Ambient Seismic Noise Research Articles

3D shear wave velocity imaging of the subsurface structure of granite rocks in the arid climate of Pan de Azúcar, Chile, revealed by Bayesian inversion of HVSR curves

Abstract. Seismic methods are emerging as efficient tools for imaging the subsurface to investigate the weathering zone. The structure of the weathering zone can be identified by differing shear wave velocities as various weathering processes will alter the properties of rocks. Currently, 3D subsurface modelling of the weathering zone is gaining increasing importance as results allow the identification of the weathering imprint in the subsurface not only from top to bottom but also in three dimensions. We investigated the 3D weathering structure of monzogranite bedrock near the Pan de Azúcar National Park (Atacama Desert, northern Chile), where the weathering is weak due to the arid climate conditions. We set up an array measurement that records seismic ambient noise, which we used to extract the horizontal-to-vertical spectral ratio (HVSR) curves. The curves were then used to invert for 1D shear wave velocity (Vs) models, which we then used to compile a pseudo-3D model of the subsurface structure in our study area. To invert the 1D Vs model, we applied a transdimensional hierarchical Bayesian inversion scheme, allowing us to invert the HVSR curve with minimal prior information. The resulting 3D model allowed us to image the granite gradient from the surface down to ca. 50 m depth and confirmed the presence of dikes of mafic composition intruding the granite. We identified three main zones of fractured granite, altered granite, and the granite bedrock in addition to the mafic dikes with relatively higher Vs. The fractured granite layer was identified with Vs of 1.4 km s−1 at 30–40 m depth, while the granite bedrock was delineated with Vs of 2.5 km s−1 and a depth range between 10 and 50 m depth. We compared the resulting subsurface structure to other sites in the Chilean coastal cordillera located in various climatic conditions and found that the weathering depth and structure at a given location depend on a complex interaction between surface processes such as precipitation rate, tectonic uplift and fracturing, and erosion. Moreover, these local geological features such as the intrusion of mafic dikes can create significant spatial variations to the weathering structure and therefore emphasize the importance of 3D imaging of the weathering structure. The imaged structure of the subsurface in Pan de Azúcar provides the unique opportunity to image the heterogeneities of a rock preconditioned for weathering but one that has never experienced extensive weathering given the absence of precipitation.

Characterization and application of submarine seismic ambient noise in the Bohai Sea and Yellow Sea

Submarine seismic ambient noise imaging combines current marine and on-land seismic detection technologies. Based on data from several broadband shallow-sea type ocean bottom seismometers (SOBSs) deployed in the Bohai Sea and north Yellow Sea, this paper analyzes the submarine seismic ambient noise characteristics. It explores the theory, technology, method and application of the submarine seismic ambient noise imaging using the single-point horizontal and vertical spectral ratio method (HVSR). The observations yield the following results: 1) Submarine seismic ambient noise has consistent and constant energy, making it an appropriate passive seismic source for submarine high-frequency surface wave investigation. 2) Using the HVSR approach, a single three-component OBS could differentiate between the basement and sediments. Array seismic observation could be utilized to extract the frequency dispersion curve and invert it to obtain the velocity structure for more accurate stratification. 3) The SOBS we use is suitable for submarine surface wave exploration. 4) Tomography results with greater resolution and deeper penetration could be obtained by combining active and passive sources in a simultaneous inversion of the HVSR and frequency dispersion curve. Seamless land-to-ocean seismic research can be accomplished with submarine seismic ambient noise imaging technologies.

High-resolution spatial elastic wave velocity variation detected using multiple-linear-array microtremor measurements

We propose a method for capturing the near-surface elastic wave velocity variation using microtremors. The proposed method does not directly estimate the velocity of the medium; instead, it measures the spatial velocity change. We apply the stretching method, which is often used to detect the time variation of shear wave velocity based on the monitoring of seismic ambient noise, to microtremor recordings. Because spatially dense ambient noise records are unavailable, we performed microtremor measurements using multiple linear arrays with multiple sensors along the survey line to collect as many recordings as possible. The synchronised microtremor recordings of each array were used to compute the horizontal-to-vertical spectral ratio (H/V), cross-correlation (CC), autocorrelation (AC), and single-station cross-correlation (SC). The H/V ratio and the waveforms of these correlation functions showed significant spatial variation. The velocity variation was measured quantitatively using the stretching method, which correlates a compressed and stretched reference function with each function on the line. The velocity variation of the vertical and radial components of CC compares well with the variation of the H/V peak, indicating that the radial components of CC retrieved the Rayleigh-wave Green’s function. The waveforms of AC and SC also showed spatial variation but the measured value of velocity change was smaller than that for CC. Further investigation is awaited to conclude if this is due to low-quality data or inappropriate measurement conditions. The reliability of the velocity change was confirmed by comparing the results to dispersion curves obtained using the conventional array method.

Ambient Seismic Noise Tomography Within the Floridan Aquifer System, Santa Fe River‐Sink Rise, Florida, US

AbstractThis study utilized ambient seismic noise tomography to investigate correlations of hydrogeological systems with heterogeneous porosity with the internal velocity structure of karst aquifers using the Floridan Aquifer System (FAS) as an example. We conducted a seismic signal analysis with 30 days of vertical component seismic data acquired within the Santa Fe River Sink‐Rise system (Sink‐Rise System), using power spectral density estimates and frequency‐wavenumber analysis to identify any noise source biases. Empirical Green's functions were derived through phase cross‐correlations and phase‐weighted stacking. The functions allowed extraction of group velocity dispersion measurements, which were inverted to generate 2D tomographic images at various periods. Tomographic images show multiple layers with varying group velocities that aligned with known hydrogeological features of the FAS, including its base, low‐porosity and low‐permeability dolostone semiconfining units characterized by elevated velocities, and zones of elevated porosity from karstification with reduced seismic velocities. Our results show how ambient seismic noise can be used to evaluate aquifer physical properties, identify unknown features, and identify the location and continuity of aquifer units.

Multimodal surface wave inversion with automatic differentiation

SUMMARY Investigating subsurface shear wave velocity (vs) structures using surface wave dispersion data involves minimizing a misfit function that is commonly solved through gradient-based optimization. Sensitivity kernels for model updates are commonly estimated using numerical differentiation, variational methods or implicit functions which however, may involve numerical instability and computational challenges when dealing with complex velocity models and large data sets. In this study, we propose a novel surface wave inversion framework in which error-free gradients are calculated by automatic differentiation (AD) and forward modelling is implemented by convenient computational graphs in the state-of-the-art deep learning framework. The AD-based inversion approach is first validated using two synthetic data sets. Then, the subsurface structures at three distinct locations, namely the Great Plains and the Long Beach in the US and Tong Zhou in China, are also derived using this method with seismic ambient noise data, which show nice consistency with those obtained using traditional methods. With the significantly improved computational efficiency, a great number of initial models can be inverted simultaneously to mitigate the impact of local minima and to estimate the uncertainty in the invert models. We have developed a new surface wave inversion package named ADsurf based on automatic differentiation and computational graphs in the deep learning framework, and its computational efficiency is also compared with the traditional finite-difference-based gradient estimation approach. While a great number of intriguing studies on the geophysical inverse problems have been conducted recently using deep learning for end-to-end mapping, the use of AD provided in the in the deep learning frameworks to assist and expedite the gradient computations are still underexploited in geophysics. Thus, it is expected that various geophysical inverse problems in many different areas beyond the surface wave inversion can also be tackled with this new paradigm in the future.

The EENSANE (Eastern European Seismic Ambient Noise) project: providing a new free database of ambient noise cross-correlations and crustal seismic models in the Carpathian-Pannonian Region and beyond

The EENSANE (Eastern European Seismic Ambient Noise) project: providing a new free database of ambient noise cross-correlations and crustal seismic models in the Carpathian-Pannonian Region and beyond

Seismic structure of the 2015 Mw7.8 Gorkha earthquake revealed by ambient seismic noise and teleseismic surface wave tomography

The destructive 2015 Mw7.8 Gorkha earthquake occurred in the Main Himalayan Thrust due to the collision of the Indian and Asian plates, which provides a unique opportunity to understand the deep dynamic processes and seismogenic mechanisms of strong earthquakes. We construct a regional-scale shear-wave velocity model of the crust and uppermost mantle using ambient seismic noise and teleseismic surface wave at periods of 5–100 s around the Gorkha earthquake region. The new shear-wave velocity model exhibits prominently lateral heterogeneities in the Gorkha earthquake areas. We observe a high-velocity (high-V) zone around the Gorkha main shock in the Main Himalayan Thrust, indicating the existence of a high-strength asperity that sustains the stress accumulating. The aftershocks are primarily located in the low-velocity (low-V) anomalies and enclosed by two high-V anomalies, which appear to act as structural barriers that influence the spread of the aftershocks. Prominent low-Vanomalies from the lower crust to the mantle lithosphere are observed along the north–south trending rifts, suggesting the hot materials upwelling due to the tearing of the northward subducting Indian lithosphere. These observations may indicate that seismic velocity heterogeneity could play an essential role in earthquake initiation and the rupture process.

N-S variations of crustal structure beneath the central Tarim Basin from joint inversion of receiver functions, ambient seismic noise surface wave dispersion, and magnetotelluric data

To understand the complex crustal structure beneath the central Tarim Basin, we perform joint inversions of P-wave receiver functions, ambient seismic noise Rayleigh wave dispersion, and magnetotelluric data along a nearly N-S oriented linear array. In this contribution, we present a multistep flowchart to enhance the efficiency and reliability of the joint inversion. Synthetic examples indicate that this method is effective and appropriate for realistic conditions. By using these three complementary datasets, we can construct accurate 1-D models, particularly in the presence of thick overlying low-velocity layers. We apply this approach to data recorded at 45 stations within the Tarim Basin and generate quasi-2-D images that reveal distinct lateral variations along the N-S profile. In the near-surface region, we observe that the conductive and low-velocity sedimentary layer is thinner beneath uplift units and thicker beneath structural depressions, which correlates well with surface geology and previous studies. Additionally, we interpret several major faults, concealed crustal detachment layers, and discuss the geological implications. A conspicuous feature of the integrated images is the identification of a localized and deep-rooted doming structure beneath the Bachu uplift, characterized by high-velocity and high-resistivity anomalies. This structure also exhibits elevated density, intense magnetism and the thinnest overlying sedimentary layer. Consequently, we infer that these anomalies are probably linked to a hybrid basement consisting of plume-related intrusions and mafic dyke swarms.

Using time-lapse seismic velocity changes to monitor the Domo de San Pedro Geothermal field, Mexico

The Domo de San Pedro Geothermal field, located in the westernmost part of the trans-Mexican volcanic belt, is part of a silicic volcanic complex. Geothermal energy is produced since 2015 from 9 wells as deep as 3 km. We monitor geothermal operations using a continuous seismic dataset from a temporary network of 20 broadband stations from March 2021 to January 2022. The well logs describing the geothermal operations allow us to investigate the seismic response of the geothermal field to fluid extraction and re-injection across the geothermal wells. We produced a catalog of 217 local earthquakes and derive an optimized 1D velocity model for the geothermal field between 1.2 m above the sea level (masl) and 12 km depth. Apparent velocity changes (dv/v) are measured using seismic ambient noise interferometry from the coda of noise cross-correlations. Next, we identify and locate subsurface velocity anomalies, combining the methods of station collapse sensitivity and ambient noise imaging applied to the continuous seismic noise records. We distinguish three periods of seismic activity where prominent changes in velocity coincide with the re-injection of fluids and significant variation in the production rate of the geothermal wells. We determine the distribution of these velocity transients inside the geothermal field and propose that they are associated with variations in reservoir fluid content and effective stress changes beneath the volcanic system and are responsible for induced microseismicity. Our study shows that implementing dv/v quantification as an additional tool for geothermal seismic monitoring can lead to an improved understanding of the behavior of the geothermal system over time and ultimately de-risk geothermal operations.

The influence of an anticline structure on ambient noise spectral anomalies at an underground gas storage

SUMMARY The purpose of this study is to investigate the seismic ambient noise spectral anomalies that occur near gas reservoirs. These anomalies involve a significant spectral amplification of the vertical component for frequencies generally between 1.5 and 4 Hz and have been reported at various hydrocarbon sites worldwide. There are differing views on the mechanisms responsible for these anomalies. The guideline for this study is that many hydrocarbon reservoirs share a common geological feature: an anticline structure. It appears to cause site effects that influence the amplitude of the ambient noise wavefield. This research examines a dense real data set of ambient noise recorded at the Chémery underground gas storage site in France. The analysis identifies stable spectral anomalies between 1.2 and 2.4 Hz that are correlated to the position of the anticline structure, which also corresponds to the position of the gas bubble. We use a beamforming technique to study the composition and the origin of the ambient noise, and show that the variations of the spectral anomalies over time are correlated to changes in the source wavefield. Finally, we perform numerical simulations of Rayleigh wave propagation within a realistic 3-D velocity model of the Chémery site, while using source distributions directly extracted from real data analysis. The comparison of the simulated anomalies with real data yields a satisfactory qualitative fit. We conclude that the fundamental-mode Rayleigh wave site effect on the anticline is the main mechanism of the spectral anomaly.

Estimation of Seismic Attenuation from Ambient Noise Coda Waves: Application to the Hellenic Subduction Zone

ABSTRACT The decay of surface-wave coda in ambient noise cross correlations can facilitate the estimation of seismic attenuation. The coda quality factor (Qc) can be measured in longer period bands using ambient noise cross correlations, which is the main advantage of using them over earthquakes. The classic model of Aki and Chouet (1975) has been applied previously to estimate coda Q in the Alps using ambient noise cross correlations. The Alps represents an ideal environment for ambient noise study, because it has very high and near-uniform station density, and the region is away from oceanic noise sources. However, many regions around the world do not have uniform station density and may be seismically more active than the Alps. One such region is the Hellenic subduction zone (HSZ), because it has a high rate of seismicity, sparser station coverage, and is surrounded by seas from outside and within. In this study, we estimate ambient seismic noise Qc in 2.5–5, 5–10, and 10–20 s period bands for the HSZ, which did not exist previously. Then, we mitigate the effects of lapse time and window length, distance, azimuth, as well as the number of stacked days on the Qc. Mapping of Qc measurements in such a geographically heterogeneous setting poses additional challenges, which we solve using a novel approach that adaptively selects paths based on their lengths and azimuthal distribution. The major tectonic zones are identified in the resulting Qc maps in the form of low Qc such as the North Anatolian fault, the Kefalonia transform zone, the Gulf of Corinth, the volcanic centers, and so on. The results also show a good correlation with large topographical features such as the Hellenides and the Thessalian plains, which have also been noticed from Qc analysis in other parts of the world.

Real-Time Ambient Seismic Noise Tomography of the Hillside Iron Oxide–Copper–Gold Deposit

We conduct an exploration-scale ambient noise tomography (ANT) survey over the Hillside Iron Oxide–Copper–Gold (IOCG) deposit in South Australia, leveraging Fleet’s direct-to-satellite technology for real-time data analysis. The acquisition array consisted of 100 sensors spaced 260 m apart which recorded continuous vertical-component seismic ambient noise for 14 days. High quality Rayleigh wave signals, with a mean signal-to-noise ratio (SNR) of 40, were recovered in the frequency band 1–4 Hz after processing the recorded data between 0.1–9 Hz. Our modelling results capture aspects of the deposit’s known geology, including depth of cover, structures linked to mineralisation, and the mineralised host rock, down to approximately 1 km depth. We compare our velocity model with existing magnetic, gravity, induced polarisation and drilling data, showing strong correlation with each. We identify several new features of the local geology, including the behaviour of key structures down to 1 km, and highlight the significance of a Cambrian-age dolomite that cuts across the main structural corridor that hosts the Hillside deposit. An analysis of model convergence rates with respect to Rayleigh wave SNRs shows that real-time data analysis can reduce recording duration at the site by 65% compared to traditional deployment durations, from ∼14 days to ∼5 days. Finally, we conclude by commenting on the efficacy of the ANT technique for the exploration of IOCG systems more broadly.

The Magmatic Patterns Formed by the Interaction of the Hainan Mantle Plume and Lei–Qiong Crust Revealed through Seismic Ambient Noise Imaging

Magmatism on continental lithospheres induced by mantle plumes is more complex compared to oceanic intraplate volcanism owing to the heterogeneous nature of continental crustal and lithospheric structures. Substantial evidence points to the deep-oriented Hainan mantle plume beneath the Lei–Qiong region, the southernmost of the South China block. In this study, we present a detailed shear wave velocity model of the crust and uppermost mantle in the Lei–Qiong volcanic region, derived from 3-year seismic data (2016–2018) from 34 stations and the use of the ambient noise tomography method. An evident columnar low-velocity anomaly was imaged in the crust and uppermost mantle beneath the Wushi Sag (WSS), Beibu Gulf, potentially suggesting that the center of either one branch or the entirety of the Hainan mantle plume impacts the crust here. This low-velocity anomaly is overlaid by a local Moho deepening, indicative of underplating beneath the existing crust. The Maanling–Leihuling Volcanic Field (MLVF) in northern Hainan Island, previously considered the center of the hotspot, does not exhibit such distinct velocity anomalies. Instead, subtle lower crustal anomalies beneath the MLVF are linked with the upper mantle low-velocity zone beneath the WSS. Additionally, the high-conductivity bodies beneath the MLVF indicate lateral magma transport. Earthquake swarms and deep-seated seismic events beneath the WSS further support the presence of magmatic processes. This study indicates that in the Lei–Qiong region, the interaction of the continental crust with the mantle plume centered in the WSS results in magma exhibiting both vertical ascent and lateral migration, leading to a dual low-velocity shear wave pattern in the upper crust, which significantly influences the surface volcanic activity.

Investigating Subglacial Water‐Filled Cavities by Spectral Analysis of Ambient Seismic Noise: Results on the Polythermal Tête‐Rousse Glacier (Mont Blanc, France)

AbstractPolythermal glaciers can trap considerable volumes of liquid water with the potential to generate devastating outburst floods. This study aims to identify water‐filled subglacial reservoirs from ambient seismic noise collected by moderate‐cost surveys. The horizontal‐to‐vertical spectral ratio technique is highly sensitive to impedance contrasts at interfaces, thus commonly used to estimate glacier thickness. Here, we focus on the inverse ratio, that is, the V/H spectral ratio (VHSR), whose high values indicate a low impedance volume beneath the surface, suggesting subglacial cavities. We analyze VHSR peaks from a seismic array of 60 nodes installed on the Tête‐Rousse Glacier (Mont Blanc massif, French Alps); data were gathered over 15 days. Mapping the VHSR amplitude over the free surface reveals the main cavity locations and the basal areas affected by melting within the glacier. Results obtained in the field are supported by a conceptual model based on 3D finite‐element simulations.

Imaging Urban Hidden Faults with Ambient Noise Recorded by Dense Seismic Arrays

Abstract The identification of preexisting near-surface faults represents a piece of crucial information needed to correctly assess the seismic hazard of any area. The mapping of these structures is particularly challenging in densely populated and heavily urbanized areas. We use ambient seismic noise recorded by a dense array in Seal Beach, California, to image shallow fault lines via a reflected surface-wave analysis. Our results highlight the presence of previously unknown shallow faults that correlate remarkably well with shallow seismicity and active survey images.

Using high-precision travel time extraction to detect time deviation of seismic instruments

The method of seismic ambient noise cross-correlations (NCFs) has been demonstrated to be applicable for time offset measurement, especially in evaluating instrument clocks. Continuous recording of seismic ambient noise data makes it possible to analyze the performance of seismic instruments online. However, long-term cross-correlation and stacking calculations are required to obtain accurate travel time from ambient noise, which greatly reduces the time resolution of instrument performance detection. Therefore, we propose a travel time extraction method based on time-frequency analysis, which could obtain the travel time accurately even though the NCF has a low signal-to-noise ratio (SNR), and it is applied to the measurement of clock offsets in seismic instruments. The method combines S Transform and dictionary learning to improve the SNR of NCFs, and uses a peak extraction algorithm based on short-time Fourier transform to obtain accurate travel times. Additionally, the travel time drift of the station pair can be obtained by calculating the travel time difference between causal and acausal parts of NCFs. Using the data from ambient noise observations and the real data with time errors to verify that the proposed method can obtain accurate travel time for NCF with SNR lower than 6 and it can pick up a time offset as low as one sampling point, the detectable change is 0.046% of travel time, which is crucial for detecting weak changes in the performance of seismic instruments.

Shear‐wave velocity structure derived from seismic ambient noise recorded by a small reservoir monitoring network

AbstractReservoir monitoring is essential to guarantee safe operations for all activities involving the production and injection of fluids into the subsurface, such as hydrocarbon production, gas storage and the exploitation of geothermal reservoirs. For this purpose, microseismic monitoring networks are operated in real time in order to identify and locate any possible seismic events in the vicinity of the reservoir. The goal of this study is to investigate whether the large amount of ambient seismic noise recorded by seismic reservoir monitoring networks can be used to infer a one‐dimensional shear‐wave velocity profile representative of the area covered by the network. Shear‐wave velocities are generally difficult to characterize and constrain, yet they are key to precisely locate seismic events. The adopted workflow consists of three steps: first, the cross‐correlation functions between all station pairs are retrieved, using 1 year of continuous data; second, the average group‐ and phase velocity dispersion curves are extracted; third, a joint group and phase velocity inversion is done. For validation, the obtained average shear‐wave velocity profile is compared with a regional model of the area as well as with local shear‐wave velocity measurements from a sonic log.

Filling the gap of seismic ambient noise taken from the earth by modification of the frequency content of the existing time series

Filling the gap of seismic ambient noise taken from the earth by modification of the frequency content of the existing time series

A Seismic Monitoring Tool for Tidal-Forced Aquifer Level Changes in the Río de la Plata Coastal Plain, Argentina

Ambient seismic noise has gained extensive applications in seismology and plays a pivotal role in environmental seismic studies. This study focuses on the Río de la Plata Coastal Plain, employing the horizontal-to-vertical spectral ratio (HVSR) method on ambient seismic noise records to analyze subsurface dynamics. The region’s hydrogeology is complex, featuring partially interconnected coastal aquifers. The HVSR analysis reveals two peaks, with P0 associated with the sediment-basement interface and P1 linked to a shallower stratigraphic discontinuity. Temporal analysis of P1 highlights cyclical patterns correlated with estuarine levels, suggesting a relationship between variations in seismic velocities and tidal dynamics. Comparisons with aquifer data support the hypothesis that tidal variations influence subsurface mechanical properties, impacting the HVSR function. The study hints at the potential of ambient seismic noise analysis as a non-invasive and cost-effective method for studying coastal aquifers and understanding groundwater dynamics. Ongoing research aims to further explore these relationships for enhanced groundwater resource management.

SeisMIC - an Open Source Python Toolset to Compute Velocity Changes from Ambient Seismic Noise

We present SeisMIC, a fast, versatile, and adaptable open-source software to estimate seismic velocity changes from ambient seismic noise. SeisMIC includes a broad set of tools and functions to facilitate end-to-end processing of ambient noise data, from data retrieval and raw data analysis via spectrogram computation, over waveform coherence analysis, to post-processing of the final velocity change estimates. A particular highlight of the software is its ability to invert velocity change time series onto a spatial grid, making it possible to create maps of velocity changes. To tackle the challenge of processing large continuous datasets, SeisMIC can exploit multithreading at high efficiency with an about five-time improvement in compute time compared to MSNoise, probably the most widespread ambient noise software. In this manuscript, we provide a short tutorial and tips for users on how to employ SeisMIC most effectively. Extensive and up-to-date documentation is available online. Its broad functionality combined with easy adaptability and high efficiency make SeisMIC a well-suited tool for studies across all scales.