Geophone Array Research Articles

Matrix imaging as a tool for high-resolution monitoring of deep volcanic plumbing systems with seismic noise

Volcanic eruptions necessitate precise monitoring of magma pressure and inflation for improved forecasting. Understanding deep magma storage is crucial for hazard assessment, yet imaging these systems is challenging due to complex heterogeneities that disrupt standard seismic migration techniques. Here we map the magmatic and hydrothermal system of the La Soufrière volcano in Guadeloupe by analyzing seismic noise data from a sparse geophone array under a matrix formalism. Seismic noise interferometry provides a reflection matrix containing the signature of echoes from deep heterogeneities. Using wave correlations resistant to disorder, matrix imaging successfully unscrambles wave distortions, revealing La Soufrière’s internal structure down to 10 km with 100 m resolution. This method surpasses the diffraction limit imposed by geophone array aperture, providing crucial data for modeling and high-resolution monitoring. We see matrix imaging as a revolutionary tool for understanding volcanic systems and enhancing observatories’ abilities to monitor dynamics and forecast eruptions.

A 3 × 3 Phase Demodulation System Based on Active Ellipse Fitting for 3C Fiber-Optic Geophone Array and Field Tests

A 3 × 3 Phase Demodulation System Based on Active Ellipse Fitting for 3C Fiber-Optic Geophone Array and Field Tests

Seismic Magnitude Estimation Using Low-Frequency Strain Amplitudes Recorded by DAS Arrays at Far-Field Distances

ABSTRACT Downhole distributed acoustic sensing (DAS) data are now routinely acquired on fiber-optic cables deployed in wells for seismic imaging and microseismic monitoring. We develop a semiempirical workflow for estimating scalar seismic moment and moment magnitude of earthquakes using strain data recorded by downhole DAS arrays. At far-field distances, the time integral of axial strain is proportional to the displacement scaled by apparent slowness. Therefore, seismic moment can be directly estimated from the amplitude of the low-frequency plateau of the strain spectra divided by frequency, similar to the methodology commonly employed for far-field displacement spectra. The effect of polarization on strain amplitudes for different types of body waves is accounted for. Benefitting from the large spatial coverage provided by DAS arrays, moment estimates from multiple channels are averaged and an average radiation coefficient is assumed over the focal sphere. We validate the methods using data of microseismic events simultaneously recorded by a surface geophone array and by DAS on fiber deployed in two horizontal wells during a hydraulic fracturing experiment. For 106 microseismic events in the magnitude range ∼ −0.65 to ∼ +0.55, we find the DAS-derived magnitudes to be consistent with the magnitudes derived from the geophone array using traditional methods, with ∼95% of the magnitude estimates differing by less than ∼0.26 units. The workflow can be potentially extended to DAS arrays in vertical wells and to S waves recorded on dark fiber DAS arrays at the surface. This methodology does not require any calibration beyond knowledge of local seismic properties, and the use of the lowest possible frequencies reduces the influence of subsurface heterogeneities and the finite spatiotemporal extent of earthquake ruptures. The capacity to estimate robust seismic magnitudes from downhole DAS arrays allows improved evaluation and management of fracture growth and more effective mitigation of induced seismicity.

Analysis of bubble curtain effectiveness in the coastal Virginia offshore wind turbine installation

The Coastal Virginia Offshore Wind (CVOW) consists of two turbines roughly 40 km off the coast of Virginia Beach, Virginia. Water- and seabed-borne acoustic signals from impact pile driving at CVOW were recorded during the installation of these turbines in May 2020. In-water pressure signals were measured using two vertical line arrays (VLAs) at ranges of 3 km and 7.5 km. The water depth at the wind turbines and both VLAs was about 26 m. During installation, one of the piles utilized a double bubble curtain during construction while the other pile did not. Bubble curtains are used to reduce the acoustic impacts of pile driving by creating a barrier of bubbles around the source. We found that the bubble curtains were most effective at longer ranges and at frequencies above 200 Hz. Normal modes are an efficient representation of the acoustic field in this relatively range-independent shallow water environment. The amplitudes of acoustic modes at several frequencies were used to analyze the effectiveness of bubble curtains. Energy propagating in the seabed was also measured by an array of geophones and was found to be unattenuated by the bubble screens.

Superimposed imaging of acoustic wave reflections for the detection of underground nonmetallic pipelines

Due to the non-conductive and non-magnetic properties, nonmetallic pipelines are difficult to be detected by traditional pipe location technologies. This paper presents a superimposed imaging method of acoustic wave reflections for pipe location, which operates on the propagation of elastic waves. The propagation and attenuation model of elastic waves in soil are constructed according to the geometric relationship between the acoustic source, geophone array and pipelines. The two-dimensional and three-dimensional acoustic field diagrams of underground pipeline are generated by superimposed imaging of the cross-correlation coefficients between the signals from the sound source and geophone array, with the attenuation caused by hysteretic damping and geometric dissipation considered in the imaging process. In order to suppress clutter interference on the imaging results, the strategy of ‘multi-point transmit, multi-point receive and cross-correlation coefficient superposition’ is adopted. In the simulation, comparison is made to demonstrate the influences of different excitation sources on the detection imaging results, including the single frequency signal, multi-frequency signal, Gaussian pulse signal and sweep signal. It is found that the excitation signals with rich frequency components are more conducive to improving the resolution of detection images. The effectiveness of the proposed imaging method is further verified in the experimental work, which may be beneficial for the visualization and determination of the location, depth and orientation of underground non-metallic pipelines.

Seismic monitoring of gas emissions at mud volcanoes: The case of Nirano (northern Italy)

Seismic signals generated at the Nirano mud volcanoes in Northern Italy have been monitored by deploying a set of small dimensions seismic arrays of vertical geophones and thee-directional sensors. During two seismic surveys campaigns, seismic signals characterized by sequences of short impulsive signals (lasting 0.1 s–0.2 s) were identified above the background seismic noise. The respective seismic sources have been identified at shallow depths (<30 m) and results sparsely distributed over a wide area. Estimated propagation velocities and polarization analysis indicate that detected pulses also include a significant S waves contribution. These findings have been interpreted as the effect of a stick-slip mechanism due to the interaction between exsolved gas bubbles, mud plugs and the vent walls. On the basis of this model, an estimate of the gas outflow was attempted and results in line with independent measurements of CH4 and CO2 emissions carried out in the area.

The Crustal Magmatic Structure Beneath the Denali Volcanic Gap Imaged by a Dense Linear Seismic Array

AbstractThe crustal structure in south‐central Alaska has been influenced by terrane accretion, flat slab subduction, and a modern strike‐slip fault system. Within the active subduction system, the presence of the Denali Volcanic Gap (DVG), a ∼400 km region separating the active volcanism of the Aleutian Arc to the west and the Wrangell volcanoes to the east, remains enigmatic. To better understand the regional tectonics and the nature of the volcanic gap, we deployed a month‐long north‐south linear geophone array of 306 stations with an interstation distance of 1 km across the Alaska Range. By calculating multi‐component noise cross‐correlation and jointly inverting Rayleigh wave phase velocity and ellipticity across the array, we construct a 2‐D shear wave velocity model along the transect down to ∼16 km depth. In the shallow crust, we observe low‐velocity structures associated with sedimentary basins and image the Denali fault as a narrow localized low‐velocity anomaly extending to at least 12 km depth. About 12 km, below the fold and thrust fault system in the northern flank of the Alaska Range, we observe a prominent low‐velocity zone with more than 15% velocity reduction. Our velocity model is consistent with known geological features and reveals a previously unknown low‐velocity zone that we interpret as a magmatic feature. Based on this feature's spatial relationship to the Buzzard Creek and Jumbo Dome volcanoes and the location above the subducting Pacific Plate, we interpret the low‐velocity zone as a previously unknown subduction‐related crustal magma reservoir located beneath the DVG.

Imaging the Crustal and Upper Mantle Structure of the North Anatolian Fault: A Transmission Matrix Framework for Local Adaptive Focusing

AbstractImaging the structure of major fault zones is essential for our understanding of crustal deformations and their implications on seismic hazards. Investigating such complex regions presents several issues, including the variation of seismic velocity due to the diversity of geological units and the cumulative damage caused by earthquakes. Conventional migration techniques are in general strongly sensitive to the available velocity model. Here we apply a passive matrix imaging approach which is robust to the mismatch between this model and the real seismic velocity distribution. This method relies on the cross‐correlation of ambient noise recorded by a geophone array. The resulting set of impulse responses form a reflection matrix that contains all the information about the subsurface. In particular, the reflected body waves can be leveraged to: (a) determine the transmission matrix between the Earth's surface and any point in the subsurface; (b) build a confocal image of the subsurface reflectivity with a transverse resolution only limited by diffraction. As a study case, we consider seismic noise (0.1–0.5 Hz) recorded by the Dense Array for Northern Anatolia that consists of 73 stations deployed for 18 months in the region of the 1999 Izmit earthquake. Passive matrix imaging reveals the scattering structure of the crust and upper mantle around the North Anatolian Fault zone over a depth range of 60 km. The results show that most of the scattering is associated with the Northern branch that passes throughout the crust and penetrates into the upper mantle.

Time-Varying Moment-Tensor Analysis with Application to Buried Chemical Explosions

Abstract The Source Physics Experiment (SPE) Phase I consisted of a series of over-buried, horizontally colocated chemical explosions at the Nevada National Security Site. Seismic waveforms from these explosions recorded at near-source accelerometers, local geophone arrays, and regional seismic stations provided a rich suite of observations suitable for resolving fine source details. To investigate the time-varying source history of the explosions, we used the frequency-domain moment-tensor inversion method described in Yang et al. (2018) with added regularization and reconstruction to suppress the nonuniqueness evident in unconstrained inversion results. The inverted moment-rate spectra are accurate within the response band of the local geophones and, in all cases, display predominately isotropic characteristics. For SPE-4Prime, SPE-5, and SPE-6, we resolve predominately isotropic moment release followed by double couple and compensated linear vector dipole (CLVD) release later in the time-varying source history. We interpret these results both in terms of absolute depth and scaled depth of burial. The apparent non-isotropic release from SPE-4Prime and SPE-5 may simply reflect increased resolving power related to improved Earth model accuracy at greater absolute depths, whereas the non-isotropic release from SPE-6 likely reflects the larger damage associated with an event at a shallower scaled depth. These results provide insight into the time-varying source characteristics of shallow explosions and motivation to study shear-wave generation by inverting for fracture, spallation, induced slip, and other temporally delayed source processes through time-varying methods.

Developing a distributed acoustic sensing seismic land streamer: Concept and validation

Motivated by existing cabled seismic land-streamer designs, we develop a distributed acoustic sensing (DAS) land-streamer system for high-resolution near-surface seismic data acquisition. The system consists of a DAS interrogator unit (IU), a fiber-optic cable attached beneath a fire-hose assembly for environmental isolation and improved fiber-ground coupling, and a vehicle-mounted accelerated weight-drop source. The DAS land streamer is easily deployed and towed along the ground surface, allowing for spatially dense data acquisition. We report two field tests with the developed hardware to evaluate the DAS land-streamer performance. The first test investigates the effects of hose weight on the surface-deployed fiber and indicates that this approach improves fiber-ground coupling and leads to an improved signal-to-noise ratio (S/N). The second test demonstrates that the DAS land streamer records waveforms with similar phase and moveouts as those recorded by horizontal geophones but offers a higher native spatial density advantage than standard geophone arrays, leading to spatially dense waveforms, improved S/N after postprocessing, and superior surface-wave acquisition array mobility. Our findings suggest that a DAS land streamer is a promising alternative to traditional geophone-based surveys and may offer several advantages, such as faster survey acquisition speed and lower field costs due to reduced acquisition hardware requirements. However, methodological limitations include recording a single horizontal ground-motion component, a dependence on favorable fiber-ground coupling conditions, and the upfront cost of IU procurement. A DAS land streamer may be useful in numerous subsurface applications, such as (pseudo) 1D multichannel analysis of surface waves or 2D surface-wave inversion for S-wave velocity model estimation for geophysical, geologic, geotechnical, and environmental investigations.

Spatiotemporal evaluation of Rayleigh surface wave estimated from roadside dark fiber DAS array and traffic noise

Seismic imaging and monitoring of the near-surface structure are crucial for the sustainable development of urban areas. However, standard seismic surveys based on cabled or autonomous geophone arrays are expensive and hard to adapt to noisy metropolitan environments. Distributed acoustic sensing (DAS) with pre-existing telecom fiber optic cables, together with seismic ambient noise interferometry, have the potential to fulfill this gap. However, a detailed noise wavefield characterization is needed before retrievingcoherent waves from chaotic noise sources. We analyze local seismic ambient noise by tracking five-month changes in signal-to-noise ratio (SNR) of Rayleigh surface wave estimated from traffic noise recorded by DAS along the straight university campus busy road. We apply the seismic interferometry method to the 800 m long part of the Penn State Fiber-Optic For Environment Sensing (FORESEE) array. We evaluate the 160 virtual shot gathers (VSGs) by determining the SNR using the slant-stack technique. We observe strong SNR variations in time and space. We notice higher SNR for virtual source points close to road obstacles. The spatial noise distribution confirms that noise energy focuses mainly on bumps and utility holes. We also see the destructive impact of precipitation, pedestrian traffic, and traffic along main intersections on VSGs. A similar processing workflow can be applied to various straight roadside fiber optic arrays in metropolitan areas.

Geotechnical site characterization with 3D ambient noise tomography

We develop a new 3D ambient noise tomography (3D ANT) method for geotechnical site characterization. It requires recording ambient noise fields using a 2D surface array of geophones, from which experimental crosscorrelation functions (CCFs) are then extracted and directly inverted to obtain an S-wave velocity ([Formula: see text]) structure. The method consists of a forward simulation using 3D P-SV elastic wave equations to compute the synthetic CCF and an adjoint-state inversion to match the synthetic CCFs to the experimental CCFs for extraction of [Formula: see text]. The main advantage of the presented method, as compared with conventional passive-source seismic methods using characteristics of Green’s function (GF), is that it does not require equal energy on both sides of each receiver pair or far-field wavefields to retrieve the true GF. Instead, the source power spectrum density is inverted during the analysis and incorporated into the forward simulation of the synthetic CCFs to account for source energy distribution. After testing on synthetic data, the 3D ANT method is applied to 3 h of ambient noise recordings at the Garner Valley Downhole Array (GVDA) site in California, using a surface array of 196 geophones placed on a 14 × 14 grid with 5 m spacing. The inverted 3D [Formula: see text] model is found to be consistent with previous invasive and noninvasive geotechnical characterization efforts at the GVDA site.

Spectral Characteristics of Hydraulic Fracturing-Induced Seismicity Can Distinguish between Activation of Faults and Fractures

Abstract Analysis of earthquake spectra can aid in understanding source characteristics like stress drop and rupture complexity. There is growing interest in probing the similarities and differences of fault rupture for natural and human-induced seismic events. Here, we analyze waveform data from a shallow, buried geophone array that recorded seismicity during a hydraulic fracturing operation near Fox Creek, Alberta. Starting from a quality-controlled catalog of 4000 events between magnitude 0 and 3.2, we estimate source-spectral corner frequencies using methods that account for the band-limited nature of the sensor response. The stress-drop values are found to be approximately self-similar, but with a slight magnitude dependence in which larger events have higher stress drop (∼10 MPa). Careful analysis of the relative corner frequencies shows that individual fault and fracture segments experienced systematic variations in relative corner frequency over time, indicating a possible change in the stress state. Clustering analysis of source spectra based on the relative proportion of high- and low-frequency content relative to the Brune model further shows that event complexity evolves over time. In addition, the faults produce earthquakes with systematically larger stress-drop values than the fractures. Combined, these results indicate that the features activated by hydraulic fracturing experience observable changes in source behavior over time and exhibit different properties depending on the orientation, scale, and fabric of the structural feature on which they occur.

Quantitative evaluation of 3D land acquisition geometries with arrays and single sensors: Closing the loop between acquisition and processing

The growing popularity of land nodes demands careful survey design practices to smoothly supersede cabled seismic acquisition with geophone arrays. Unfortunately, trace density is often used as a catchall proxy to describe survey quality, which is a gross oversimplification. We describe comprehensive and quantitative workflows focusing on final image quality for evaluating existing or new 3D land acquisition geometries with arrays and single sensors. They streamline the design process, remove human bias, and close the loop between acquisition and processing. A central element is a data-driven approach for deriving absolute signal-to-noise ratio (S/N) directly from the data. The resulting S/N volumes can be analyzed as cubes or slices or distilled to statistical quantities. We apply new workflows to three typical use cases from 3D land seismic data. First, we quantitatively contrast different 3D data sets acquired with various field acquisition geometries and understand which acquisition parameters are likely responsible for S/N differences. Second, we perform a realistic numerical feasibility study evaluating multiple 3D acquisition geometries with arrays and single sensors and assess their expected performance on a complex SEG Advanced Modeling Arid data set representative of the desert environment. For feasibility studies, complete automation can be achieved by applying migration in lieu of processing and data-driven S/N as evaluation steps. Finally, we show how to predict absolute S/N outcomes of new 3D acquisitions based on the existing legacy data with different acquisition geometry. We demonstrate the excellent predictive power of the analytical signal-strength estimate formula for both field and synthetic elastic data sets. Translating survey design into commonly spoken “image S/N language” improves communication between geoscientists and enables more effective decision-making.

Acquisition and near-surface impacts on VSP mini-batch FWI and RTM imaging in desert environment

The SEG Advanced Modeling (SEAM) Arid benchmark model was designed to simulate an extremely heterogeneous low-velocity near surface (NS), which is typical of desert environments and typically not well characterized or imaged. Imaging of land seismic data is highly sensitive to errors in the NS velocity model. Vertical seismic profiling (VSP) partly alleviates the impact of the NS as the receivers are located at depth in the borehole. Deep learning (DL) offers a flexible optimization framework for full-waveform inversion (FWI), often outperforming typically used optimization methods. We investigate the quality of images that can be obtained from SEAM Arid VSP data by acoustic mini-batch reverse time migration (RTM) and full-waveform imaging. First, we focus on the effects of seismic vibrator and receiver array positioning and imperfect knowledge of the NS model when inverting 2D acoustic data. FWI imaging expectedly and consistently outperforms RTM in our tests. We find that the acquisition density is critical for RTM imaging and less so for FWI, while NS model accuracy is critical for FWI and has less effect on RTM imaging. Distributed acoustic sensing along the full length of the well provides noticeable improvement over a limited aperture array of geophones in imaging deep targets in both RTM and FWI imaging scenarios. Finally, we compare DL-based FWI imaging with inverse scattering RTM using the upgoing wavefield from the original SEAM data. Use of significantly more realistic 3D elastic physics for the simulated data generation and simple 2D acoustic inversion engine makes our inverse problem more realistic. We observe that FWI imaging in this case produces an image with fewer artifacts.

Machine learning-assisted processing workflow for multi-fiber DAS microseismic data

In recent years, Distributed Acoustic Sensing (DAS) deployed in deviated wells has been increasingly used for microseismic monitoring. DAS can provide observations of microseismic wavefields with high spatial resolution and wide aperture, at the cost of unusually large data volumes compared with conventional downhole microseismic monitoring. To tackle this big-data challenge, we have developed key elements of a processing workflow that is assisted by machine learning techniques. We trained a convolutional neural network (CNN) for event detection and a U-Net model for both P- and S-wave arrival time picking. The workflow was applied to two multiwell DAS datasets acquired during hydraulic fracturing completions in western Canada. These datasets also include co-located 3C borehole geophone arrays that enable further comparison between catalogs from both sensor types. Compared with a traditional short-term average/long-term average (STA/LTA) method for event detection, our results indicate that the CNN method has a lower false-trigger rate and increases the event catalog size by a factor of 2.6–5.6. U-Net yields arrival-time picks with relatively small errors, high efficiency, and minimal user intervention, providing hypocenter location and focal depth that is arguably more accurate than the geophone catalog. While the proposed automated workflow requires substantial effort to build high-quality and large training datasets, it enables the use of DAS for real-time seismicity monitoring and risk management after the training stage. Although the DAS system detected fewer events than the geophone catalog and missed smaller magnitude events, our results indicate that fiber-optic sensors provide enough sensitivity to detect and locate sufficient events to characterize the treatment stages. DAS also captured induced events located at a hypocentral distance of &amp;gt;1 km, which are possibly indicative of reactivation of structural features.

Comparisons Between Array Derived Dynamic Strain Rate (ADDS) and Fiber‐Optic Distributed Acoustic Sensing (DAS) Strain Rate

AbstractDistributed acoustic sensing (DAS) strain rate and particle velocity can be compared through approximate scaling with medium velocity. We instead performed a direct comparison between array derived dynamic strain (ADDS) rate and DAS strain rate for six frequency bands. The PoroTomo project at Brady's Hot Springs, Nevada, deployed a 240‐geophone 3C array co‐located with fiber‐optic DAS system and 8.7 km of buried cable. We selected subsets of the geophone array to create four smaller arrays and computed ADDS. The horizontal components of the ADDS were rotated into the direction of the fiber‐optic cable and then compared with the observed DAS strain rates. From three example regional earthquakes of local magnitudes 2.9, 4.1, and 4.3, the ADDS are found to be coherent with DAS for frequencies ≤1 Hz. For frequencies &gt;1‐Hz, this correlation decays quickly. Small differences between linear and areal dynamic strains at 1‐Hz suggest poor signal‐to‐noise or localized strain that is perturbed by shallow heterogeneities compare to the average strain propagating across the geophone array. The implication is that around 1‐Hz, straight fiber DAS is measuring axial strain along the fiber and can provide good approximations to translational particle motions. However, above 1‐Hz, DAS becomes more sensitive to shallow velocity gradients that can be beneficial for geophysical imaging yet becomes a limitation for traditional seismic analysis methods depending on absolute amplitude and phase from translational particle motions.

Full-Waveform Inversion of Fiber-Optic VSP Data From Deviated Wells

Distributed acoustic sensing (DAS) technology permits measuring the strain or strain rate along a fiber deployed in a well due to seismic wave propagation. In vertical seismic profiling (VSP) acquisitions where seismic waves are excited at the surface and measured by subsurface receivers in the well, the DAS serves as a fast alternative to a conventional geophone array. Like conventional multicomponent VSP velocity measurements, DAS VSP data contain information about the subsurface properties that are encoded in seismic events and attributes such as compressional and shear direct arrivals, reflections, converted modes, multiples, and amplitude and phase variations. These seismic data can be used to obtain elastic properties of the formation and characterize the reservoir. Full-waveform inversion (FWI) extracts the elastic properties of the formation from the seismic wavefield by minimizing the misfit between real measurements and synthetically modeled wavefields. The synthetically generated wavefields are obtained by solving partial differential equations that accurately model the physical phenomena of the real waveforms. For conventional geophone sensors, FWI is formulated for the particle velocity field. In this paper, we present a formulation of the modeling and inversion specifically for DAS measurements as an averaged strain along the fiber. The algorithm does not require converting the data to velocities. The gradient of the misfit function, by adjoint formulation, is a cross correlation in time of the forward-propagated wavefield and backward-propagated residuals injected from the receivers. For conventional sensors, the residuals are injected as force terms, but for DAS data, the residuals are averaged in space first and then injected as moment tensor sources with radiation patterns determined by the well deviation. For multi-offset in-plane and out-of-plane VSP acquisitions, a two-dimensional (2D) algorithm has been developed that inverts for a 2D distribution of elastic medium properties and includes three-dimensional (3D) well deviation effects. This paper will present the results of applying the inversion to real multi-offset, highly out-of-plane VSP fiber data acquired in a deviated well. Simulations confirm that the well trajectory has a considerable impact on the data amplitude and must be included in the modeling and inversion to reproduce amplitude variations. The inverted compressional and shear velocities agree well with the reference model based on sonic data. Another real data example is a multi-offset walk-above acquisition where a targeted domain is located below a deviated portion of the well. The inversion matches reflections and produces an image in the target area.

Monitoring CO2 Injection at the CaMI Field Research Station Using Microseismic Noise Sources

AbstractMonitoring subsurface velocity variations due to industrial activities using passive seismic imaging techniques has gained popularity in recent years. In this study, we examine the spatiotemporal variations of persistent, non‐ambient seismic noise during CO2 sequestration at the Containment and Monitoring Institute Field Research Station near Brooks, Alberta, Canada. Based on the temporal migration and power spectral density (PSD) analysis of continuous seismic records from both a dense geophone array and “X”‐shaped geophone lines operated from June to August 2019, we detect two non‐ambient local noise sources correlated with the local industrial activities during the two months: a dominant noise source (1–5 Hz) southeast of the study region and a slightly weaker noise source in the higher frequency range (5–15 Hz) around the injection well. The former noise source overlaps with the operations near a submersible disposal pump. The substantial diurnal variations in noise levels in PSD as a function of time of day, month and location are further evidence of these two noise sources. We propose that the persistent noise source around the injection well originated from the subsurface microtremors caused by the coupled interaction between the injected CO2 fluid and formation rocks. The proposed methods based on passive microseismic noise offer a potentially valuable strategy for long‐term evaluation of the safety of CO2 sequestration, which can be extended to future integrity monitoring of underground energy storage.

Advanced monitoring of tailings dam performance using seismic noise and stress models

Tailings dams retain the waste by-products of mining operations and are among the world’s largest engineered structures. Recent tailings dam failures highlight important gaps in current monitoring methods. Here we demonstrate how ambient noise interferometry can be applied to monitor dam performance at an active tailings dam using a geophone array. Seismic velocity changes of less than 1% correlate strongly with water level changes at the adjacent tailings pond. We implement a power-law relationship between effective stress and shear wave velocity, using the pond level recordings with shear wave velocity profiles obtained from cone penetration tests to model changes in shear wave velocities. The resulting one-dimensional model shows good agreement with the seismic velocity changes. As shear wave velocity provides a direct measure of soil stiffness and can be used to infer numerous other geotechnical design parameters, this method provides important advances in understanding changes in dam performance over time.