convert every station into a virtual source recorded by all other receivers. Our next step was to measure phase traveltimes and spectral amplitudes at different periods from crosscorrelations between stations separated by distances between two and six wavelengths. This is done in a straightforward fashion in the Fourier domain. Then, we interpolated these measurements onto a regular grid and computed local gradients of traveltimes and local Laplacians of the amplitude to infer local phase velocities using a frequency dependent Eikonal equation. This procedure was repeated for all 2320 virtual sources and final phase velocities were estimated as statistical average from all these measurements at each grid points. The resulting phase velocities for periods between 0.65 and 1.6 s demonstrate a significant dispersion with an increase of the phase velocities at longer periods. Their lateral distribution is found in very good agreement with previous ambient noise tomography done at Valhall as well as with a full waveform inversion P-wave model computed from an active seismic data set. We put effort into assessing the spatial resolution of our tomography with checkerboard tests, and we discuss the influence of the interpolation methods on the quality of our final models

Assessing similarity in continuous seismic cross-correlation functions using hierarchical clustering: application to Ruapehu and Piton de la Fournaise volcanoes

SUMMARY Passive seismic interferometry has become a popular technique towards monitoring. The method depends on the relative stability of background seismic sources in order to make repeatable measurements of subsurface properties. Such stability is typically assessed by examining the similarity of cross-correlation functions through time. Thus, techniques that can better assess the temporal similarity of cross-correlation functions may aid in discriminating between real subsurface processes and artificial changes related variable seismic sources. In this study, we apply agglomerative hierarchical clustering to cross-correlation functions computed using seismic networks at two volcanoes. This allows us to form groups of data that share similar characteristics and also, unlike common similarity measures, does not require a defined reference period. At Piton de la Fournaise (La Réunion island), we resolve distinct clusters that relate both to changes in the seismic source (volcanic tremor onset) and changes in the medium following volcanic eruptions. At Mt Ruapehu (New Zealand), we observe a consistency to cross-correlation functions computed in the frequency band of volcanic tremor, suggesting tremor could be useful as a repeatable seismic source. Our results demonstrate the potential of hierarchical clustering as a similarity measure for cross-correlation functions, suggesting it could be a useful step towards recognizing structure in seismic interferometry data sets. This can benefit both decisions in processing and interpretations of observed subsurface changes.SCOPUS: ar.jinfo:eu-repo/semantics/publishe