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D.S. Draganov
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Near-surface characterization of the lunar subsurface is essential for future exploration and infrastructure development, particularly for the construction of underground habitats that provide protection against radiation and micrometeorites. However, conventional seismic approaches for estimating subsurface properties typically rely on prior velocity models or multicomponent data, which are not available for legacy Apollo datasets. In this study, we propose a data-driven approach for estimating the critical angle (CA) and phase rotation of P-wave reflection events using active-source seismic data from the Apollo 16 mission. The CA is directly related to subsurface velocity contrasts, making it a key parameter for constraining near-surface structure. Our method is based on spectral recomposition, in which an inversion scheme is used to reconstruct the seismic spectrum of individual wavelets and extract their fundamental properties without requiring prior geological information. The proposed workflow is applied to near-surface lunar seismic data, allowing the detection of the CA and estimation of phase variations along reflection events. The results show that the estimated CA values are consistent with previously reported velocity structures, with differences on the order of a few per cent. These findings indicate that the method can reliably characterize near-surface lunar layers under limited data conditions. This work demonstrates the potential of data-driven spectral methods for extracting physically meaningful parameters from sparse and degraded seismic datasets, providing a practical tool for future lunar geophysical investigations and site characterization.
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Near-surface characterization of the lunar subsurface is essential for future exploration and infrastructure development, particularly for the construction of underground habitats that provide protection against radiation and micrometeorites. However, conventional seismic approaches for estimating subsurface properties typically rely on prior velocity models or multicomponent data, which are not available for legacy Apollo datasets. In this study, we propose a data-driven approach for estimating the critical angle (CA) and phase rotation of P-wave reflection events using active-source seismic data from the Apollo 16 mission. The CA is directly related to subsurface velocity contrasts, making it a key parameter for constraining near-surface structure. Our method is based on spectral recomposition, in which an inversion scheme is used to reconstruct the seismic spectrum of individual wavelets and extract their fundamental properties without requiring prior geological information. The proposed workflow is applied to near-surface lunar seismic data, allowing the detection of the CA and estimation of phase variations along reflection events. The results show that the estimated CA values are consistent with previously reported velocity structures, with differences on the order of a few per cent. These findings indicate that the method can reliably characterize near-surface lunar layers under limited data conditions. This work demonstrates the potential of data-driven spectral methods for extracting physically meaningful parameters from sparse and degraded seismic datasets, providing a practical tool for future lunar geophysical investigations and site characterization.
The Galápagos archipelago is one of the regions with the highest rates of eruption and surface magma emission in the world. Knowledge about the subsurface structure is fundamental for a better understanding of the dynamics of the magmatic systems in the area. However, the details of the internal architecture beneath the archipelago remain poorly constrained at both shallow and deep levels. To shed light on these, we apply seismic interferometry by autocorrelation to records of earthquakes with epicentral distances greater than 30°, obtained from 18 broadband stations deployed around two volcanoes (Cerro Azul and Sierra Negra) located in Western Galápagos, which is characterized by the highest volcanic activity of the archipelago. The methodology we apply results in the identification of the main mantle discontinuities at a wide range of depths with high resolution. We combine the individual results from all stations to construct a representative depth model for the entire region down to a depth of 800 km. Our results reveal coherent reflectivity patterns consistent with previously identified mantle structures and define the extent and location of the Galápagos mantle plume. These findings provide new insights into the mantle structure beneath the archipelago and can be used to improve our understanding of plume processes driving volcanism and its surface expression in the region.
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The Galápagos archipelago is one of the regions with the highest rates of eruption and surface magma emission in the world. Knowledge about the subsurface structure is fundamental for a better understanding of the dynamics of the magmatic systems in the area. However, the details of the internal architecture beneath the archipelago remain poorly constrained at both shallow and deep levels. To shed light on these, we apply seismic interferometry by autocorrelation to records of earthquakes with epicentral distances greater than 30°, obtained from 18 broadband stations deployed around two volcanoes (Cerro Azul and Sierra Negra) located in Western Galápagos, which is characterized by the highest volcanic activity of the archipelago. The methodology we apply results in the identification of the main mantle discontinuities at a wide range of depths with high resolution. We combine the individual results from all stations to construct a representative depth model for the entire region down to a depth of 800 km. Our results reveal coherent reflectivity patterns consistent with previously identified mantle structures and define the extent and location of the Galápagos mantle plume. These findings provide new insights into the mantle structure beneath the archipelago and can be used to improve our understanding of plume processes driving volcanism and its surface expression in the region.
Characterizing the shallow lunar subsurface is essential for future exploration activities, including landing-site assessment, infrastructure construction and subsurface resource investigation. However, conventional seismic approaches for near-surface characterization commonly depend on prior velocity information and assumptions regarding the geological structure, which are difficult to constrain for legacy Apollo seismic datasets acquired with unconventional geometries. In this study, we propose a data-driven methodology integrating spectral recomposition and neural networks (NNs) for lunar near-surface velocity-model prediction using active-source seismic data acquired during the Apollo missions. The proposed approach reconstructs spectral information associated with seismic wavelets linked to reflected events and incorporates this information as an additional feature for training a fully convolutional NN. To accommodate the Apollo acquisition geometry, the seismic traces were reorganized into combined common-receiver gathers. Synthetic datasets representative of expected lunar near-surface formations, including unconsolidated regolith and underlying consolidated layers, were generated to train the network. The predicted velocity models successfully reproduced the main kinematic characteristics observed in the lunar seismic data, including continuity of reflected events and travel-time trends. Forward modelling using the reconstructed models generated synthetic seismograms consistent with the observed Apollo seismic data, yielding low normalized root-mean-square error values. The results indicate the presence of a shallow low-velocity regolith layer overlying a more consolidated unit, consistent with previous Apollo 16 and Apollo 17 studies. These findings demonstrate that the proposed methodology can provide physically consistent lunar near-surface velocity models directly from seismic data, without requiring prior velocity analysis, highlighting its potential for future planetary seismic exploration and lunar geotechnical investigations.
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Characterizing the shallow lunar subsurface is essential for future exploration activities, including landing-site assessment, infrastructure construction and subsurface resource investigation. However, conventional seismic approaches for near-surface characterization commonly depend on prior velocity information and assumptions regarding the geological structure, which are difficult to constrain for legacy Apollo seismic datasets acquired with unconventional geometries. In this study, we propose a data-driven methodology integrating spectral recomposition and neural networks (NNs) for lunar near-surface velocity-model prediction using active-source seismic data acquired during the Apollo missions. The proposed approach reconstructs spectral information associated with seismic wavelets linked to reflected events and incorporates this information as an additional feature for training a fully convolutional NN. To accommodate the Apollo acquisition geometry, the seismic traces were reorganized into combined common-receiver gathers. Synthetic datasets representative of expected lunar near-surface formations, including unconsolidated regolith and underlying consolidated layers, were generated to train the network. The predicted velocity models successfully reproduced the main kinematic characteristics observed in the lunar seismic data, including continuity of reflected events and travel-time trends. Forward modelling using the reconstructed models generated synthetic seismograms consistent with the observed Apollo seismic data, yielding low normalized root-mean-square error values. The results indicate the presence of a shallow low-velocity regolith layer overlying a more consolidated unit, consistent with previous Apollo 16 and Apollo 17 studies. These findings demonstrate that the proposed methodology can provide physically consistent lunar near-surface velocity models directly from seismic data, without requiring prior velocity analysis, highlighting its potential for future planetary seismic exploration and lunar geotechnical investigations.
Accurate subsurface characterization is essential for the sustainable development of geothermal energy, particularly for assessing reservoir performance. In this study, we present the design and acquisition of an S-wave active-source seismic survey at the Kwintsheul geothermal site in the Netherlands, motivated by large uncertainties in microseismic-event locations and unresolved fault structures. Using a full-wavefield modelling and inversion framework, we evaluate multiple acquisition scenarios constrained by existing seismic data and field accessibility, and select an optimized survey geometry that balances imaging resolution and operational feasibility. We record an S-wave survey along a line of 3-component receivers using an electrical vibrator oriented in the crossline direction, which allows approximating an SH-wave data when using the crossline receiver component. The resulting dataset provides the basis for developing a site-specific S-wave velocity model and improving structural imaging of the geothermal reservoir.
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Accurate subsurface characterization is essential for the sustainable development of geothermal energy, particularly for assessing reservoir performance. In this study, we present the design and acquisition of an S-wave active-source seismic survey at the Kwintsheul geothermal site in the Netherlands, motivated by large uncertainties in microseismic-event locations and unresolved fault structures. Using a full-wavefield modelling and inversion framework, we evaluate multiple acquisition scenarios constrained by existing seismic data and field accessibility, and select an optimized survey geometry that balances imaging resolution and operational feasibility. We record an S-wave survey along a line of 3-component receivers using an electrical vibrator oriented in the crossline direction, which allows approximating an SH-wave data when using the crossline receiver component. The resulting dataset provides the basis for developing a site-specific S-wave velocity model and improving structural imaging of the geothermal reservoir.
Seismic interferometry (SI) retrieves seismic responses by, for example, cross-correlating observations at different receiver locations, offering a new data for subsurface imaging. Monitoring soil conditions along railway embankments is essential for ensuring the stability and safety of rail infrastructure. This study explores the use of active and passive seismic sources, combined with SI technique, to enhance subsurface imaging.Active seismic sources produce high-resolution reflections and surface-wave data, critical for identifying and monitoring key soil properties. These controlled sources provide superior signal-to-noise ratios and establish a reliable baseline for subsurface imaging. Passive seismic sources, such as train-induced vibrations, complement active-source data by providing continuous and natural excitation of the subsurface. Both active and passive sources are processed using SI technique, with adaptive subtraction applied to suppress dominant surface waves and improve imaging clarity.The integration of active- and passive-source data might help achieve better interpretation of the subsurface and monitoring for possible changes. Although this study is still under development, it demonstrates the potential to deliver a scalable, non-invasive solution for monitoring railway embankments and surrounding soils. By advancing our understanding of subsurface conditions, this approach could contribute substantially to the predictive maintenance and safety of rail infrastructure, paving the way for future innovations in geophysical monitoring.
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Seismic interferometry (SI) retrieves seismic responses by, for example, cross-correlating observations at different receiver locations, offering a new data for subsurface imaging. Monitoring soil conditions along railway embankments is essential for ensuring the stability and safety of rail infrastructure. This study explores the use of active and passive seismic sources, combined with SI technique, to enhance subsurface imaging.Active seismic sources produce high-resolution reflections and surface-wave data, critical for identifying and monitoring key soil properties. These controlled sources provide superior signal-to-noise ratios and establish a reliable baseline for subsurface imaging. Passive seismic sources, such as train-induced vibrations, complement active-source data by providing continuous and natural excitation of the subsurface. Both active and passive sources are processed using SI technique, with adaptive subtraction applied to suppress dominant surface waves and improve imaging clarity.The integration of active- and passive-source data might help achieve better interpretation of the subsurface and monitoring for possible changes. Although this study is still under development, it demonstrates the potential to deliver a scalable, non-invasive solution for monitoring railway embankments and surrounding soils. By advancing our understanding of subsurface conditions, this approach could contribute substantially to the predictive maintenance and safety of rail infrastructure, paving the way for future innovations in geophysical monitoring.
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.
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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.
Journal article
(2025)
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Faezeh Shirmohammadi, Deyan Draganov, Johno van IJsseldijk, Ranajit Ghose, Jan Thorbecke, Eric Verschuur, Kees Wapenaar
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.
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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.
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. ...
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. ...
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.
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.
Journal article
(2025)
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Faezeh Shirmohammadi, Deyan Draganov, Ranajit Ghose, Eric Verschuur, Jan Thorbecke, Kees Wapenaar
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.
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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.
Journal article
(2025)
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Flavio Poletto, Cinzia Bellezza, Sevket Durucan, Gualtiero Böhm, Fabio Meneghini, Athena Chalari, Anna Stork, Mahmut Parlaktuna, Erdinç Şentürk, Deyan Draganov, Gijs van Otten
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.
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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.
Urban challenges in seismology
Seismic monitoring of Kwintsheul’s geothermal operation (the Netherlands)
Journal article
(2025)
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David Naranjo, Marius Isken, Boris Boullenger, Tania Toledo, Cornelis Weemstra, Deyan Draganov
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.
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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.
Journal article
(2024)
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José Augusto Casas, Gabriela Alejandra Badi, Thomas Dylan Mikesell, Sebastian Esteban Garcia, Deyan Draganov
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.
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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.
Conference paper
(2024)
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F. Shirmohammadi, D. Draganov, J. van IJsseldijk, R. Ghose, J. Thorbecke, E. Verschuur, K. Wapenaar
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.
...
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.
Overcoming Urban Noise and Model Uncertainty
Induced Seismicity Monitoring in Dutch Geothermal Fields
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.
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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.
Journal article
(2024)
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Fabio Meneghini, Flavio Poletto, Cinzia Bellezza, Biancamaria Farina, Deyan Draganov, Gijs van Otten, Anna L. Stork, Gualtiero Böhm, Martijn Janssen, More Authors...
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.
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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.
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.
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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.
Journal article
(2024)
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Cinzia Bellezza, Erika Barison, Biancamaria Farina, Flavio Poletto, Fabio Meneghini, Gualtiero Böhm, Deyan Draganov, Martijn T. G. Janssen, Gijs van Otten, More authors...
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.
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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.
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.
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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.
Surface-Wave Supervirtual Seismic Interferometry
The Ugly, the Bad, and the Good
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.
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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.
Journal article
(2024)
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Faezeh Shirmohammadi, Deyan Draganov, Aukje Veltmeijer, Milad Naderloo, Auke Barnhoorn
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.
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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.