The three-dimensional (3D) distributed acoustic sensing (DAS) vertical seismic profile (VSP) technique is an effective tool to characterize subsurface reservoirs, enabling the use of large and densely sampled borehole receiver arrays with many surface vibrator source points for onshore time-lapse monitoring. However, the processing of the DAS VSP signals for imaging purposes is based on a reliable wavefield separation, which may depend on the recognition and quality of the direct arrivals. To overcome this limitation for common-source gathers with poor signal-to- noise ratio or with interferences, we apply the dual-signal processing method, which allows us to estimate and separate the DAS wavefields by signals' combination without arrival picking. We present a case study of a 3D VSP DAS dataset recorded at a geothermal reservoir in Turkey, showing that the method, similar to a geophone and hydrophone combination, is robust and effective and can be advantageously integrated with the conventional processing. Supported by signal benchmarking, modelling and signal-to-noise ratio analysis, we treat common-source and common-receiver data. Our analysis shows the advantages and limitations of the proposed approach, valuable in the time-lapse perspective.

Seismic monitoring is essential for understanding subsurface processes, particularly in geothermal operations where low-magnitude events can provide valuable insights into reservoir behaviour. There are two significant challenges when monitoring the seismicity in Dutch geothermal operations: (1) detecting signals from seismic events as noise levels are typically high in regions hosting geothermal operations, and (2) accurately estimating their corresponding hypocentre and uncertainty. In this study, we present a comprehensive workflow for detecting and characterising low-magnitude seismic events. Specifically, we integrated data preparation, template-matching and machine-learning-based event detection, and probabilistic hypocentre estimation. Applying this workflow to 4 months of recordings in Kwintsheul, Netherlands, we detected 65 events with coherent signals, including six weak seismic events (ML < 0.0) near a local fault and a geothermal injection well. These events suggest the presence of a recurring microseismic sequence previously unreported in the area. However, spatial uncertainties, the short monitoring period, and the limited azimuthal coverage make the nature of these events unclear. Our findings highlight the importance of improving network design and refining velocity models to reduce uncertainties in event locations and magnitudes. The proposed workflow offers a scalable solution for enhancing seismic monitoring, particularly in urban and geothermal settings.

High-resolution seismic reflections are essential for imaging and monitoring applications. In seismic land surveys using sources and receivers at the surface, surface waves often dominate, masking the reflections. In this study, we demonstrate the efficacy of a two-step procedure to suppress surface waves in an active-source reflection seismic data set. First, we apply seismic interferometry (SI) by cross-correlation, turning receivers into virtual sources to estimate the dominant surface waves. Then, we perform adaptive subtraction to minimize the difference between the surface waves in the original data and the result of SI. We propose a new approach where the initial suppression results are used for further iterations, followed by adaptive subtraction. This technique aims to enhance the efficacy of data-driven surface-wave suppression through an iterative process. We use a 2-D seismic reflection data set from Scheemda, situated in the Groningen province of the Netherlands, to illustrate the technique’s efficiency. A comparison between the data after recursive interferometric surface-wave suppression and the original data across time and frequency–wavenumber domains shows significant suppression of the surface waves, enhancing visualization of the reflections for subsequent subsurface imaging and monitoring studies.

This study examines the applicability of seismic methods for monitoring hydrogen storage and detecting potential leakage in sandstone reservoirs, with a particular focus on amplitude variations in angle-dependent image gathers. Using the FluidFlower benchmark model as a controlled geological framework, two types of sandstone—mildly consolidated and unconsolidated—are considered. Gassmann’s fluid substitution is used to model elastic property changes under different hydrogen saturation and leakage scenarios, and seismic responses are generated using Kennett’s reflectivity method.

The analysis shows that seismic amplitudes are sensitive to both fluid saturation and lithology. In mildly consolidated sandstones, hydrogen injection leads to observable increases in amplitude at reservoir interfaces. In unconsolidated sandstones, elastic contrasts are more pronounced, resulting in stronger and more detectable seismic responses. These findings highlight the need to account for lithological characteristics when designing seismic monitoring strategies for underground hydrogen storage.

We examine the deep geothermal potential beneath Malargüe, Argentina, using global-phase seismic interferometry (GloPSI) and ghost reflections, retrieved from it, to analyze the intrinsic attenuation in the crust and upper mantle. By processing data from the MalARRgüe seismic array and distant earthquakes, we identify distinct patterns of seismic-wave attenuation: the crust displays moderate attenuation, while the upper mantle near the Moho discontinuity shows much higher attenuation. This sharp contrast suggests the presence of elevated temperatures or partial melt, possibly linked to a magma chamber, which could enhance geothermal potential in the region. The method provides higher spatial resolution and depth-specific information than traditional models, allowing non-invasive identification of zones with increased heat flow—potential geothermal “sweet spots.” This approach also avoids the need for expensive drilling, making it valuable for large-scale geothermal assessment.

The overburden structures often can distort the responses of the target region in seismic data, especially in land datasets. Ideally, all effects of the overburden and underburden structures should be removed, leaving only the responses of the target region. This can be achieved using the Marchenko method. The Marchenko method is capable of estimating Green's functions between the surface of the Earth and arbitrary locations in the subsurface. These Green's functions can then be used to redatum wavefields to a level in the subsurface. As a result, the Marchenko method enables the isolation of the response of a specific layer or package of layers, free from the influence of the overburden and underburden. In this study, we apply the Marchenko-based isolation technique to land S-wave seismic data acquired in the Groningen province, the Netherlands. We apply the technique for combined removal of the overburden and underburden, which leaves the isolated response of the target region, which is selected between 30 and 270 m depth. Our results indicate that this approach enhances the resolution of reflection data. These enhanced reflections can be utilised for imaging and monitoring applications.

Seismic interferometry (SI) retrieves the Green function between two receiver locations using their recordings from a boundary of sources. When using sources and receivers only at the surface, the virtual-source gathers retrieved by SI contain pseudo-physical reflections as well as ghost (non-physical) reflections. These ghost reflections are the results of the cross-correlation or auto-correlation (AC) of primary reflections from two different depth levels, and they contain information about the seismic properties of specific layers in the subsurface. We investigated the application of ghost reflections for layer-specific characterization of the shallow subsurface using SI by AC. First, we showed the technique's potential using synthetic data for a subsurface model with a lateral change in velocity, a gradient in depth for velocity, a thickness change and a velocity change of the target layer. Then, we applied the technique to shallow subsurface field data. We also focused on improving the retrieval of ghost reflections by removing the free-surface multiples and muting undesired events in active-source gathers before applying SI. Our results demonstrate that the ghost reflections can be used advantageously to characterize the layer that causes them to appear in the results of SI. Consequently, they can also provide valuable information for imaging and monitoring shallow subsurface structures.

As part of the Synergetic Utilisation of CO (Formula presented.) storage Coupled with geothermal EnErgy Deployment project, investigating CO (Formula presented.) reinjection with different seismic methods, both passive and active seismic surveys have been conducted at the geothermal power plant at Hellisheiði, Iceland. During the 2021 survey, two geophone lines recorded noise for a week. We process the passive-source data with seismic interferometry to image the subsurface structure around the CarbFix2 reinjection reservoir. To improve image quality, we perform an illumination analysis to select only noise panels dominated by body-wave energy. The results show that most noise panels are dominated by air-wave energy arriving from the direction of the power plant. We use panels with a near-vertical incidence to create a zero-offset image and a larger selection of body-wave-dominated panels to create virtual common-shot gathers. We process the gathers with a simple reflection seismology processing workflow to obtain stacked images. The zero-offset images show a relatively lower signal-to-noise ratio and only horizontal reflectors. The stacked images show slightly dipping reflectors and possibly lateral amplitude variations around the expected injection region. This could indicate a region of interest for future research into the reinjection reservoir.

Lack of data and urban noise pose significant challenges to monitoring anthropogenic seismicity in densely populated areas such as the Randstad region in the Netherlands. We deployed a temporary seismic array to monitor a geothermal doublet located at Kwintsheul, Netherlands. We implement innovative array processing, beamforming, and ML automatic-picking techniques to detect low-magnitude microseismic events that could be obscured by urban noise. Additionally, we propose a novel method to incorporate model uncertainties into hypocenter estimations based on the open-access subsurface information of the Netherlands. Contrary to previous studies, our analysis clearly shows that local low-magnitude seismicity does exist and highlights the value of denser seismic arrays and novel detection techniques for monitoring anthropogenic seismicity. The proposed hypocenter localization aids in avoiding under- or overestimation of location uncertainties, which is crucial for informed decision-making. This study advances seismic monitoring techniques in urban geothermal settings, providing critical data for informed decisionmaking and risk assessment of geothermal operations.

Seismic interferometry (SI) retrieves new seismic responses, for example reflections, between either receivers or sources. When SI is applied to a reflection survey with active sources and receivers at the surface, non-physical (ghost) reflections are retrieved as well. Ghost reflections, retrieved from the correlation of two primary reflections or multiples from two different depth levels, are only sensitive to the properties in the layer that cause them to appear in the result of SI, such as velocity, density and thickness. We aim to use these ghost reflections for monitoring subsurface changes, to address challenges associated with detecting and isolating changes within the target layer in monitoring. We focus on the feasibility of monitoring pore-pressure changes in the Groningen gas field in the Netherlands using ghost reflections. To achieve this, we utilize numerical modelling to simulate scalar reflection data, deploying sources and receivers at the surface. To build up subsurface models for monitoring purposes, we perform an ultrasonic transmission laboratory experiment to measure S-wave velocities at different pore pressures. Applying SI by autocorrelation to the modelled data sets, we retrieve zero-offset ghost reflections. Using a correlation operator, we determine time differences between a baseline survey and monitoring surveys. To enhance the ability to detect small changes, we propose subsampling the ghost reflections before the correlation operator and using only virtual sources with a complete illumination of receivers. We demonstrate that the retrieved time differences between the ghost reflections exhibit variations corresponding to velocity changes inside the reservoir. This highlights the potential of ghost reflections as valuable indicators for monitoring even small changes. We also investigate the effect of the sources and receivers’ geometry and spacing and the number of virtual sources and receivers in retrieving ghost reflections with high interpretability resolution.

CO2 capture and underground storage, combined with geothermal resource exploitation, are vital for future sustainable and renewable energy. The SUCCEED project explores the feasibility of re-injecting CO2 into geothermal fields to enhance production and store CO2 for climate change mitigation. This integration requires novel time-lapse monitoring approaches. At the Hellisheiði geothermal power plant in Iceland, seismic surveys utilizing conventional geophones and a permanent fiber-optic helically wound cable (HWC) for Distributed Acoustic Sensing (DAS) were designed to provide subsurface information and CO2 monitoring. This work details the feasibility study and active seismic acquisition of the baseline survey, focusing on optical fiber sensitivity, seismic modeling, acquisition parameters, source configurations, and quality control. Post-acquisition signal analysis using a novel electromagnetic vibrating source is discussed. The integrated analysis of datasets from co-located sensors improved quality-control performance and geophysical interpretation. The study demonstrates the advantages of using densely sampled DAS data in space by multichannel processing. This experimental work highlights the feasibility of using HWC DAS cables in active surface seismic surveys with an environmentally friendly electromagnetic source, providing also a unique case of joint signal analysis from different types of sensors in high-temperature geothermal areas for energy and CO2 storage monitoring in a time-lapse perspective.

The Marchenko method is capable of estimating Green’s functions between the surface of the Earth and arbitrary locations in the subsurface. These Green’s functions are used to redatum wavefields to a deeper level in the subsurface. The Marchenko method enables the isolation of the response of a specific layer or package of layers, free from the influence of the overburden and underburden. In this study, we apply the Marchenko-based isolation technique to land S-wave seismic data acquired in the Groningen province, the Netherlands. We apply the technique for combined elimination of the overburden and underburden. Our results indicate that this approach enhances the resolution of reflection data. These enhanced reflections can be utilised for imaging and monitoring applications.

Geothermal power production may result in significant CO2 emissions as part of the produced steam. CO2 capture, utilisation, subsurface storage (CCUS) and developments to exploit geothermal resources are focal points for future clean and renewable energy strategies. The Synergetic Utilisation of CO2 Storage Coupled with Geothermal Energy Deployment (SUCCEED) project aims to demonstrate the feasibility of using produced CO2 for re-injection in the geothermal field to improve geothermal performance, while also storing the CO2 as an action for climate change mitigation. Our study has the aim to develop innovative reservoir-monitoring technologies via active-source seismic data acquisition using a novel electric seismic vibrator source and permanently installed helically wound cable (HWC) fibre-optic distributed acoustic sensing (DAS) system. Implemented together with auxiliary multi-component (3C and 2C) geophone receiver arrays, this approach gave us the opportunity to compare and cross-validate the results using wavefields from different acquisition systems. We present the results of the baseline survey of a time-lapse monitoring project at the Hellisheiði geothermal field in Iceland. We perform tomographic inversion and multichannel seismic processing to investigate both the shallower and the deeper basaltic rocks targets. The wavefield analysis is supported by seismic modelling. The HWC DAS and the geophone-stacked sections show good consistency, highlighting the same reflection zones. The comparison of the new DAS technology with the well-known standard geophone acquisition proves the effectiveness and reliability of using broadside sensitivity HWC DAS in surface monitoring applications.

Knowledge about the temporal evolution of a volcano is fundamental for an accurate understanding of the occurring physical dynamic processes and an appropriate assessment of the most probable near‐future volcanic scenarios. Using seismic data recorded in the area of one of the most hazardous volcanoes along the Argentina–Chile, international border—Copahue volcano, we obtain information for an improved interpretation of the processes that occurred before, during, and after eruptive events. We use a single‐station methodology to assess variations in the mechanical properties and internal structure of the Copahue volcano. Thus, we obtain information about structural alterations, friction and fractures, and variations in rigidity in the volcanic system. Our results show that the time variations of the evaluated seismic parameters correlate to the volcanic phenomena observed on the surface, that is, incandescence and ash emissions. Accounting for the physical processes, to which the analyzed seismic parameters are sensitive, and previous models developed for the area, we propose a physical model explaining the eruptive events that occurred at Copahue in the period 2018–2023. This model can potentially be used for the assessment of future scenarios, which is of fundamental importance for the institutions in charge of the real‐time monitoring of Copahue volcano to improve the quality of their evidence‐based decisions.

We apply supervirtual interferometry to boost the surface-wave content of two different seismic surveys. The method uses seismic interferometric principles to exploit data redundancy in multi-fold surveys. The effect on the first survey is generally positive, where the signal-to-noise ratio is improved and the relative amplitude of other events, like direct waves or reflections, is decreased. The second survey shows that the effects are not always positive. For some shots, the quality of the dispersion curve decreases and for some a higher mode becomes more dominant. This can be caused when assumptions made for seismic interferometry by corrrelation are not complied with, primarily heterogeneities in the medium and attenuation. As such, the effect of applying supervirtual interferometry could be used as an indication for local heterogeneities.

Safe navigation in ports and waterways subjected to siltation requires nautical depth monitoring. For this purpose, surveying vessels equipped with a zero-offset echo sounder and intrusive point measurements are frequently used. Because these measurements depend on the availability of a surveying vessel and require access to quay walls, such as at the container terminals in seaports, the temporal resolution is limited. Especially at these locations, a high temporal resolution monitoring system could allow for a higher occupancy rate. We propose to use Distributed Acoustic Sensing to monitor the nautical depth using fiber-optical cables. We install five horizontal fibers at different heights between two points and continuously record along the complete installation. Analysing the continuous recordings, we show that horizontal fibers can be used to monitor the water-mud interface depth with a vertical resolution around six mm. Multiple passive sources, like vessel movements and water currents, are used to estimate the water-mud interface.

Using post-critical reflection data, it is possible to obtain useful information that allows more reliable geological characterization of the subsurface. However, the strong distortion caused by the phase shift in post-critical wavelets makes the use of post-critical reflections rather challenging. For this reason, an approach which is capable of estimating the phase shift of each wavelet of a reflection event in a data-driven manner is desirable. In this vein, in case the frequency spectrum of a wavelet can be correctly estimated, it is possible to estimate the instantaneous phase shift. In this work, we propose an approach which can perform such estimation based on spectral recomposition of seismic data. We design an inversion approach in order to reconstruct the seismic spectrum of the wavelets of a reflection event, which subsequently allows us to estimate the instantaneous phase of each wavelet of the near-surface reflection events without performing prior velocity analysis and/or critical-angle estimation. After finding the instantaneous phase for each wavelet of a reflection event, we show next how one can find the respective phase shifts that can then be corrected.

Poor knowledge of source and receiver positions in ultra-high-resolution marine seismic data is the cause of severe damage which requires novel processing techniques to mitigate. This type of seismic data is highly relevant for ultra-shallow subsurface imaging in geo-engineering projects both offshore and in harbours. Current positioning technologies are limited partly by their accuracy but also the fact that they are only placed on head and tail buoys of the towed arrays. This leaves receiver locations on the length of the streamer cable to be interpolated. Rather than developing additional processing methods, we propose to improve the quality of the data by introducing a complimentary receiver positioning system to reconstruct the shape of the streamer cable in 4D using Fiber Optic Shape Sensing (FOSS) technology. In this abstract, we outline the key features of FOSS technology and provide a conceptual overview of our efforts to bring this technology to the field.

High-resolution seismic reflections are essential for imaging and monitoring applications using data-driven methods such as seismic interferometry (SI) and Marchenko redatuming. For seismic land surveys using sources and receivers at the surface, the surface waves are the dominant noises that mask the reflections. We use SI to suppress surface waves from the reflection dataset. SI is a technique that allows the retrieval of new seismic responses at one receiver from a virtual source at the position of another receiver using, e.g., cross-correlation or convolution. We processed a two-dimensional seismic reflection dataset acquired along a line in Scheemda, located in the Groningen province of the Netherlands. The sources are placed with a spacing of 2 m, and 601 receivers are placed every 1 m. We implemented some pre-processing steps, including source signature deconvolution and filtering. Then, we applied SI by cross-correlation by turning receivers into virtual sources to estimate the dominant surface waves. Afterwards, we performed adaptive subtraction with different filter parameters for the matching filter to minimise the difference between the surface waves in the original data and the result of SI. Comparing the retrieved results from SI with the original data in the time domain and the frequency-wavenumber domain shows that at least some parts of surface waves are suppressed from the dataset, which can help to better visualise reflections for future studies in imaging and monitoring the subsurface.

We conducted ground penetrating radar (GPR) surveys to detect the presence of simulated clandestine burials at the Amsterdam Research Initiative for Subsurface Taphonomy and Anthropology (ARISTA) test facility. Our aim is to determine the characteristic responses of the simulated clandestine burials in this man-made sandy environment (reclaimed land) and use them to provide recommendations for forensic investigations. We performed GPR surveys over three simulated clandestine burials at ARISTA during four non-consecutive days. The acquired data represent common-offset data to investigate changes to burial detectability depending on central antenna frequency (250 MHz and 500 MHz), different GPR instruments (NOGGIN or pulseEKKO), changes to survey grid orientation relative to burials, and increased soil moisture content in the survey area. In common-offset radargrams the burial anomalies take on many forms, appearing as disruptions to existing features (direct-wave arrivals and soil horizons) and as isolated reflection events (hyperbolic events and burial-length horizontal anomalies). In time slices, the burials are characterized by high- or low-amplitude rectangular anomalies. When used in conjunction, the radargrams and time slices produce characteristic responses consistent with the locations of the burials, regardless of the survey grid orientation. Increased soil moisture at the site improves the detectability of the burials.