Once trained, surrogate models can emulate costly physics-based forward solvers at a negligeable computational cost, making them attractive tools to accelerate computationally expensive Markov chain Monte Carlo (MCMC) inversions. In the context of waveform modeling, it is nevertheless challenging to derive accurate surrogate models over the support of a realistically chosen prior probability density function (pdf). To circumvent this issue, one solution is to identify a region of high posterior densities with a somewhat inaccurate surrogate solver and then retrain a new surrogate model using samples drawn from this approximate and inflated posterior pdf. The resulting surrogate model has less coverage, but also higher accuracy in the posterior region of interest. Based on these ideas, we introduce a multifidelity MCMC formulation in the context of crosshole ground-penetrating radar (GPR) full-waveform inversion. To reduce the dimensions of the input and output domains as needed for efficient surrogate modeling, we rely on parameterization in the form of principal components inferred from training data, while surrogate modeling is performed with polynomial chaos expansions. To initialize the algorithm, a surrogate model is first learned between larger-scale features of the input domain and lower-frequency characteristics of the output domain using samples from the prior pdf. The associated modeling error is quantified and parameterized by a covariance matrix that is included in a model-error-aware likelihood function. An MCMC inversion is then performed using this first low-fidelity surrogate model to obtain a first approximation of an inflated posterior pdf. As this tempered posterior pdf has less support than the prior pdf, samples from it can be used to train a higher-fidelity surrogate model with larger input (finer-scale features) and output (higher frequencies) dimensions. This new surrogate model is then used in a second MCMC inversion with an updated likelihood function, and so on. In a test example with four fidelity levels, in which we move from initially 15 input principal components to 100, the posterior pdf is estimated at two-orders-of-magnitude lower computational cost than if using the full-physics forward solver only. The mean of the estimated posterior pdf is unbiased, which is not the case for an algorithm in which the surrogate model is learned using samples from the prior pdf only. The methodology could be adapted to other applications beyond crosshole GPR, such as seismic or tracer test data inversions.
How to cite: Linde, N., Meles, G., and Marelli, S.: Accelerated Bayesian Full Waveform Inversion with Multifidelity Surrogate Modeling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4226, https://doi.org/10.5194/egusphere-egu25-4226, 2025.
Imaging of the shallow near-surface, and any processes associated with it, is particularly important considering the interaction of this zone with human life. Climate change is considerably changing the properties and processes of the shallow subsurface, leading to an increase in triggering conditions of natural hazards, such as landslides. Hence, it is particularly important to have an accurate understanding of the evolution of subsurface properties and their temporal changes to assess the dynamic hazard conditions. One of the key problems to be solved are the physical limitations and resolution owing to classical geophysical methods such as refraction tomography, surface wave analysis or electrical resistivity tomography. On the other hand, more advanced methods such as the use of fiber-optic seismic are expensive in terms of acquisition and processing.
Here we present Spectral Ground Penetrating Radar (SGPR) data compared to classical geophysical techniques. The latest developments on SGPR significantly shift the possibilities of ground imaging by using a frequency modulated continuous electromagnetic wave (FMCW) in place of the impulse usually used in GPR technology. These novel devices and methodology represent a huge leap in subsurface imaging resolution, while also providing interpretation capabilities for results previously used primarily in seismic reflection methods in wider industrial approach. In addition, new visualization capabilities based on a number of physical parameters unique to this method are also under development.
An example of the application of this method is a time-lapse study of a landslide under significant anthropogenic influence in Ciśiec (Silesian voivodeship, Poland). This landslide poses high risk to the community, where accurate monitoring is crucial to ensure the safety of people and infrastructure. At the same time this site is a large-scale model of a landslide where triggering factors can be estimated and are representative to this part of the Outhern Carpathians. The SGPR method proved particularly useful in characterizing the 10-30 m zone, where other geophysical methods give limited or low-resolution information. This allowed very accurate imaging of slip planes and zones of compaction, further distinguishing structures not visible on other geophysical methods and which were not recognized in previous studies since 2018.
The results presented here demonstrate the usefulness of the SGPR methodology, especially in environments where other geoelectric and electromagnetic methods cannot be used or give limited results, and where seismic methods are expensive. Landslides are just one example of the application of this novel methodology, allowing both single and time-lapse measurements to be carried out quickly, cost-effectively and with unprecedented resolution.
How to cite: Marciniak, A., Trześniowski, Z., Majdański, M., Prykhodchenko, R., Uhlemann, S., Flores-Orozco, A., Oryński, S., Cader-Marciniak, J., Rzońca, P., and Kowalczyk, S.: Spectral Ground Penetrating Radar in Landslide Studies - The next-generation solution for near-surface imaging, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6478, https://doi.org/10.5194/egusphere-egu25-6478, 2025.
Ground penetrating radar (GPR) offers the great potential to non-invasively monitor soil and root conditions in agricultural environments. A novel experiment in Jülich aims at analysing the interactions between soil, plants and atmosphere under controlled laboratory conditions with as realistic as possible soil and atmosphere composition and temperature. In order to monitor the distribution of water and nutrition as well as the growth of roots and the flow processes in the soil, a 3D GPR tomography system with a spatial resolution of up to 5 cm and a temporal resolution of about 10 s was designed. The novel system consists of 39 multi-antenna tiles (MAT), each holding 64 antennas that can be used as transmitters and receivers. A MAT can be connected to the main module (MAM) in a star-shaped topology or to another MAT in a chain. In both configurations, the tiles are synchronized with an accuracy of about 25 ps. By this approach, the system is very versatile in terms of adjusting the amount and distribution of modules. Each tile contains its own data acquisition (DAQ) module, which is based on a RF-system-on-module (RFSoM). Each RFSoM includes DACs, ADCs, FPGA and CPU, such that the system internal analog path in between of the data generation, the antennas and the digitization is no longer than one meter. The antennas need to have a wide bandwidth for the use of Ricker pulses with a center frequency of 900 MHz and need to be optimized for our specific setup that includes a large amount of very close antennas. Therefore, we designed two-dimensional antennas with a shape we refer to as “circular bow-tie” and a size of 3 cm × 6 cm. Here, we present the system requirements and our derived system concept. The system is scalable in terms of reducing/extending the amount of antenna channels and DAQ modules. Due to the versatile DAQ hardware, the system also offers great flexibility in terms of adjusting the generated transmitter waveform and the signal processing.
How to cite: Mester, A., Bachner, M., Schardt, G., Chkhetia, R., Silex, W., Krenz, E., Rongen, H., Zimmermann, E., Klotzsche, A., and Natour, G.: Design of a Novel Scalable Multi-Channel GPR System for High-Resolution High-Speed Tomography of Soil Columns, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13206, https://doi.org/10.5194/egusphere-egu25-13206, 2025.
Traditional Ground Penetrating Radar (GPR) systems rely on antennae driven by the electric field component of the resonant electromagnetic waves they employ. While effective, these systems often suffer from bulkiness and limited adaptability in constrained environments. By contrast, antennae driven by the magnetic field component present several distinct advantages. These include a significantly more compact design, and a modest increase in operational bandwidth. To explore these benefits, we have developed and tested a compact ferromagnetic core antenna based GPR system. This prototype demonstrated comparable depth penetration and resolution to traditional electric antenna-based systems, but with a much smaller form factor, making it particularly well-suited for applications where space and weight constraints are critical.
The Undara Volcanic National Park in Northern Queensland, Australia, is home to one of the most extensive lava tube networks in the world, stretching over an estimated 160 kilometres. These tubes were formed by basaltic lava flows around 190,000 years ago, leaving behind vast subterranean passageways. We conducted field tests of our magnetic antenna based GPR system in a section of the Undara network, specifically at the Stephenson’s and Ewamian Caves. These caves, part of the lava tube system, are accessible via collapsed sections known as skylights, providing an ideal natural testbed for evaluating the system’s performance.
Accurate material property estimation is essential for understanding the lithology of surveyed areas, as properties like dielectric permittivity and electrical conductivity are directly influenced by a rock’s mineral composition, texture, and porosity. These properties can serve as proxies for broader lithological characteristics, offering valuable insights into subsurface geology. To expand the potential of GPR systems, we explored combining electric and magnetic field components from simulation data. This dual-component approach aims to uncover additional subsurface properties, enhancing the accuracy and detail of geological interpretations. Further, we are investigating how this combined methodology can be applied to real-world data, potentially revolutionizing subsurface exploration in both terrestrial and extraterrestrial environments.
How to cite: Auld, M., Macnae, J., and Iles, G.: Magnetic Antenna Ground Penetrating Radar Lava Tube Detection Use Case and Property Estimation., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2415, https://doi.org/10.5194/egusphere-egu25-2415, 2025.
This study optimizes in-hole electrical resistivity tomography (ERT) by integrating surface electrodes to assess directional resistivity variations through numerical simulations and field applications. The proposed methodology involves rotating surface electrodes around a borehole at various azimuths while keeping the in-hole electrodes stationary. Four in-hole imaging arrays—A-BMN, A-MNB, AB-MN, and AM-NB—are evaluated for their directional performance using synthetic azimuthal apparent resistivity datasets. The arrays are tested under two scenarios: the in-panel scenario, where subsurface anomalies align with the surface electrodes, and the off-panel scenario, where surface electrodes are positioned opposite the anomaly. The analysis considers array measurement sensitivities, modeling accuracy, anomaly detection resolution in the in-panel scenario, and the impact of symmetric sensitivity effects in the off-panel scenario. The results reveal that the A-BMN and A-MNB arrays exhibit high measurement sensitivity and moderate modeling accuracy, but symmetric effects significantly constrain their directional performance. In contrast, the AB-MN array shows low sensitivity, poor model accuracy, a pronounced symmetric effect, and limited directional response. The AM-NB array, however, demonstrates high measurement sensitivity, improved model accuracy, minimal symmetric effects, and robust directional capabilities. Field validation involved rotating surface electrodes to eight predefined azimuths around monitoring wells while keeping in-hole electrodes stationary. Following chemical injection at a nearby injection well, measurements revealed substantial resistivity and conductivity variations at azimuths corresponding to the injection well’s orientation. Rose diagrams of resistivity data identified dominant flow paths and primary contaminant dispersion azimuths. This optimized, directionally sensitive in-hole ERT approach significantly improves multi-directional detection capabilities, enabling effective characterization of anisotropic subsurface conditions. By incorporating rotating surface electrodes, the study establishes in-hole ERT as a reliable method for identifying fluid flow pathways and elongated subsurface anomalies, advancing its application in hydrogeological, environmental, and geotechnical investigations.
How to cite: Doyoro, Y. G., Lin, C.-P., and Wu, P.-L.: Optimization of Directionalized In-Hole Electrical Resistivity Tomography (ERT) and its Field Application , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14835, https://doi.org/10.5194/egusphere-egu25-14835, 2025.
How to cite: Ghadjari, H., Shahsavari, P., Dettmer, J., Gilbert, H., and Azizzadenesheli, K.: Nonlinear Electrical Resistivity Tomography with a Fourier Neural Operator Surrogate Model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6913, https://doi.org/10.5194/egusphere-egu25-6913, 2025.
Monitoring subsurface processes during soil remediation is crucial for optimizing environmental restoration techniques. Geophysical tools, such as Spectral Induced Polarization (SIP) and Time Domain Reflectometry (TDR), offer non-invasive methods for tracking these processes. This study focuses on the electrical monitoring of foam propagation in saturated porous media to enhance remediation strategies for hydrocarbon-polluted aquifers.
Aqueous foam, consisting of gas bubbles dispersed in a liquid phase containing surfactants, is widely used in soil remediation due to its high viscosity and ability to act as a blocking, mobilizing, or vectorizing agent. Understanding the electrical properties of foam propagation is essential for evaluating its effectiveness in remediation processes.
Our experiments were conducted in a 2D tank packed with 1 mm glass beads and saturated with tap water (400 µS/cm) Figure 1. The foam was generated using an anionic surfactant (SDS) and injected into the tank at a gas fraction (quality) of 85% and a constant flow rate of 8 mL/min. The SIP method was employed to measure complex electrical resistivity across frequencies ranging from 1.46 Hz to 187 Hz, while the TDR method was used to assess relative permittivity and electrical conductivity at this frequency of 70MHz. Additionally, image monitoring was utilized to convert optical densities into foam saturation values (Sf), providing a means to validate the geophysical measurements.
The results, (Figure 1, Figure 2), show that foam propagation causes significant changes in dielectric permittivity and resistivity in regions affected by foam injection. For the central zone, Probe 13, the dielectric permittivity decreases by 63% (from ~19 to ~7), while resistivity increases up to 6000% (~85 Ω.m to ~5100 Ω.m). In contrast, Near-Center zones, e.g. probe 12, show moderate changes (~33% permittivity decrease, ~120% resistivity increase). Probes in the edge zones, such as Probe 11, show no significant changes in permittivity or resistivity, as the foam propagation did not reach these areas. This lack of variation validates that foam impact is confined to the central and intermediate zones. The observed foam saturation from image analysis validates the geophysical measurements, with higher foam saturation (up to 90%) in the central zone correlating with greater electrical property changes. Additionally, we observe higher phase shifts in Probe 13, Figure 3. We are further analyzing the phase-frequency variation (1.46 Hz to 20 kHz) to better understand the polarization effects induced by foam.
These findings highlight the potential of SIP and TDR methods for monitoring foam flow in porous media and provide valuable insights into the complex interactions between foam and electrical properties. This study underscores the importance of integrating geophysical techniques with image-based analysis to improve the understanding and effectiveness of soil remediation processes.
How to cite: Shoker, A., Deparis, J., Kessouri, P., Maineult, A., Ahmadi-Sénichault, A., Holzhauer, J., Davarzani, D., Colombano, S., Leroy, P., and Lion, F.: Experimental Study of Electrical Monitoring of Foam Propagation in Porous Media: Spectral Induced Polarization (SIP) and Time Domain Reflectometry (TDR) Measurements in a 2D Tank, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13086, https://doi.org/10.5194/egusphere-egu25-13086, 2025.
Every dam site must have a complete stability assessment and seismic integrity evaluation under high ground vibration because aging, foundation deterioration, seepage phenomena, internal erosion, cavities, and cracks have resulted in dam damage. Often ERT technique and in-situ measurement in boreholes are used to monitor the state of the dam. In this project, we propose to use variety of seismic techniques both active and passive seismic combined with 3D ERT and spectral GPR measurements on the same profile.
In this study, compression and shear wave velocities were integrated to delineate elastic properties of the dam's materials and evaluate the seismic stability subjected to local soil stiffness and site response at the Rybnik dam and Orzepowice embankment, Poland. To asses those values we used seismic travel time tomography for general recognition of spatial differences, MASW technique to assess water infiltration and reflection seismic imaging to recognize the geological structures under the dam.
Here we present initial results and gathered data. We used standard standalone 3C seismic stations combined with Distributed Accousting Sensing (DAS). As sources both sledgehammer and industrial S wave source were used. This setup allows comparison of multicomponent data for both source types.
This research was funded by National Science Centre, Poland (NCN) project number 2022/45/B/ST10/00658.
How to cite: Roshdy, E., Majdański, M., Marciniak, A., Oryński, S., Popielski, P., Kowalczyk, S., Mieszkowski, R., Cader, J., Trześniowski, Z., Ostrzołek, I., and Długosz, S.: Preliminary results of earth dam monitoring using multiple geophysical imaging techniques, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6539, https://doi.org/10.5194/egusphere-egu25-6539, 2025.
Seismic refraction tomography (SRT) and surface wave analysis (SWA) are two geophysical methods frequently used in near-surface investigations. SRT provides models of the subsurface 2D/3D P-wave velocity distribution, whereas the classical SWA approach solves for the 1D or pseudo 2D S-wave velocity variation with depth. Optimized acquisition schemes allow for the joint collection of SRT and SWA data sets, improving data consistency and reducing resource requirements. Processing and inversion of the data sets are commonly carried out in separate workflows, and only the results are subjected to a joint interpretation. This can lead to inconsistencies between the resolved models, due to different intrinsic limitations, resolutions, as well as solution non-uniqueness of the inversion, potentially misleading the interpretation. Since both methods are sensitive to the properties of the soil or rock matrix, a suitable joint inversion scheme can exploit the existing synergies to improve the coherency and interpretation of the resolved subsurface models.
Accordingly, we developed a structural joint inversion (SJI) scheme and explore its application to SRT and SWA data. Structural similarity is established through the popular cross-gradient constraint to enhance the geometrical consistency between the resolved P-wave and S-wave velocity models. To solve for the pseudo 2D S-wave velocity structure from 1D SWA data, we incorporate lateral constraints to enforce spatial continuity and consistency between adjacent profiles. The SJI is realized using quadrilateral 2D grids with flat topography, because (1) SWA field data is typically collected over flat surfaces, allowing us to neglect topographical effects during data processing, and (2) model gradients and cross-gradient are computed based on finite differences. The SWA forward modeling and the SJI scheme are developed using the open-source library pyGIMLi (Rücker et al., 2017). As a first step, we conduct a numerical study to test the SJI on simple synthetic models with blocky piecewise-constant structures. Our investigations demonstrate that the SJI is superior to the individual inversion approach in delineating subsurface features and reconstructing true model properties. In a second step, we used seismic field data collected in a shallow aquifer, where an initial independent analysis revealed structural similarity between the SRT and SWA data sets. The effects of the cross-gradient constraint on the field data are less pronounced, but the resolved models correspond well to the local geology and a complementary electrical data set. Results obtained through our SJI scheme highlight the improved structural coherency between the resolved P- and S-wave velocity models, which is critical for the localization of subsurface units and the reliability of derived parameters (e.g., porosity) in near-surface investigations.
References: Rücker, C., Günther, T., Wagner, F.M., 2017. pyGIMLi: An open-source library for modelling and inversion in geophysics, Computers and Geosciences, 109, 106-123, doi: 10.1016/j.cageo.2017.07.011.
How to cite: Roser, N., Wagner, F., Steiner, M., and Flores Orozco, A.: Structural joint inversion of SRT and SWA data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6958, https://doi.org/10.5194/egusphere-egu25-6958, 2025.
S-wave reflection seismic imaging has emerged as a fundamental tool in near-surface geophysical investigations due to its superior resolution and increased sensitivity to lithological and geotechnical properties, compared to P-wave methods. These advantages make it particularly effective for resolving detailed subsurface structures, which are crucial for applied investigations in fields such as neotectonics and subrosion/karst, where accurate delineation of structural and stratigraphic features is essential. However, near-surface S-wave data acquisition and processing face numerous challenges, including complex wave-propagation, strong velocity contrasts, scattering, and noise contamination. These issues are further compounded by unconsolidated sediments, complex layering, and deformation features.
Advanced processing techniques are essential to overcome these obstacles, but when dealing with reflection seismic S-wave data, very often a simple, general processing sequence, e.g. involving classical NMO-correction, CMP stacking and post-stack FD time migration is applied, as described in, e.g., Krawczyk et al. (2012)1, Pugin et al. (2013)2 and Wadas et al. (2016)3. In the case of good data quality and a simple geology, these workflows might yield sufficient results, but in the case of poor data quality, in combination with a complex geological setting, more sophisticated processing sequences, such as DMO-correction, specialized filters, CRS analysis, pre-stack time/depth migration, and even full-waveform inversion, are required.
This study presents reflection seismic S-wave data from various locations in Germany that deal with different complex geological issues, i.e., neotectonics and subrosion/karst. The data were acquired using LIAG's electrodynamic micro-vibrator ELVIS (with a source spacing of 2 m or 4 m and a sweep frequency range of 20 Hz to 160/200 Hz) and a landstreamer equipped with horizontal geophones (receiver spacing of 1 m) in a roll-along configuration. Data quality varied significantly due to factors such as environmental noise, surface waves, scattering, and attenuation.
A comparison of results from conventional and advanced processing approaches of the S-wave data demonstrates the value of sophisticated imaging techniques in enhancing S-wave imaging for near-surface applications, and thus the structural and physical characterization of the underground.
1 doi:10.1016/j.jappgeo.2011.02.003
2 doi:10.3997/1365-2397.2013005
3 doi:10.5194/se-7-1491-2016
How to cite: Wadas, S. H.: Enhanced S-Wave Reflection Seismic Imaging for Near-Surface Applications - Overcoming Challenges in Complex Geological Settings with Advanced Processing Techniques, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3229, https://doi.org/10.5194/egusphere-egu25-3229, 2025.
Impact Echo (IE) is a commonly applied non-destructive testing (NDT) method in the field of civil engineering for the thickness measurement of concrete structures, which are only accessible from one side, as well as for the detection and localization of defects. When conducting measurements, a small mechanical impact is generated, and the resulting displacement is measured a couple of centimeters away from the impact point. The method measures the frequency of the zero-group-velocity S1 Lamb wave mode, which is directly correlated to the specimen’s thickness. Problems in data interpretation arise when lateral dimensions are not much larger than the specimen’s thickness. In such cases, so-called geometry effects mask the signals of the S1 Lamb wave. However, the physical cause for these geometry effects was not fully understood. This study presents a review on different numerical studies, which have been conducted to characterize these geometry effects and to minimize their influence for data evaluation. For the latter, time-frequency techniques like spectrograms or the continuous wavelet transform have been utilized for more accurate S1 frequency estimations. Also, the possibilities for the application of f-k-filters as well as array devices have been explored.
How to cite: Dethof, F. and Keßler, S.: Challenges for data evaluation and interpretation of Impact Echo data for non-destructive testing of concrete structures, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6213, https://doi.org/10.5194/egusphere-egu25-6213, 2025.
Ultrasonic imaging methods are widely used in non-destructive testing (NDT) and structural health monitoring (SHM) to ensure the safety of critical infrastructure. This work focuses on a methodology that combines Full Waveform Inversion (FWI) and Reverse Time Migration (RTM) techniques to improve the imaging of ultrasonic data and analysis of complex concrete structures. This approach allows a deeper understanding of the internal properties and heterogeneities within complex materials. The European project I am involved in, "USES of novel UltraSonic and Seismic Embedded Sensors for the non-destructive evaluation and structural health monitoring of infrastructure and human-built objects" (USES2) (www.uses2.eu), aims to integrate novel sensor technologies, advanced processing and innovative imaging to improve the monitoring of industrially relevant applications in sectors such as energy, mobility and construction.
Ultrasonic testing provides critical insight into the interior of concrete structures, including thickness measurement, geometry determination, localization of embedded components, and material quality assurance. However, the heterogeneous and multiphase nature of concrete poses challenges such as wave dispersion, scattering and attenuation, which make it difficult to detect small defects and internal features. FWI and RTM overcome these limitations by using the full ultrasonic wave field, unlike conventional approaches that use only a portion of the measured data. As a result, these techniques enable high-resolution recovery of material properties and detailed imaging of complex internal structures.
The first results of this work are presented here. Data sets were acquired using the A1040 MIRA 3D Pro ultrasound tomography system on polyamide and concrete specimens with drilled holes. The recorded ultrasonic wavefields were analyzed and compared with the modeling results. To ensure consistency between simulated and recorded wavefields, the source signature was recovered using multiple approaches and the dominant signature for FWI was identified. FWI-based finite-difference modeling was then applied to the ultrasound data to estimate elastic properties such as shear wave velocity and density distributions. This analysis provided valuable information for identifying internal inhomogeneities and served as an initial model for RTM.
The next phase of this research will extend the methodology to ultrasonic data collected from more complex samples and in-situ structures. Significant effort will be focused on refining the imaging resolution of ultrasonic data using RTM. The RTM algorithm has the potential to improve resolution in imaging concrete media, particularly in resolving steeply dipping interfaces and complex structures.
In summary, this methodology, which integrates advanced FWI and RTM approaches to ultrasonic data, offers new possibilities for the diagnosis and detection of heterogeneities and defects in concrete structures. It provides high-resolution and consistent images for NDT and SHM applications, addressing critical challenges in these fields.
How to cite: Suchkova, A. and Niederleithinger, E.: Waveform Inversion of Ultrasonic data – first synthetic and laboratory experiments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1544, https://doi.org/10.5194/egusphere-egu25-1544, 2025.
Carbonate reservoirs have been drawing the attention of the energy industry for decades. Quantitative information on carbonate rocks remains a challenge in exploration geophysics as these porous and fractured rocks are generally heterogeneous and anisotropic at differents scales. The interest in investigating such rocks spans many applications, for example, monitoring underground water resources and geological CO2 storage.
We aim to study carbonate rocks at the laboratory scale that can help with large-scale seismic interpretation. This is a promising experimental approach that could lead to significant progress in the development of imaging methods for the subsoil at different scales. We developed an automated experimental prototype involving a point-like pulsed-laser (PL) or a piezoelectric transducer (PZT) as seismic sources and a single-point Laser Doppler Vibrometer (LDV) as a receiver for efficient and high-resolution seismic data acquisitions on core samples. The MHz frequency-range seismic signals recorded by the LDV are used to study Vp inside the carbonate core slice through first-arrival travel-time tomography. The seismic tomographic images obtained from both the PL-LDV and the PZT-LDV datasets are compared with an X-ray CT-scan image of the carbonate core. In parallel, numerical tests on synthetic and decimated data are run to study the hyperparameters and the resolution of the tomography tool, which helped us to establish an optimal inversion strategy on real data involving a multi-grid approach. The tomography results are completed with a sensitivity analysis through spike tests.
Synthetic and spike tests have concluded that both the PL-LDV and PZT-LDV setups may correctly reconstruct the P-wave velocity, however, the tomographic Vp images from the experimental PL-LDV and PZT-LDV datasets are different even though they share some common trends and patterns. The X-ray CT-scan image shows that the Vp model retrieved from the PL-LDV dataset is in better agreement with the CT-scan image and confirms these trends and patterns in general.
We will discuss the reasons for which the two experimental results are different, with the help of tomography on both the experimental and numerical data after decimation. The point-like feature of the PL seismic source may have contributed greatly to the higher 2D tomography resolution, among other advantages of the PL source: it should have allowed to minimize the potential bias caused by 3D information.
Therefore, we validated an experimental prototype featuring a PZT source and a pulsed-laser source for high-resolution measurements in laboratory as well as a tomography workflow: we propose an original and efficient geophysical core-slice-probing configuration based on the PL-LDV set-up leading to a more accurate tomographic P-wave velocity reconstruction as compared to the PZT-LDV set-up.
How to cite: Shen, C., Brito, D., Diaz, J., Virieux, J., Garambois, S., and Bordes, C.: Tomography of a carbonate core with ultrasonic seismic sources and Laser-Doppler Vibrometer at the laboratory scale, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14127, https://doi.org/10.5194/egusphere-egu25-14127, 2025.
The iron-oxide mine of Blötberget in the Bergslagen mineral-endowed district in central Sweden has been the target of several geophysical studies in recent years. Among these studies, a series of seismic surveys aim to delineate the lateral and depth extent of the deposits for methodological and technological testing given the wealth of borehole data available for validation. The ore in Blötberget primarily comprises high-quality iron-oxides in the form of magnetite and hematite, partly enriched with apatite. The deposits occur in sheets, ranging from 10-50 m in thickness, with an approximately 45° eastward dip along an NNE-trending zone.
In June 2022, an additional seismic dataset was acquired to investigate the potential of distributed acoustic sensing (DAS) measurements in imaging the iron-oxide deposits. The use of DAS data presents several challenges, one of the most important being the directional sensitivity of the DAS cable. To date, there are only limited borehole and surface DAS applications for mineral exploration and in hardrock settings, and there is hence good potential to develop new how-to solutions for these purposes.
This study presents the seismic data generated by a vibrator truck and recorded by a 2200 m long straight fiber cable, deployed on the downdip of the mineralization. The cable was covered with gravel to improve its coupling to the ground. While complex, the results are promising, revealing distinct seismic signatures generated from the mineralization in specific data segments.
Acknowledgments
This work is partly sponsored by the Smart Exploration Research Center. The center has received funding from the Swedish Foundation for Strategic Research (SSF) agreement no. CMM22-0003. This is publication SE25-001.
How to cite: Gyger, L., Malehmir, A., Wilczynski, Z., Markovic, M., Mansi, M., Valishin, O., and Hamerslag, R.: Distributed acoustic sensing for mineral exploration: a pilot study from central Sweden, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3087, https://doi.org/10.5194/egusphere-egu25-3087, 2025.
Railway embankments, constructed in the 19th and early 20th centuries without modern engineering standards, are increasingly vulnerable to failure due to ageing, climate change, and rising transportation demands. Extreme weather events increasingly pose a risk to the resilience of these embankments, as prolonged wet and dry periods increase the risk of serviceability issues and progressive failure. Continuous monitoring and early intervention in earthworks are more cost-effective than addressing failures after they occur. This study explores the potential of Distributed Acoustic sensing (DAS) for long-term seismic monitoring of embankment slopes, capturing seasonal behaviour variations with high-resolution temporal and spatial data. Focused primarily on DAS, the study demonstrates its effectiveness in enabling frequent, distributed measurements along a 350m long fibre optic cable buried in the slope of a live railway embankment near London, UK. Four active seismic surveys were conducted along the fibre optic cable across different seasons. The findings highlight the sensitivity of DAS to changes in embankment condition throughout the monitoring period, emphasising its unique capability for continuous, detailed monitoring over time and space.
How to cite: Saqlain, M., Trafford, A., Harms, J., and Donohue, S.: The application of DAS for evaluating seasonal changes in seismic velocities of a railway embankment, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5056, https://doi.org/10.5194/egusphere-egu25-5056, 2025.
Distributed Acoustic Sensing (DAS) technology can convert unused fiber-optic cables of existing telecommunication networks (dark fibers) into arrays of virtual seismic receivers. Moreover, the seismic waves generated by human activities recorded on these receiver networks can be used to seismically image the urban subsurface at high resolution with a small footprint. This capability can help to evaluate the potential of the urban subsurface for safe and sustainable utilization in numerous applications, such as groundwater management and also geothermal development of an area. However, extracting coherent seismic signals from the complex urban seismic noise remains challenging due the uneven distribution of urban noise sources and often uncertain deployment conditions and resulting coupling of dark fiber.
We present an enhanced ambient noise interferometry workflow designed to identify and enhance coherent surface waves in complex DAS urban seismic noise data. The workflow is applied to urban seismic noise, predominantly generated by traffic, recorded on a dark fiber located along a major urban road in Berlin, Germany. Our workflow comprises a standard interferometric approach based on cross-correlations to retrieve coherent seismic phases for each hour of recording (Virtual Shot Gathers, VSGs), followed by Multichannel Analysis of Surface Waves (MASW) to derive 1D velocity models along consecutive and overlapping portions of the array. The individual 1D velocity models are then merged into a pseudo-2D velocity model of the subsurface. Our results are improved by incorporating a scheme to select VSGs using clustering driven by unsupervised machine-learning. This approach effectively excludes transient and localized noise sources while retaining high-quality VSGs. Additionally, a coherence-based enhancement technique is applied to stacked VSGs to improve their signal-to-noise ratio and, consequently, enhance the quality of the resultant dispersion curves. Ultimately, the resultant 1D velocity models achieve an increased investigation depth and their interfaces correspond well with available lithologic information from boreholes and models for Berlin. Our enhanced workflow yields more reliable results requiring less data than conventional processing schemes, thus fostering reduced acquisition costs and thereby more efficient investigations of the urban subsurface.
How to cite: Ehsaninezhad, L., Wollin, C., Rodríguez Tribaldos, V., and Krawczyk, C.: Improved subsurface imaging using urban ambient noise DAS recordings, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6367, https://doi.org/10.5194/egusphere-egu25-6367, 2025.
Carbon dioxide (CO2) capture and sequestration (CCS) is a key strategy in mitigating greenhouse gas emissions. CCS demands that the captured gas remains securely within the geological formation to prevent unintended migration or leakage. This necessitates continuous monitoring during and after injection to mitigate economic losses and potential damage to local ecosystems due to leaks. Among various monitoring techniques, seismic monitoring is recognized as one of the most effective methods for CCS projects globally. Moreover, the emerging carbon trading systems require precise quantification of CO2 migration. Early CCS projects have utilized seismic time-lapse analysis, examining temporal changes in seismic attributes. Techniques such as normal moveout velocity analysis or AVO (Amplitude Versus Offset) analysis were employed to qualitatively assess changes in subsurface parameters caused by CO2 injection through variations in amplitude and time shifts in specific horizons. However, these techniques suffer from the loss of pre-stack information, like angle and amplitude, which can compromise the accuracy of model-building outcomes. To improve the effectiveness of CCS monitoring, it's crucial to develop or refine methods that retain and leverage the full spectrum of seismic data, ensuring both safety and economic viability of these environmental initiatives.
Theoretically, the Reverse Time Migration (RTM) method can utilize all reflected and scattered waves for imaging, serving as an advanced technique for CO2 migration imaging. RTM employs Claerbout's imaging principle to locate subsurface reflectors by correlating the source-side forward-propagating wavefield with the receiver-side backward-propagating wavefield. From a rigorous theoretical perspective, imaging algorithms should apply the inverse operator of the forward operator to seismic data. However, the aforementioned imaging algorithm applies the adjoint operator (conjugate transpose) of the forward operator to seismic data, resulting in low resolution and unbalanced amplitude in the final imaging result. This abstract introduces a high-precision time-lapse seismic imaging method based on accurate two-way illumination compensation of the seismic source- and receiver-side wavefields. The proposed method extends the two-way illumination compensation RTM approach, developed for seismic exploration using a scattering integration algorithm (SI-RTM), into time-lapse mode for CO2 sequestration monitoring. The SI-RTM method accurately calculates the diagonal elements of the Hessian operator, allowing for better preconditioning of the final subsurface image, thereby improving amplitude preservation in the imaging outcomes. The proposed time-lapse SI-RTM method capitalizes on the advantages of SI-RTM by reducing the impact of acquisition geometry and alleviating the need for data consistency in the time-lapse imaging algorithm. Numerical experiments using the Kimberlina CO2 sequestration model demonstrate that the proposed time-lapse SI-RTM method enhances the image quality of deep CO2 reservoirs. It minimizes the impact of inconsistent acquisition geometry for different surveys and better reconstructs the subsurface changes caused by CO2 injection/migration, facilitating high-resolution monitoring of CO2 migration.
How to cite: Wang, J., Wu, F., Li, Q., and He, Y.: CO2 sequestration monitoring using a high-precision time-lapse reverse time migration method, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14659, https://doi.org/10.5194/egusphere-egu25-14659, 2025.
Sermeq Kujalleq in Kangia (SKK) in West Greenland is one of the fastest moving glaciers in the world, with a flow speed up to 30–40 meters per day, resulting in a large outflux of ice into the ocean. Our project investigates the dynamical behavior of SKK and its interaction with the surrounding slow-moving ice. To that aim, passive seismic and other geophysical field campaigns spanning the summer 2022 were conducted on the slow-moving ice, in the vicinity of the fast ice-stream.
In this study, we use continuous seismic field measurements combined with Global Navigation Satellite System(GNSS) measurements to investigate the summer subglacial processes of SKK over a three-month period. Seismic horizontal-to-vertical spectral ratios (HVSR) were used to capture subglacial changes, while GNSS receivers tracked surface velocities. At the end of June, we observed the appearance of a low-frequency resonance peak in the HVSR data that is present until the end of July. At the same time, our analysis revealed a ~20% speed-up in ice flow and ~8 cm of vertical uplift, coinciding with simulated elevated subglacial water pressures and water storage. Notably, the HVSR time series clearly detects the start of the melt season, marked by a shift from a coupled state, where the glacier is in contact with the bed, to a partially decoupled state characterized by inefficient subglacial drainage and reduced basal friction.
Numerical modeling based on elasticity equations further validated these observations, linking lower resonance frequencies with the decoupling process. This study highlights the potential of HVSR to detect rapid subglacial transitions from a coupled to a partially decoupled state. These findings also demonstrated that glaciated areas surrounding ice streams, though slow-moving, can exhibit fast-changing dynamics.
How to cite: van Ginkel, J., Wehrlé, A., Nap, A., Walter, F., Kneib-Walter, A., Rousseau, H., Jouvet, G., and Lüthi, M.: Seismic insights into the subglacial hydrology in the vicinity of Sermeq Kujalleq in Kangia, Greenland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8598, https://doi.org/10.5194/egusphere-egu25-8598, 2025.
Posters on site: Fri, 2 May, 08:30–10:15 | Hall X1
Anisotropic media are prevalent in many geological and physical scenarios, characterized by direction-dependent physical properties that pose challenges to conventional imaging techniques. Our numerical simulations demonstrate that electromagnetic waves exhibit waveform splitting in anisotropic media, leading to poor imaging results. To overcome this issue, we have developed a Reverse Time Migration (RTM) imaging algorithm specifically for anisotropic media. We compare the performance of the RTM algorithm in anisotropic media with that in isotropic media. The results show that our new algorithm effectively improves imaging quality in anisotropic media. It delineates geological boundaries more clearly, enhances the imaging of weak reflectors, and reduces artifacts caused by anisotropic effects. This research provides a valuable methodology for more accurate subsurface imaging in anisotropic geological environments, with potential applications in fields such as water-ice exploration, buried river-channel detection, and directional fracture identification.
How to cite: Yuan, Y., Hu, C., Xu, Z., Li, Z., and Zhu, P.: Migration Imaging Algorithm for Ground-Penetrating Radar in Anisotropic Media, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6760, https://doi.org/10.5194/egusphere-egu25-6760, 2025.
Ground Penetrating Radar (GPR) is a non-invasive soil investigation tool that uses electromagnetic waves to probe the subsurface and determine the distribution of the electrical permittivity and conductivity. Traditional systems use impulse radar, which transmits short duration waveforms. Advances in high frequency electronics, such as high sampling rate converters, allow greater flexibility in waveform design and signal processing. This work focuses on analysing impulse, stepped frequency continuous wave (SFCW) and chirp waveforms to improve the signal-to-noise ratio (SNR) and measurement speed of GPR systems. Impulse radars use high peak to average power ratio (PAPR) waveforms. To increase SNR for a given maximum voltage, multiple measurements are averaged (stacked). SFCW GPR systems offer higher average power, but require further processing due to “ringing” introduced after frequency to time conversion. In some cases, chirp waveforms have been successfully implemented in GPR systems. Both SFCW and chirp waveforms can be designed to have the desired frequency spectrum, reducing ringing in the reconstructed time domain signal. In a model-based approach, we compared a Ricker wavelet pulse with a center frequency of 600 MHz, an SFCW and a chirp signal with non-linear frequency modulation. The spectrum of the SFCW waveform was shaped by varying the duration of transmission (dwell time) of each frequency. The signals were fed through a gprMax-simulation with an on-ground GPR setup. The modelled soil consists of two homogeneous layers. The upper layer has a conductivity of 10 mS/m and a relative permittivity of 7, while the lower layer has a conductivity of 20 mS/m and a relative permittivity of 20. The boundary between the two layers is at a depth of 30 cm below the antennas. The received SFCW and chirp signals were finally transformed into time domain for comparison with the impulse signal. In the experiment described, chirp and SFCW techniques provide 10 dB increase in SNR in comparison to the impulse technique. The analysis confirms that shaping the spectrum by non-linear frequency modulation prior to transmission reduces ringing in the reconstructed time domain signals. For the described setup, switching from impulse to frequency modulated waveform based techniques is beneficial for systems requiring a high signal to noise ratio for a limited transmission voltage. The efficiency of the waveforms can be increased by using a variable transmission time that depends on the frequency. The choice between chirp and SFCW depends on hardware and measurement time requirements.
How to cite: Chkhetia, R., Mester, A., Zimmermann, E., and Natour, G.: Comparison of Impulse, Stepped-Frequency and Chirp Signals in Terms of Measurement Efficiency for Ground-Penetrating Radar Systems, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8473, https://doi.org/10.5194/egusphere-egu25-8473, 2025.
Geophysical imaging utilising the Ground Penetrating Radar (GPR) is a staple for observing the subsurface in high resolution. It produces images of the distribution of dielectric permittivity and electrical conductivity of the surveyed subsurface region. To produce these images, the data is supplied to an inversion algorithm. This algorithm iteratively improves the estimates of what the subsurface looks like. Each iteration is based on how close the response produced by the estimate is to the data.
To evaluate the response from estimate models, we require an efficient forward solver of the Maxwell's equations. It can be performed in time-domain, as very capably done via gprMax, or in frequency-domain. Working in frequency-domain allows for spectral analysis of subsurface response, choosing particular frequencies of interest, and unique parallelisation and inversion strategies. For wide-band antennas used in a GPR survey, we are developing an efficient frequency domain forward modelling code in 3D. Simulating in 3D allows us to account for the antenna's complete radiation pattern. Moreover, to account for the wide band data, the forward solver will be equipped with a custom meshing algorithm that creates separate meshes for different frequency ranges of the data spectrum. Care needs to be taken that adequate boundary conditions are implemented in the forward solver for accurate domain truncation.
We will present the capabilities and features of the forward solver with synthetic test cases. Supplying our forward engine to a suitable Full Waveform Inversion (FWI) strategy that maximises the adaptable meshing and frequency domain evaluations could result in high performance. The exact strategy for such an FWI will be defined and tested such that it leads to accurate and efficient reconstruction of the electrical subsurface properties.
How to cite: Singh, C. D., Rulff, P., and Slob, E.: Wide band frequency domain forward and inverse modelling code for GPR data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-492, https://doi.org/10.5194/egusphere-egu25-492, 2025.
Ground fissures are a unique urban geological hazard. In recent years, China's ground fissures have increasingly attracted international attention due to their extensive coverage, large scale, and significant harm. These fissures severely restrict urban planning and construction, hinder economic development, and pose threats to the safety and property of the population. High-resolution detection and analysis of the causes of ground fissures are crucial for urban planning and disaster prevention and mitigation. Ambient noise seismic surveys have the advantages of continuous ambient noise sources, low cost, and fast deployment. These advantages are good for urban exploration. Ground penetrating radar(GPR), with its capability for rapid, non-destructive ultra-shallow subsurface detection, can achieve high-resolution imaging of underground structures within tens of meters below the surface. This study combines Ambient noise seismic method and deep-penetrating GPR method to investigate ground fissures in Donggugang Village, Langfang City. The seismic and radar profiles were calibrated and interpreted using borehole data near the survey lines, revealing the distribution and extension of the ground fissures underground. Based on the seismic and radar detection results, an analysis of the mechanisms causing the fissures was conducted, suggesting that the formation of the ground fissures in the study area is due to the combined effects of secondary faults extending westward from the Haihe fault and changes in the groundwater level.
How to cite: Xiaoqiong, L.: Intergrating Application of Ambient noise seismic Technology and Deep-Penetrating Ground Penetrating Radar Technology in the Detection of Ground Fissures in Langfang City, Hebei, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1826, https://doi.org/10.5194/egusphere-egu25-1826, 2025.
Residues of industrial mining activities like rock waste, tailings, and stockpiles are amongst the largest human-made structures in both area and volume. In the case of tailings dams, the risk posed by failure is well documented and has led to the implementation of regulatory standards. As one of the measures to reduce potential harm to the environment and people, the Global Industry Standard on Tailings Managment (GISTM) implemented by UNEP in 2020 proposes the installation of "monitoring systems to manage risk at all phases of the facility lifecycle". This is one of the objectives of the EU-funded project MOSMIN (Multiscale observation services for mining-related deposits), which strives to develop holistic, full-site services for the geotechnical and environmental monitoring of mining-related deposits through the combination of Earth observation with in situ geophysical data. The integrated data sets should then be leveraged by using modern analysis approaches like machine-learning to characterize deformations and identify environmental hazards.
In this work, we present the in situ geophysical campaigns conducted to acquire passive seismic data at two tailings dam facilities both related to copper mining, namely the tailings storage facilities of the FQM Trident mine in Kalumbila, Zambia, and the Codelco Chuquicamata mine near Calama, Chile. Both installations combine conventional seismic sensors with the deployment of a fibre-optic sensing array over targeted tailing dam sectors, for the continuous recording of ambient seismic noise. The main goal of this approach will be to both characterise the internal structure of the dams underneath the fibre-optic array and to monitor subsurface processes at different scales, resolutions and depths of investigation. We aim to apply several seismological methods for structural and material property characterization, the investigation of temporal changes in seismic properties and the evaluation of material contrasts in the body of the tailings dam. Suitable methods are ambient noise tomography and horizontal over vertical spectral ratios (H/V). Details of both setups like instrument deployment, fiber cable and trajectory, the procedure and construction of the layout, as well as preliminary results will be discussed.
How to cite: Wollin, C., Rodriguez Tribaldos, V., Haberland, C., Ryberg, T., Trichandi, R., Krawczyk, C., and Kirsch, M.: Geophysical Monitoring of Mining-related Deposits in the MOSMIN Project, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19455, https://doi.org/10.5194/egusphere-egu25-19455, 2025.
Forward modelling of seismic wavefields is a cornerstone of geophysical studies, aiding in subsurface characterization and exploration. In this study, we introduce a Physics-Enhanced Deep Fourier-Attention Network (PE-DFAN) to simulate the forward process from physical property differences to wavefields, addressing the limitations of conventional neural networks in capturing complex wavefield patterns. Conventional neural networks often struggle to model the intricate spatial correlations inherent in wave propagation, resulting in a tendency to learn only the average field behaviour. To overcome this, we incorporate a Fourier attention layer that learns coordinate correlations effectively and expands input coordinates into a high-dimensional Fourier space. This design enhances the network's ability to represent fine-grained spatial variations. Furthermore, our model outperforms both standard neural networks and purely Fourier-feature-based networks in predictive accuracy. To ensure higher-order physical consistency, we introduce a frequency-domain-based acoustic equation as an additional constraint in the loss function. This physics-informed approach enforces adherence to acoustic equation principles, leading to improved alignment with theoretical expectations. Experimental results demonstrate that the PE-DFAN achieves superior performance in both accuracy and physical fidelity, marking a significant advancement in neural network-based seismic forward modelling. This work underscores the potential of combining advanced neural network architectures with physics-based constraints, paving the way for more precise and computationally efficient seismic modelling frameworks.
How to cite: Yang, Q., Kang, R., and Vega, F.: Physics-Enhanced Deep Fourier Network for Seismic Wave Forward Modelling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1830, https://doi.org/10.5194/egusphere-egu25-1830, 2025.
Shallow subsurface imaging of lithologies and structures is important for development and utilization of deep underground space. However, it is a challenging task for geologists and geophysicists in areas with dense buildings and high population. Compared with compressional wave reflection methods, shear waves generally have low frequencies and shorter wavelengths and can often provide higher lateral and vertical resolution for identification of small-scale subsurface features. To validate the shear wave reflection method to map subsurface structures and to help to build a 3D geological model in an area with few boreholes, a 3 km 2D SH wave seismic reflection profile was acquired in Shanghai, China, in October 2019. Additionally, vertical seismic profile (VSP) measurements were performed in a c. 152 m deep borehole about 120 m offset from the seismic profile. We report here on some results from the 2D survey and from the VSP measurements.
A 5 ton vibrator truck operated in S-wave mode with a sweeping frequency from 10 to 100 Hz and sweep length of 10 s was used as a source. An S-Land seismic recording system with 168 microelectromechanical systems (MEMS) were available for recording the SH wave seismic data. Out of these, 96 units were used to record at a sample rate of 0.5 ms and 3 s of data, and 72 units were rolled to the far end of the line during data acquisition. In total, 1032 receiver locations were occupied during acquisition and 304 source points, with 9 m source spacing, were activated along the survey line. VSP data were recorded with a GEODE seismic recording system and one 28-Hz 3C receiver over the depth interval 3 m to 152 m in the borehole. The data were spatially sampled at 1 m intervals and recorded at a sampling rate of 0.25 ms. The vibrator was activated at 4.5 m offset from the borehole.
Numerous continuous reflection horizons consistent with VSP data are observed in the c. upper 2 s after stacking and migration. A particularly strong reflection at 1.5 to 1.6 s likely originates from the bedrock, which was not penetrated by the borehole. Quaternary deposits consist of sand interlayered with clay that are also reflective in the upper 0.25 s, as well as a semi-continuous reflection with relatively low amplitude between 0.25 s to 1.5 s. The VSP was used to calibrate the seismic data and to improve the geological interpretation down to total drilled depth. The SH wave imaging extrapolated the imaging from the bottom of the borehole to bedrock. Our results not only provide high-resolution imaging of subsurface structures, but also show the potential of the method to help building 3D geological models for development and utilization of deep underground space.
How to cite: Wang, Z., Juhlin, C., Lü, Q., Liu, Z., and Si, Y.: Joint SH-wave seismic reflection and VSP imaging of shallow subsurface structure in an urban area, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4068, https://doi.org/10.5194/egusphere-egu25-4068, 2025.
The coastal zone, a critical interface between land and sea, is characterized by intense human activity and development, making it a key area for multidisciplinary research. However, achieving accurate shallow subsurface detection in these areas, including nearshore waters, remains challenging due to limitations in current exploration technologies and the distinct challenges of marine and land-based survey methods. This study tackles this issue by investigating the western coastline of Dong'ao Island, Zhuhai. A network of 22 node seismograph stations were deployed across varied coastal environments—hillside, beach, and seafloor—to systematically analyze seismic ambient noise characteristics in each setting. The research aims to enhance understanding of seismic noise in different coastal contexts, contributing to improved techniques for shallow subsurface detection in coastal zones. Key findings from the analysis can be summarized as follows:
- Submarine stations exhibit higher seismic ambient noise energy levels compared to their hillside and beach counterparts. Dominant frequency bands concentrate within the ranges of 2~10 s and 0.5~0.01 s. Sources of this noise are primarily attributed to mechanical disturbances originating from coastal and offshore maritime activities, alongside anthropogenic influences such as nearby human activities and road traffic. High-frequency seismic background noise greater than 1 Hz in the three environments is rich in information and balanced in signal, which meets the needs of shallow strata imaging in coastal zones.
- Employing F-K inversion techniques, a two-dimensional shear wave velocity profile was successfully generated for the study area, delineating the depth of the basement interface beneath the sedimentary layer. The viability of utilizing ambient noise for probing coastal zones was substantiated via comparison with results obtained from the horizontal-to-vertical spectral ratio (HVSR) method and corroborated by adjacent drilling data. This outcome underscores the potential of passive seismic methodologies for investigating complex coastal geophysical structures.
- To derive high-order mode dispersion curves characterized by energy concentration, comparative experiments were conducted with varying operational parameters for data acquisition. Subsequently, a joint inversion of both high-order and low-order modes was performed, yielding higher-resolution and more accurate velocity structure imaging results beneath the coastal zone.
- The successful acquisition of two-dimensional shallow shear wave velocity profiles in the western coastal zone of Dong'ao Island unequivocally validates the feasibility of employing passive source node seismograph exploration technology to eliminate blind spots in shallow strata exploration within coastal zones. This approach transcends the limitations imposed by traditional exploration techniques, achieving seamless integration of land-to-sea seismic exploration. It is anticipated that this research will furnish robust technical support for engineering projects and resource development initiatives in coastal regions.
This research was granted by the National Natural Science Foundation of China (No. 42106078) and the Guangzhou Science and Technology Plan Project (No. 2023A04J0243).
How to cite: Liu, S., Xu, X., Lin, J., and Wang, X.: Exploration of Coastal Zone Noise Characteristics and Shallow Stratigraphic Exploration Methods: A Case Study of Dong'ao Island in Zhuhai, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5112, https://doi.org/10.5194/egusphere-egu25-5112, 2025.
Karst environments pose significant challenges for geophysical exploration due to their considerable lateral and vertical heterogeneity. In Ireland, approximately 16% of public water supply is sourced from groundwater, and karstified limestones are regionally important aquifers. Evidence from drill logs, from mining and from exploration data indicate the presence of karst conduits at depths exceeding 100 metres. Imaging such deep resources has numerous practical applications, including enhancing water supply systems and identifying geothermal energy targets.
Previous near surface studies have shown that high-contrast features, such as water-filled caves, can trap seismic energy and generate durable resonant oscillations. Building on this, this study investigates the seismic detection of deep water-filled caves in limestone karst systems through their frequency characteristics, using synthetic seismic simulations.
We aim to define the unique seismic "resonant fingerprint" of these features within simulated seismic reflection data. Additionally, we analyze how seismic signatures are influenced by cave geometry, and water content. This work aims to advance the understanding of seismic methods for characterizing deep karst systems and their potential for groundwater resource management.
How to cite: bayat, S., Henry, T., and Bean, C. J.: Seismic Detection of Deep-Seated Karst Conduits: Defining Fingerprint Characteristics Using Synthetic Seismic Simulations & Exploring the Impact of Cave Geometry on Resonant Seismic Emissions., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5208, https://doi.org/10.5194/egusphere-egu25-5208, 2025.
Fiber-optic distributed acoustic sensing (DAS) has become a standard tool in borehole monitoring and earthquake seismology, with its applications expanding into other areas. Recent studies demonstrate the use of surface-DAS (S-DAS) arrays for reflection seismic imaging and both passive and active source surface-wave analysis and inversion. S-DAS offers high sensitivity in low frequencies and denser channel sampling than conventional geophone arrays. However, it also presents challenges of directional sensitivity along the fiber and difficult, nonuniform fiber-ground coupling. Understanding these challenges is crucial for the further development of S-DAS applications.
In June 2022, a seismic field campaign was conducted at a hardrock mineral exploration site in Blötberget, central Sweden. The campaign utilized a broadband vibroseis source with a 2-200 Hz linear sweep and diverse collocated receivers, including S-DAS, 3-component (3C) 10 Hz geophone arrays, and vertical component broadband MEMS accelerometers. The receivers were arranged in a 2D profile with 5 m receiver and source spacing, except for the 3C geophones, which were spaced at 10 m intervals. The approximately 2000 m long line was primarily deployed for active source reflection seismics, but seismic data were also recorded passively for ambient noise surface-wave analysis.
This study focuses on the fiber's directional sensitivity and the application of S-DAS for surface-wave analysis and inversion. We compare our results to the active-source 3C geophone data and the vertical accelerometer data (both active and passive). We attempt to quantify S-DAS's response compared to other recording systems and evaluate its applicability for retrieving dispersion curves of surface waves. Results suggest phase consistency between different arrays and an increased resolution of the surface-wave phase-shift array in S-DAS data.
Acknowledgements: This work is partly supported by the Smart Exploration Research Centre. The center has received funding from the Swedish Foundation for Strategic Research (SSF) under grant agreement no. CMM22-0003. This is publication SE25-002.
How to cite: Wilczynski, Z., Kaslilar, A., Malehmir, A., Juhlin, C., Gyger, L., Markovic, M., and Manzi, M.: Comparative analysis of surface-DAS and collocated 3-component geophones for surface-wave studies, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9579, https://doi.org/10.5194/egusphere-egu25-9579, 2025.
In this study, seismic data were acquired using the research vessel Tamhae 2 (KIGAM) to investigate the complex geological structures of the Pohang offshore area in the East Sea. The acquisition setup included a 900-meter streamer with a receiver spacing of 12.5 meters. The seismic source had a volume of 1,254 cubic inches, with a source spacing of 25 meters and an offset range from 75 to 975 meters. To accurately image complex subsurface geological structures, various seismic data processing techniques were applied. These techniques aim to remove different types of noise present in raw seismic data and effectively attenuate multiples. In this study, noise removal was achieved through methods such as low-cut filtering, static correction, trace editing, swell noise attenuation, and random noise attenuation to enhance the signal-to-noise ratio. Additionally, techniques like SRME (Surface-Related Multiple Elimination), SRWEMR (Surface-Related Wave Equation Multiple Removal), predictive deconvolution, broadband de-ghost filtering, and parabolic Radon filtering were employed to eliminate WB (water bottom) multiples, which otherwise impede stratigraphic interpretation. Finally, Kirchhoff time migration was used to image the complex subsurface structures. We confirmed that the signal processing techniques applied in this study effectively removed noise and WB (water bottom) multiples. Additionally, signal processing enabled us to derive a more accurate velocity model. Through the final stack section generated with this velocity model, we could confirm that the complex subsurface structures were well imaged.
How to cite: Son, W., Kim, B.-Y., Yoo, D., and Lee, G.-S.: Seismic Imaging of Complex Subsurface Structures in the Pohang Offshore Area Using Signal Processing Techniques, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14007, https://doi.org/10.5194/egusphere-egu25-14007, 2025.
Full-waveform inversion (FWI) is a nonlinear optimization technique that allows the extraction of subsurface property information from seismic data. In full-waveform inversion, low-frequency is essential for extracting long-wavelength features and appropriate subsurface properties. However, low-frequency in seismic data obtained in the field are often contaminated by various noises and are typically removed using high-pass filters. Low-frequency provides structural information necessary for constructing a background velocity model and are crucial in preventing full-waveform inversion results from converging to local minimum instead of the global minimum. Furthermore, the lack of low-frequency components in the data can lead to cycle skipping problems, which mostly causes the inaccurate retrieval of long-scale features. Various studies have been conducted to address the absence of low-frequency components in full-waveform inversion. Chen et al.(2019) extracted low-frequency information related to the long-wavelength components of the subsurface using the multiscale envelope of seismic data. Na et al.(2024) proposed an algorithm for low-frequency reconstruction based on recurrent neural networks. The proposed algorithm was shown to accurately reconstruct the low-frequency components of seismic data. In this study, full-waveform inversion was applied to the data with the reconstructed low-frequency. In numerical test, modified Overthrust model was utilized to generate the synthetic observed data. A Ricker wavelet with a dominant frequency of 8Hz was utilized as the source wavelet, and a Butterworth filter with a cutoff frequency of 8Hz were applied to generate data with removed low-frequency components. Finally the inversion results for both data with and without reconstructed low-frequency components were compared.
Acknowledgments
This research was supported by Korea Institute of Marine Science & Technology Promotion (KIMST) funded by the Ministry of Oceans and Fisheries, Korea (RS-2023-00259633).
How to cite: Na, D., Jeong, S., Shin, S., and Chung, W.: Application of full-waveform inversion to low-Frequency reconstruction algorithm, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14920, https://doi.org/10.5194/egusphere-egu25-14920, 2025.
In the case of applying magnetic exploration to detect underground man-made objects precisely, it is important to calculate magnetic responses analytically due to various shapes, such as one-dimensional line segments, 2D disk types, and 3D prismatic bodies. As part of these contributions, in this study, I derive the closed-form expressions of the magnetic field of one of 2D disk types, a rectangular disk. First, the gravitational potential due to a rectangular disk parallel to the x-y plane is defined by the two-dimensional surface integral. The vector gravity can be derived by differentiating the gravitational potential in each axial direction. The surface integrals that include the multiple square roots of the distance between observation points to the rectangular disk are required. Differentiating the vector gravity once more in each axial direction yields the gravity gradient tensor. For a causal body with constant magnetization, Poisson's relation is applied to convert the gravity gradient tensor to the magnetic field. The derived expressions of magnetic response are validated by comparing them with a three-dimensional rectangular prism with thin thickness. For the inclined rectangular disk, the magnetic fields are computed by transforming the observing coordinate system to the coordinate system affixed to the rectangular disk, and then the magnetic fields can be obtained by the inverse coordinate transformation.
How to cite: Rim, H.: Closed-form expressions of vector gravity and magnetic field due to a rectangular disk., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2301, https://doi.org/10.5194/egusphere-egu25-2301, 2025.
Groundwater resources are under increasing pressure from climate change and growing demands, making the application of advanced exploration methods crucial, especially in areas like northern Germany, where complex subsurface geology leads to significant challenges. This study integrates seismic reflection methods and Electrical Resistivity Tomography (ERT), employing constrained inversion with PyGIMLi, where seismic interfaces guide ERT to enhance subsurface imaging.
The study area is located in Hude, Lower Saxony, Germany, within the Oldenburg-East Frisia Water Board (OOWV) region. The subsurface geology predominantly consists of Plio-Pleistocene unconsolidated sediments. The Miocene sequence, characterized by widespread clayey and silty deposits, forms the aquifer base. During the Pliocene, the Baltic River System deposited a substantial succession of sands over the Miocene strata, followed by at least two Quaternary glaciations. These glaciations introduced glaciofluvial sediments, including thick sands and gravels interspersed with impermeable till layers and clay-rich units. Glacial processes also created channel structures infilled with cohesive sediments, such as the Lauenburger Clay, resulting in significant heterogeneity in hydraulic conductivity and petrophysical properties.
The Elsterian meltwater sand aquifer, located beneath the Lauenburger Clay, is a key groundwater-bearing unit with a significant thickness of approximately 60 meters. The variability in the thickness and distribution of the Lauenburger Clay, which acts as a confining layer, has been interpolated through geological modeling and further investigated with geophysical measurements. This complex geological framework, characterized by alternating permeable and impermeable layers and significant variability, emphasizes the value of non-invasive geophysical methods in reducing reliance on exploratory boreholes while effectively identifying aquifers and improving understanding of subsurface conditions.
We acquired two intersecting seismic profiles (N-S and W-E), using both P-wave and S-wave reflection techniques. The N-S P-wave profile (1,560 m) runs parallel to the Quaternary channel and covers two newly drilled exploratory boreholes, while the W-E profile (840 m) crosses the channel. Corresponding S-wave profiles (1,440 m N-S and 842 m W-E) provided higher-resolution images, particularly in shallower regions where P-wave data alone may lack sufficient detail. Vertical seismic profiling (VSP) was performed in the boreholes to refine velocity models. Complementary ERT profiles of 1,430 m (N-S) and 950 m (W-E) were acquired along the seismic lines using Wenner and dipole-dipole configurations.
The results highlight the advantages of combining seismic and ERT methods through constrained inversion, leading to enhanced imaging of the subsurface. This approach, guided by seismic interfaces, enables precise identification of geological formations, closely matching borehole lithological data. These findings demonstrate the potential of integrating seismic and ERT methods to optimize groundwater exploration, enabling more precise identification of aquifers and reducing the number of required exploratory wells, particularly in areas with complex geological conditions.
How to cite: Alaei, N., Buness, H., Günther, T., Eckardt, T., Scheihing, K., Beienz, J., and Gabriel, G.: Improving Groundwater Resource Mapping in Complex Geological Regions Using Constrained Inversion of Seismic and ERT Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13584, https://doi.org/10.5194/egusphere-egu25-13584, 2025.
Flood defense structures are becoming increasingly vulnerable to failure from escalating threats of climate change. This challenge is evident in the network of agricultural earthen dykes along the Bay of Fundy coastline in Atlantic Canada, which safeguard economically critical infrastructure in the region. Addressing these vulnerabilities requires assessment methods to guide engineering interventions ranging from rehabilitation to reconstruction. Non-invasive geophysical techniques, such as electrical resistivity imaging (ERI), are gaining prominence for assessing flood embankments. ERI can detect subsurface electrical resistivity anomalies that are potentially indicative of internal zones of weakness.
This study investigates the application of ERI in evaluating and guiding dyke rehabilitation strategies in the Upper Bay of Fundy. The objectives are to: 1) develop a rapid screening approach capable of imaging potential internal weak zones; 2) assess the effectiveness of ERI in identifying structural vulnerabilities; 3) examine the primary factors influencing resistivity variations, including grain size distribution and pore water salinity; and 4) evaluate the impact of tidal level fluctuations on ERI imaging. A series of geophysical field investigations were conducted at Shepody dykelands in southern New Brunswick, between 2022 and 2024. This included a shallow EM apparent conductivity mapping, 2D ERI and a time-lapse 3D ERI survey. The latter was carried out over a period of 3.5 hours during which time the megatidal Bay of Fundy rose about 3 m, advancing approximately 100 m over tidal mudflat and grassland before rising up against the side of the roughly 2.5 m high dykes. The increasing tide level was anticipated to influence resistivity measurements. The timelapse 3D ERI survey utilized a novel electrode array configuration to enhance sensitivity without severely compromising survey efficiency. Furthermore, complementary geotechnical data were collected in 2024 through Standard Penetration Tests (SPT) using a split spoon sampler. Laboratory analysis of the samples measured resistivity, grain size distribution and pore water conductivity.
The 2D ERI inversion results reveal significant subsurface resistivity anomalies within the dyke, highlighting localized zones of elevated conductivity within the dyke. The correlation of various laboratory measurements indicates a stronger relationship between soil resistivity and pore water conductivity than grain size distribution. We conclude that the increased conductivity observed by 2D ERI is primarily caused by the presence of highly conductive saline water that has intruded into the dyke in areas of higher hydraulic conductivity during high tide. Such regions could be at risk from seepage-induced internal erosion, piping, or other anomalous geotechnical conditions. Time-lapse 3D ERI inversion results demonstrated the real-time effects of tidal variations on resistivity profiles, providing insights into measurement deviations caused by tidal influences. These findings underscore the effectiveness of ERI in assessing coastal flood embankments by identifying critical regions within flood dykes that should be prioritized for monitoring or further sampling to determine their potential impact on structural integrity. The results of this study demonstrate the capability of ERI to provide valuable insights that can enhance the resiliency strategies of flood defense structures.
How to cite: Lelièvre, P., Mendoza, R., Butler, K., and Nasir, O.: Informing Flood Dyke Resiliency Strategies Through Electrical Resistivity Inversion: A Case Study from the Upper Bay of Fundy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12169, https://doi.org/10.5194/egusphere-egu25-12169, 2025.
The Electrical Resistivity Tomography (ERT), a method based on the differences in electrical response of different geological materials, has multiple applications in complementary fields such as Geology, Archeology and Paleontology. Examples of this application include the exploration and delimitation of buried anthropic structures or assessing the geometry of cave galleries.
The Baio cave site has yielded a restricted yet interesting fossil record on its surface providing interesting climatic information regarding the Middle-Upper Paleolithic transition. Additionally, despite its restricted length (< 30 m), the cave contains a rich paleontological sedimentary deposit of approximately 6 m predominantly composed of cave bears. Whether the current known extension of the cave represents the actual extension of the galleries, and/or whether additional caves are represented in the adjacent sectors of the Baio cave is an interesting matter due to their potential archaeo-palaeontological content and geological information towards understanding cave formation processes in this area. Thus, with the aim of gaining information on their possible orientation and location of new galleries/caves, a comprehensive and multifaceted multiscale study has been carried out on the basis of a detailed ERT investigation around the Baio cave supported by the characterization of the main orientation fracture networks on the local and regional scale.
The collected structural data consistently indicate the presence of four main fracture systems across all scales showing approximately the following trends: N020E, N060E, N105E and N160E. These preferred orientations are interpreted as longitudinal, transverse and oblique discontinuity surfaces associated to folding processes responsible for the main geological structures within the Basque Arc domain of the Basque-Cantabrian Basin. These orientations hold significant promise for locating new caves with potential archaeo-palaeontogical record, suggesting avenues for exploration. In fact, these measures are in complete accord with the trends of maximum anomalies recognized in the ERT profiles performed around the Baio cave (N020E, N065E and N107E and N160E directions), interpreted as partially or full air-filled galleries or cavities. These cavities, located at depths not exceeding 5 meters from the surface, might be considered as possible candidates in order to complete the archaeo-palaeontological research in progress.
How to cite: Martínez Torres, L. M., Puelles, P., Apraiz, A., Gómez-Olivencia, A., and Esteban, J. J.: Geophysical Exploration of Archaeo-palaeontological cave sites by Electrical Resistivity Tomography : A Case Study of Baio Cave, N Spain, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8661, https://doi.org/10.5194/egusphere-egu25-8661, 2025.
Electrical resistivity tomography (ERT) has been successfully applied in a wide range of fields, including geotechnical and environmental engineering. However, conventional measurement protocols often fall short under complex field conditions or when precise imaging is required. Comprehensive datasets, which provide the highest resolution, are better suited to capturing detailed subsurface information. Unfortunately, acquiring such datasets in practice is infeasible due to the vast number of required data points. The pseudo-pole-pole (pdPP) measurement strategy enables the acquisition of comprehensive datasets through superposition, eliminating the need for remote electrodes and allowing data quality evaluation using reconstructed normal and reciprocal datasets. However, noise accumulation during the superposition process can introduce significant errors in the reconstructed data, with differing impacts on normal and reciprocal data.
This study investigates noise accumulation in ERT data reconstructed from pdPP measurements. A linear error model was used to account for measurement errors and derive the error model for reconstructed data. Noise accumulation of different data types were analyzed based on a homogeneous model. Synthetic and field experiments further validated these findings, and practical considerations, such as the optimal placement of reference electrodes, were also explored. The results show that the derived error model can serve as a data filter and weighting tool during inversion to ensure reliable imaging. Reconstructed normal measurements generally exhibit better quality than reciprocal data. Quality control based on normal and reciprocal errors can selectively exclude data with minor errors while retaining data with larger errors. It is recommended to reconstruct normal-type comprehensive datasets from pdPP measurements, with reference electrodes placed approximately 1/5 of the survey line length from the first and last electrodes.
How to cite: Che, H., Hedblom, P., and Dahlin, T.: Improvements in the reconstruction of ERT data based on pseudo-pole-pole measurements, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8465, https://doi.org/10.5194/egusphere-egu25-8465, 2025.
Posters virtual: Mon, 28 Apr, 14:00–15:45 | vPoster spot 1
EGU25-20181 | Posters virtual | VPS21
Joint inversion of surface wave dispersion data derived from subarrays and two-station methodsMon, 28 Apr, 14:00–15:45 (CEST) | vP1.10
Ambient noise surface wave imaging has become a powerful tool for mapping subsurface velocity structures. Recent advancements in seismology, including the widespread deployment of high-density arrays such as nodal seismometers and Distributed Acoustic Sensing (DAS) systems, have facilitated the use of subarray-based methods for surface wave dispersion data extraction, such as phase-shift, F-K, and F-J methods. Alternatively, dispersion data can also be derived from two-station approaches, such as the FTAN method. However, integrating dispersion data extracted from subarrays and two-station methods remains challenging. In this study, we propose a joint inversion framework that combines these two types of surface wave dispersion data to achieve improved constraints on subsurface structures. We demonstrate its accuracy and practical applicability by conducting numerical experiments and applying the method to field data. The proposed approach introduces intrinsic spatial smoothing constraints. It effectively integrates subarray and two-station dispersion measurements, resulting in better imaging of subsurface shear-wave velocity structures compared to using either dataset alone. The versatility and potential of this method highlight its promising applications in a wide range of geophysical scenarios.
How to cite: Luo, S.: Joint inversion of surface wave dispersion data derived from subarrays and two-station methods, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20181, https://doi.org/10.5194/egusphere-egu25-20181, 2025.
EGU25-5528 | ECS | Posters virtual | VPS21
Research on mine electrical resistivity inversion method based on Deep Learning MethodMon, 28 Apr, 14:00–15:45 (CEST) | vP1.11
Coal seam floor water hazards, caused by stress changes resulting from coal mining, are a common type of mine water disaster, and their monitoring and prevention are critical for mine safety. The mine resistivity method, a geophysical exploration technique, is widely used for monitoring and detecting such water hazards due to its high sensitivity to water-bearing structures. In practical monitoring, it is necessary to rapidly and accurately invert apparent resistivity data. However, traditional linear inversion methods are prone to local optima, leading to biased results. In contrast, deep learning-based inversion methods utilize data mining to train networks, avoiding reliance on initial models and enabling fast computation of global optimal solutions.
This study constructs a multi-layer convolutional and skip-connected U-Net model to capture resistivity features at different scales. The model is trained and validated using synthetic data to evaluate its inversion accuracy and efficiency in monitoring coal seam floor water hazards. The results show that the U-Net-based inversion method can accurately identify low-resistivity anomalies associated with water hazards in the coal seam floor and quickly achieve the global optimal solution.
The method is further applied to the inversion of resistivity models with complex boundaries to simulate the impact of stress changes caused by coal mining on the formation of floor water hazards. The results demonstrate that this method is several times faster than traditional linear inversion methods, while maintaining high consistency with the actual model. Therefore, this inversion method provides an efficient new tool for monitoring coal seam floor water hazards and holds great promise for advancing technologies in mine water disaster prevention and geological exploration.
How to cite: Wang, H. and Hu, Y.: Research on mine electrical resistivity inversion method based on Deep Learning Method, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5528, https://doi.org/10.5194/egusphere-egu25-5528, 2025.
EGU25-18491 | ECS | Posters virtual | VPS21
Characterizing Sedimentary Facies of Meandering Paleochannel and Floodplain Deposits using Multi-Frequency Ground Penetrating Radar: A Case Study from the Western Part of Bengal BasinMon, 28 Apr, 14:00–15:45 (CEST) | vP1.18
The sedimentary architectures of paleo-river channels and their associated floodplains play a crucial role in shaping alluvial aquifers. Meandering point bars, known for their high permeability, enhance groundwater recharge, while floodplains serve as natural filters, regulating both the vertical and lateral movement of groundwater. Geophysical methods, particularly Ground Penetrating Radar (GPR), facilitate high-resolution imaging of subsurface features, allowing for detailed mapping of sedimentary structures and hydrogeological characteristics. This study focuses on a paleo-meandering point bar and its adjacent floodplain deposits within a heterogeneous alluvial aquifer in North 24 Parganas, West Bengal. Four GPR survey sites were analyzed, three along the meandering channel axis and one on the adjacent floodplain, using 200 MHz and 80 MHz antennas to capture subsurface features up to a depth of 20 meters. Six radar facies (RF) and three types of radar bounding surfaces (RS) including chute channels, lateral accretion surfaces, and erosional surfaces were identified, corresponding to various sedimentary lithofacies. Towards the meandering apex, the paleochannels displayed well-defined, continuous, and horizontal subparallel RF indicative of top silty clay deposits that increase in thickness. In contrast, wavy, inclined, sub-horizontal RF indicates channel sand deposits, which exhibit a decrease in thickness toward the meander apex. The GPR profiles of the floodplain revealed sub-horizontal laminated RF, typical of finer silt and clay deposits at greater depths. The comparison of RF and RS at different scales highlights distinct depositional patterns between meandering channel deposits and floodplain sediments. This study emphasizes the importance of integrating multi-frequency GPR data to interpret sedimentary processes in fluvial-sedimentary environments, providing valuable insights into the sedimentary architecture and hydrogeological properties of the paleo-meandering system.
How to cite: Dutta, A. D., Gogoi, H., Bose, O., Bhowmik, T., Sengupta, P., and Mukherjee, A.: Characterizing Sedimentary Facies of Meandering Paleochannel and Floodplain Deposits using Multi-Frequency Ground Penetrating Radar: A Case Study from the Western Part of Bengal Basin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18491, https://doi.org/10.5194/egusphere-egu25-18491, 2025.
