Ambient Noise Cross-correlation Research Articles

Passive Guided Wave Tomography for Erosion Monitoring in an Air/Sand Test Loop

The detection and quantification of defects in pipes by non-destructive testing techniques plays a crucial role in several industries (petrochemical and nuclear in particular). Once a defect is detected, assessing its severity enables to schedule maintenance appropriately, hence reducing maintenance cost and rupture or leakage risks. Structural Health Monitoring (SHM) is an approach that consists in instrumenting a structure with permanent sensors to monitor its health status throughout its life. Guided elastic waves are particularly suitable for SHM applications on thin structures (such as pipes) thanks to their ability to propagate over long distances and their high sensitivity. An SHM approach called "passive guided waves tomography" has emerged in recent years to detect and quantify corrosion in pipes (or plate-like structures). This technology is based on the combination of guided elastic wave tomography algorithms and a passive method such as the so-called ambient noise cross-correlation. It allows to obtain absolute and precise maps of the thickness of an area surrounded by a distribution of sensors without emitting waves, simply by analyzing the elastic noise that exists naturally in the pipe (due to vibrations, fluid-structure interactions with a moving fluid, etc.). In this paper passive guided waves tomography is tested in representative conditions thanks to an erosion loop that circulates air and sand. By impacting the tube wall, sand grains erode the structure, creating thickness losses that we monitor with passive tomography.

Quick clay monitoring using distributed acoustic sensing: A case study from Rissa, Norway

Quick clay avalanche is one of the most devastating landslide types worldwide. Hence, an early warning system is in demand to mitigate the fatal consequences caused by such events. To address this, distributed acoustic sensing data are collected in an area containing quick clay deposits between July 2021 and February 2022 in Rissa, Norway, while a new road is constructed on the quick clay. Road construction can induce unwanted changes to the mass balance in the clay, and previous landslides have been triggered by such changes. For this purpose, passive and active data are collected to test and compare various analysis methods. Using extracted Rayleigh wave dispersion from active sledgehammer shots, shear-wave velocity depth profiles covering the first 15 m could be estimated and compared using a linearized and a nonlinear surface wave inversion method. Furthermore, ambient noise crosscorrelation is used to obtain the dispersion from the ambient noise and associated shear-wave velocity profiles, providing two possible data collection methods for the early warning system. The obtained dispersion curves and the estimated shear-wave velocity profiles show small time-lapse variation during the acquisition period (up to approximately 23 m/s), where the variation is within one standard deviation. Such a small variation suggests that the construction work and the extra load added to the quick clay do not alter the quick clay’s properties. Nevertheless, the obtained results capture the nonrepeatability effects within the acquisition period and provide reference curves for the study area at undisturbed conditions and valuable information for future comparisons to refer to potential failure scenarios. This is the first step in exploring an early warning system for quick clay landslides using fiber-optic cables. Further work will investigate the possibility of automatizing the system and improving the accuracy of the sensing system.

On the Accuracy of Surface-Wave Dispersion Measurements from Horizontal-Component Ambient Noise Cross Correlations

Abstract At present, both Rayleigh and Love waves can be extracted from cross-correlations of ambient noise in ambient noise tomography (ANT). It has been demonstrated that accurate Rayleigh-wave dispersion curves can be extracted from vertical-component noise when noise sources are evenly distributed in space. However, because the rotation of horizontal components alters the distributions of effective sources in horizontal–horizontal cross correlations between a pair of stations, it is still not completely sure if dispersion curves of Rayleigh and Love waves extracted from horizontal-component noise data are accurate for ANT. In this study, through numerical simulations, we demonstrate that surface-wave phase velocities extracted from the horizontal–horizontal cross-correlation functions (CCFs) systematically deviate from structural phase velocity even when noise sources are evenly distributed in space. The deviations of phase velocities quickly increase with decreasing station separations of CCFs when station separations are shorter than three wavelengths. Further analysis on field data recorded at seismic stations in the contiguous United States confirms the existence of the phase-velocity deviations of Rayleigh and Love waves when they are measured from horizontal–horizontal CCFs. Because the deviations become smaller with increasing station separations and are less than 0.25% at station separations longer than three wavelengths, we suggest that it is best to only select those CCFs with station separations longer than three wavelengths in ANT when measuring phase velocities of surface waves from horizontal-component CCFs, such as Love waves from radial–radial CCFs.

Generating 1D depth profile of shear-wave velocity from ambient noise cross-correlation: application to Jakarta array

In the past decade, cross-correlations of ambient seismic noise have been exploited in various applications to model the shallow-to-deep structure of Earth’s interior through tomographic inversions. The stack of cross-correlations between a 2-station pair represents empirical Green’s function and comprises the information of the subsurface structure between those stations. In practice, noise correlation function (NCF) is analyzed to reconstruct surface wave group or phase velocity dispersion; then, the dispersion data is used to model shear-wave velocity (Vs). This study presents a case for temporary seismic networks deployed in the Jakarta Basin; we applied a two-step routine to obtain a representative 1D Vs profile beneath an array. First, we extracted our array’s average phase velocity dispersion based on the relationship between NCF’s spectra and the Bessel function. Then, we invert for the 1D depth profile of Vs using a transdimensional Bayesian inversion to allow for exploring a number of layers in parameterizations. We successfully generate a 1D Vs profile up to 5 km depth reflecting the regional stratigraphy of the Jakarta Basin. In general, a sedimentary basin fill covers the area reaching a depth of 650 m. We suggest that this simple routine can be undertaken for other ambient noise cross-correlation cases; such a 1D depth profile would be beneficial to be used as a reference model.

Monitoring of Groundwater in a Limestone Island Aquifer Using Ambient Seismic Noise

The limestone islands of Malta face high levels of water stress due to low rainfall over a small land area and a high population density. We investigate an innovative, cost-effective approach to groundwater monitoring in an island environment by computing auto- and cross-correlations of ambient seismic noise recorded on short-period and broadband seismic stations. While borehole readings give accurate site-specific water level data of the groundwater across the islands, this technique provides a more regional approach to quantitative groundwater monitoring. We perform the moving window cross-spectral method to determine temporal changes in seismic velocity (δv/v). Comparison of the δv/v with groundwater levels from boreholes and precipitation shows comparable patterns. We find that the variations of the δv/v from auto-correlations are more pronounced than the cross-correlation, and that short-period seismic stations are also sensitive. The δv/v signal deteriorates at longer interstation distances, presumably because paths traverse complex geology. We conclude that changes in the groundwater level found beneath very small islands, even as small as 3 km2, can be detected seismically. Low-cost, easy-to-deploy seismic stations can thus act as an additional tool for groundwater monitoring, especially in places with limited natural water reservoirs, like rivers and lakes, and infrastructure.

Past Earthquake Simulations Using Ambient Seismic Noise in Vrancea, Romania

Abstract The Vrancea seismic zone (VSZ), located in Romania, at the sharp bend of the southeast Carpathians, is an anomalous intraplate seismic nest releasing the largest strain in continental Europe. The last powerful earthquake in Vrancea occurred in 1977 causing significant damage to the densely populated cities in southeast Romania. The seismic infrastructure was underdeveloped at that time and the earthquake was not well recorded locally. Using ambient seismic noise recorded at modern broadband seismic stations around Vrancea in the year 2020, and the approximate moment tensor solutions of significant earthquakes Mw>6 since 1977, we reconstruct ground-motion waveforms recorded by modern seismometers decades after their occurrence. The virtual earthquake approach uses empirical Green’s functions from ambient noise cross correlations between pairs of seismic stations and adds the signatures of a model earthquake: double couple mechanism, buried source, and a realistic earth model in the epicentral area. Ambient noise data capture the signatures of complex subsurface structures and the 3D path effects, providing a more physically accurate representation of the seismic wavefield than purely synthetic data. Our new results demonstrate the viability of this innovative method and provide a unique opportunity for more accurate seismic hazard analysis in intraplate seismic zones with insufficient instrumental data.

Observation of Higher-Mode Rayleigh Waves from Ambient Noise in the Tarim Basin, China

Abstract Higher mode surface waves, which can provide additional constraints on subsurface structures in addition to fundamental modes in surface-wave tomography, have been observed from ambient noise cross-correlation functions (CCFs) in sedimentary basins in oceans or near coastlines. However, few studies show that higher mode surface waves can be observed and extracted directly from ambient noise CCFs in inland basins. In this study, we report observations of high signal-to-noise ratio fundamental and the first higher mode Rayleigh waves at a period range of 0.2–1.90 s and 0.2–1.35 s, respectively, from ambient noise CCFs in the southeastern margin of the Tarim basin, the biggest inland basin in China. We confirm the credibility of the first higher mode surface waves by showing that the observed first higher mode dispersion curves are matched with predicted ones calculated from S velocity models solely constrained by fundamental-mode dispersion curves. After the verification of the credibility of the first higher mode surface waves, we demonstrate that the inclusion of the first higher mode dispersion curves helps image deeper structures with an increase of average depths from ∼0.73 to ∼1.24 km, which will be beneficial to future explorations of deep oil and gas resources in the Tarim basin.

Comment on ‘Rayleigh-wave H/V ratio measurement from ambient noise cross-correlations and its sensitivity to Vp: a numerical study’ by Malkoti et al

SUMMARY We present corrections to the expressions for surface-wave Green’s tensors shown in a recent paper by Malkoti et al.

Travel time picking of ambient noise cross-correlation using a deep neural network combining convolutional neural networks and Transformer

Travel time picking of ambient noise cross-correlation using a deep neural network combining convolutional neural networks and Transformer

Determining hydraulic diffusivity from ambient noise in subsurface flow rate and temperature data

SUMMARY Determining the properties that control fluid flow and pressure migration through rocks is essential for understanding groundwater, energy reservoirs and fault zones. However, direct measurements of these properties underground generally require expensive and invasive processes such as pumping large volumes of water in or out of the ground. These conventional methods may change the structure that they are trying to measure and do not resolve variations in space without complex, multiple experiments. Here, we capitalize on the existing, natural fluctuations of pore pressure, flow and temperature that are always present underground, likely driven by tides, seismic waves and other noise in the Earth. We develop the theoretical framework to utilize these noises to determine hydrogeologic structure. We begin with prior work demonstrating a connection between cross-correlation and Green's functions for diffusive processes and illustrate how the existing theory could be used specifically for the case of inferring hydraulic diffusivity from closely spaced observations of pore pressure. We extend the current theory to include a capability for inferring Green's functions from closely spaced flow rate measurements, rather than pore pressure data. We then note that closely spaced temperature measurements are much more practical as an observational system, however, diffusive transport is likely not the dominant cause of high-frequency fluctuations of temperature in the Earth. Advective transport is a more plausible controlling factor and thus we need to incorporate advection into the theory and model the corresponding response functions. We therefore develop a semi-analytical method that includes advection and numerically compute the corresponding response function. We use these synthetics to illustrate how cross-correlation of ambient noise in subsurface temperature measurements carries information about hydraulic structure and show that it is possible to constrain hydraulic diffusivity values from cross-correlation of closely spaced continuous temperature measurements. This new method opens up the possibility of passive determination of reservoir properties with high spatial resolution from closely spaced, continuous temperature data, which is a realistic deployment strategy that could be used in a wide variety of settings.

Ambient noise cross-correlations and 3-D shear-wave model in the Wudalianchi volcanic region

Ambient noise cross-correlations and 3-D shear-wave model in the Wudalianchi volcanic region

A look at the blind Kumamoto experiment: combining active and passive seismic observations to avoid Rayleigh-wave mode misidentification

We present our pathway through participation in the blind Kumamoto exercise, particularly the Step 1 of site characterization. The combination of passive and active seismic imaging techniques is used to image the velocity profile beneath the KUMA site. The estimation of the broadband Rayleigh wave dispersion curve is based on cross-correlations of ambient seismic noise and analysis of active seismic shots. We calculate correlations from the entire time series (only vertical components) of each seismic array after classical pre-processing of ambient noise data. Then, a passive seismic section is constructed using all available stations pairs and stacking the cross-correlation traces with similar interstation distances. The obtained passive seismic section is analyzed using a high-resolution Radon transform to obtain the dispersion image of Rayleigh waves traveling through the KUM-LL, KUM-M and KUM-SM arrays. Then, the information is merged and interpolated to obtain the final broadband dispersion curve. In addition, active source seismic data are used with the high-resolution Radon technique to constrain the model at shallow depths (< 30 m). Then, a broadband dispersion image is constructed with significant energy from 0.9 Hz to 45 Hz. The final dispersion curve is inverted using the non-linear neighborhood algorithm. Using just the fundamental mode Rayleigh wave, a first model with normal velocity variation in depth is obtained that corresponds well with the preferred model provided by the organizing committee. The addition of a mHVSR curve in a joint inversion better constrains the deeper part of the model (> 1 km). After comparison of the submitted dispersion curve to the theoretical dispersion curve for the preferred model (Step 4 of the blind test), the authors note that there was a clear misinterpretation in the fundamental mode of their submitted results, especially at frequencies higher than 5 Hz. Using both fundamental (only visible in the passive data set) and first overtones of Rayleigh waves (only visible in the active seismic data set) a refined velocity model could have been inferred, but we decided to keep our first submitted result. This detailed interpretation should be further studied as dispersion images from forward and backward hammer shots are quite different, which may indicate strong variations in the geometry and/or shear-wave velocities of the first meters of the subsurface.Graphical

Defining the Yangtze–Cathaysia suture zone in South China using ambient noise tomography

SUMMARYThe South China Craton formed after collision between the Yangtze and Cathaysia Blocks. The suture zone between these two blocks is the crux of understanding the geological evolution of South China. Due to the relative paucity of high-resolution subsurface data, the location of the suture zone in the southwestern region remains uncertain. To find the suture zone, we created a high-resolution model of the crust and upper mantle structure using 27 months of continuous waveform data acquired from 457 stations in South China. The model uses extracted phase velocity dispersion curves of Rayleigh waves at 4–40 s from ambient noise cross-correlation functions, to perform a direct inversion for an azimuthal anisotropic VSV model. In the crust a prominent belt of strong azimuthal anisotropy exists between the Yangtze and Cathaysia Blocks. The fast polarization axes in this belt correspond to the NE-trending orogen between the two blocks. In the deeper crust of the Cathaysia Block we image multiple areas of diffuse low-velocity anomalies. As defined by the margins of the strongly anisotropic belt, the Yangtze–Cathaysia suture zone is delineated by lines that traverse: Shaoxing–Jiangshan–Pingxiang–Longsheng–Hechi and Shitai–Jiujiang–Yueyang–Dayong–Jishou. Further analysis of the seismic data links deep low velocities with widespread Late Mesozoic magmatism in the Cathaysia Block. The deep low velocities are likely a result of dehydration of the subducting Pacific Plate causing mantle upwelling and underplating.

Crustal velocity images of northwestern Türkiye along the North Anatolian Fault Zone from transdimensional Bayesian ambient seismic noise tomography

SUMMARY Türkiye poses a complex crustal structure and tectonic settings owing to the northward convergence of the Arabian and African plates with respect to the Anatolian and Eurasian plates. A reliable 3-D crustal structure of the unruptured segment of the North Anatolian Fault Zone (NAFZ) in the Sea of Marmara is thus of utmost importance for seismic hazard assessments considering that the megacity Istanbul—with more than 15 million habitants—is close to this seismic gap. This study provides high-resolution shear wave velocity images of northwestern Türkiye, including the NAFZ, revealed from ambient seismic noise tomography. We extract over 20 000 Green’s functions from seismic ambient noise cross-correlations and then construct group velocity perturbation maps from the measured group delays with a transdimensional Bayesian tomographic method. We further perform an S-wave velocity inversion to image depth-varying velocity structures. Our high-resolution data allowed us to image S-wave velocities down to 15 km depth and reveal weak crustal zones along the NAFZ, as indicated by low shear wave velocities. We find a low-velocity zone along the Main Marmara Fault, linked with aseismic slip and a deep creep mode. Furthermore, we identify a high-velocity anomaly associated with the unruptured section that defines the boundaries of the locked zone in the crust, which can potentially trigger a destructive earthquake in the future.

The 2013–2020 seismic activity at Sabancaya Volcano (Peru): Long lasting unrest and eruption

Sabancaya volcano is the youngest and second most active volcano in Peru. It is part of the Ampato-Sabancaya volcanic complex which sits to the south of the ancient Hualca Hualca volcano and several frequently active faults, thus resulting in complex volcano-tectonic interactions. After 15 years of repose, in 2013, a series of 4 earthquakes with magnitude >4.5 occurred within 24 h, marking the beginning of a new episode of unrest. Several additional swarms of earthquakes occurred in the following years until magmatic eruptive activity started on 6 November 2016. This activity is ongoing as of this writing, with an average of 50 explosions per day. In this study, we present results of multiparametric monitoring of Sabancaya's activity observed during 2013–2020. Seismic data are used to create a one-dimensional seismic velocity model, to catalog, locate, and characterize earthquakes, to detect repeating earthquake families, and to monitor seismic velocity variations by ambient noise cross-correlation. These analyses are complemented by visual and remote sensing observations and ground deformation measurements. All monitored parameters showed significant changes on 6 November 2016, the day of eruption onset, thus dividing the eruptive activity into pre-eruptive and eruptive stages.The unrest is characterized by high levels of seismic activity with hundreds of events detected per day. Volcano-tectonic (VT) earthquakes were dominant during the pre-eruptive period while long-period (LP) events and explosions have been most numerous since the eruption onset. Earthquake locations highlight long-lasting seismogenic zones along multiple previously active regional faults, as well as along newly identified faults. This VT seismicity is mainly distributed in a sector from the northwest to the east of the volcanic complex at distances of up to 30 km from the crater. We focus our analysis on two eruptive episodes: the eruption onset and subsequent crater migration from south to north, and the increase of lava dome extrusion rate in 2019. Both episodes are accompanied by seismic velocity decreases of up to 0.2% and are preceded by a few weeks by bursts of distal VT activity, including numerous repeating earthquakes. These repeated events were located on several remote tectonic faults (5–25 km from the vent). We suggest that these phenomena could be due to the injection of a batch of magma in the deep reservoir and/or conduit, which would generate 1) a pressure wave propagating in the hydrothermal system, triggering the bursts of seismic activity and 2) slow rising of magma by melting old material filling the conduit that eventually produced the eruptive and dome growth acceleration events.

Evaluating and correcting short-term clock drift in data from temporary seismic deployments

Temporary seismic network deployments often suffer from incorrect timing records and thus pose a challenge to fully utilize the valuable data. To inspect and fix such time problems, the ambient noise cross-correlation function (NCCF) has been widely adopted by using daily waveforms. However, it is still challenging to detect the short-term clock drift and overcome the influence of local noise on NCCF. To address these challenges, we conduct a study on two temporary datasets, including an ocean-bottom-seismometer (OBS) dataset from the southern Mariana subduction zone and a dataset from a temporary dense network from the Weiyuan shale gas field, Sichuan, China. We first inspect the teleseismic and local event waveforms to evaluate the overall clock drift and data quality for both datasets. For the OBS dataset, NCCF using different time segments (3, 6, and 12-h) beside daily waveforms data is computed to select the data length with optimal detection capability. Eventually, the 6-h segment is the preferred choice with high detection efficiency and low noise level. For the land dataset, higher drift detection is achieved by NCCF using the daily long waveforms. Meanwhile, we find that NCCF symmetry on the dense array is highly influenced by localized intense noise for large interstation distances (>1 ​km) but is well preserved for short interstation distances. The results have shown that the use of different segments of daily waveform data in the OBS dataset, and the careful selection of interstation distances in the land dataset substantially improved the NCCF results. All the clock drifts in both datasets are successfully corrected and verified with waveforms and NCCF. The newly developed strategies using short-segment NCCF help to overcome the existing issues to correct the clock drift of seismic data.

Detection of clock errors in seismic records and estimation of time shifts for a seismic network

In the records of autonomous seismological observations occurrence of quartz watch clock drift often leads to incorrect time records. This paper presents a method for detecting such errors in a seismic station network based on the analysis of ambient seismic noise cross-correlation functions using Monte-Carlo Markov chain (MCMC) approach without using a reference signal. The proposed method was tested on the seismic data of a temporary seismic network installed on Paramushir Island in 2021-2022 for which time shifts were successfully estimated and corrections to the cross-correlation functions were made.

Temporal changes of seismic velocities below Bezymianny volcano prior to its explosive eruption on 20.12.2017

The strong explosive eruption of Bezymianny volcano (Klychevskoy volcano group) occurred on 21 December 2017, the preparation phases of which were recorded by a local seismic network. Applying methods of estimation of seismic velocity changes based on cross-correlation of ambient noise, we obtained different velocity variations at several passbands before the eruption. In order to explain the observations obtained, we performed qualitative mechanical estimates of stress changes resulting from the migration of the pressure source. The obtained and estimated velocity changes have the same patterns. We propose that observed and evaluated velocity changes are caused by fluids migration from mid-crustal magma reservoir of the Bezymianny volcano to the shallow magma chamber that then triggered the eruption.

Enhancing cross correlations of ocean ambient noise in the time domain based on random matrix theory.

Cross correlations of diffuse noise can be utilized to recover the time domain Green's function (TDGF) between two points. This principle allows for a variety of practical applications, such as seismic tomography, ocean thermometry, passive localization, etc. However, in the real ocean environment, loud interference noise sources usually bias the travel time estimates of the TDGF or result in poor recovery quality. To deal with this issue, a diffuse noise reconstruction approach is proposed to eliminate the influence of the strong interference noise by utilizing the time domain statistical property of ocean ambient noise recorded on single hydrophones with the help of random matrix theory. Simulation and experimental data analysis indicate that this algorithm can effectively extract the diffuse noise component from the ocean ambient noise field and retrieve the TDGF with a higher signal-to-noise ratio when coherent accumulation of cross correlations of the reconstructed diffuse noise is performed.

The Urban Underground Space beneath the Karst Basin of Guilin, China, Revealed by Ambient Seismic Noise Tomography

Abstract Detection of hidden faults and sedimentary layers in the urban subsoil is significant for the utilization of the underground space, earthquake hazard mitigation, and so forth. Guilin, located in southwest China, is well known for the development of the most typical karst landform in the world and has become an international tourist city that needs scientific planning and knowledge of the urban underground space. After collecting waveform data recorded continuously over a period of about 1.5 months by a dense array of 114 short-period seismic stations installed in and around Guilin, we adopt ambient seismic noise cross-correlation method to extract Rayleigh-wave phase velocity dispersion curves within the period range from 0.5 to 5 s and to obtain a high-resolution S-wave velocity (VS) model of the shallow crust above 9 km using surface-wave tomography. The vertical VS gradient image indicates that the sediment thickness of the Guilin Karst basin is about 1–3 km. Sedimentary layers are relatively thick between Yanshan Mountain and Haiyang Mountain, and along the Yi river valley, where karst groundwater may be abundant and used as an important option for urban water supply. Both the absolute VS velocity image and the relative VS anomaly image clearly reveal the occurrence, location, and deep extension characteristics of major faults. Longsheng–Yongfu, Nanning–Guilin, Yaoshan–Yanshan, Baishi, and Guanyang–Hengyang may be regional deep faults cutting through the upper crust at least. The evolution of the basin is mainly controlled by the steep dipping Longsheng–Yongfu and Baishi faults, and partially controlled by the gently dipping Nanning–Guilin fault in the interior of the basin. The Nanning–Guilin fault is an active and partially buried fault obliquely crossing Guilin city. Urban seismic imaging, such as the new VS tomography presented here, can play an important role in understanding tectonic and tectonic-subsidence earthquake hazards associated with these buried faults.