Towards the construction of a new magnetic map of Antarctica, we investigate the use of gradient-boosted equivalent sources to model data from aeromagnetic surveys. Airborne surveys have larger spacing between adjacent lines compared with along-line spacing. By using the equivalent source technique, gravity and magnetic data can be interpolated onto a regular grid at constant height. This method is particularly useful to prepare the data for further use, such as modelling crustal structures and geological interpretation. The equivalent source technique uses a finite layer of sources to generate the same field as the observed data. These sources are then used to predict the field in unobserved locations. However, estimating the source coefficients that best fit the observed data is computationally demanding. To overcome this problem, the source coefficients are estimated in overlapping windows and carried out iteratively, similar to the gradient boosting method used in machine learning. At each iteration, the sources are fit to the field residuals from the previous iteration. Here we apply the gradient-boosted equivalent sources method to interpolate total-field anomaly observations and convert them to the norm of the anomalous field. We use two layers of equivalent sources at different depths to fit both the regional field and the field due to the shallower sources. We demonstrate using synthetic surveys and an Antarctic magnetic dataset that our dual-layer gradient-boosted equivalent sources are able to produce grids of both the total-field anomaly and the norm of the anomalous field accurately and with a low computational cost.
How to cite: Uppal, I., Uieda, L., Oliveira Jr, V. C., and Holme, R.: Using a dual-layer gradient-boosted equivalent sources method to grid large magnetic datasets., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-455, https://doi.org/10.5194/egusphere-egu25-455, 2025.
Alternative navigation (AltNav) includes development of magnetic navigation (MagNav) using the Earth’s magnetic field as a reference. Current implementation requires highly accurate estimates of the full expected magnetic field along the predicted travel path. This is a challenging problem.
This presentation focuses on delivery of trustable estimates of the crustal magnetic anomaly as a component of the full field. In many operational situations (depending on altitude and speed), the variations of the crustal magnetic field represent the primary signal for use in MagNav.
One key challenge is the integration of original survey data into a comprehensive grid/model with accompanying estimation of the anomaly uncertainty. The required resolution and accuracy of this information will vary depending on navigational operation, but current MagNav implementations are dependent on highly accurate anomaly estimation. To meet this requirement, it is important to assess and optimize: (1) the quality and sampling of the original survey data; (2) the methods used to interpolate the survey data into a regular grid; and (3) the upward (or downward) continuation of the data (both for anomaly and directional gradient) to the required navigational position.
We report on methods developed for these 3 requirements using (1) FFT-based power spectrum analysis of initial survey sampling, (2) a new method for magnetic grid cell uncertainty estimation, and (3) experimentation with generalized equivalent source techniques for on-the-fly calculation of anomaly and directional gradient at selected locations.
How to cite: Saltus, R., Chulliat, A., and Balmes, A.: Magnetic Anomalies: Anywhere and Anytime – Accurate Information for Use in Alternative Navigation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12869, https://doi.org/10.5194/egusphere-egu25-12869, 2025.
Airborne magnetic surveys provide valuable insights into subsurface structures but often suffer from levelling errors due to inconsistencies between flight lines. These errors, such as striping patterns caused by sensor variations and magnetic field fluctuations, can obscure anomalies and distort interpretations. Traditional corrections like tie-line or micro levelling address these issues but rely on time and frequency domain analyses, making the process labor-intensive, costly, and reliant on expert intervention. Automating and enhancing these workflows is crucial for efficient and accurate levelling across large-scale airborne magnetic datasets. In this work, we propose a deep learning framework for levelling airborne magnetic data by leveraging a U-Net-based architecture. The model is trained in a supervised manner. We use a combination of perceptual loss and mean squared error (MSE) loss to capture fine-grained details while maintaining global consistency in the levelled data. Once trained, the proposed method demonstrates computational efficiency during inference, enabling automatic and robust levelling corrections for large datasets without requiring manual intervention or additional tie-line constraints. The model's performance was evaluated on an independent survey data from the Geological Survey of Brazil database, as well as on an out-of-distribution (OOD) dataset consisting of magnetic field data acquired by Geotech Limited, demonstrating its generalizability and robustness. Our approach demonstrates performance on par with traditional levelling methods, as validated by both quantitative and qualitative metrics, while introducing significant advantages in efficiency and automation. This deep learning-based solution simplifies the levelling process and provides a scalable, adaptive framework designed to meet the demands of modern geophysical surveys.
How to cite: Sanjeev, S., Geng, M., Sun, J., Abughazal, S., Yang, Q., and Vega, F.: Deep learning-based approach to Levelling Airborne Magnetic Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2997, https://doi.org/10.5194/egusphere-egu25-2997, 2025.
The magnetic field from Earth's crust helps us understand its thermal structure by finding the depth to the bottom of magnetic sources, an essential indicator of the crustal thermal properties. This study aims to estimate the depth to the bottom of magnetic sources precisely using the magnetic field. Traditional methods, like the spectral peak and centroid techniques, are commonly used to estimate the depth to the bottom of magnetic sources. However, these methods typically require prior knowledge about the magnetization source, derived from empirical relationships of wave-vectors in the spectral domain, which is challenging to obtain over large regions. We devised an innovative deep-learning approach utilizing a convolutional neural network to directly estimate the depth to the bottom of the magnetic sources, eliminating the need for prior knowledge of the fractal magnetization source. Synthetic fractal magnetizations were constructed to train the model, and the performance of the convolutional neural network was compared to the modified centroid approach. Our convolutional neural network methodology was confirmed by utilizing a diverse range of realistic synthetic fractal magnetization, incorporating various window widths and depths to the bottom of the magnetization source. The model is applied to the high-resolution aeromagnetic data of the southern Indian shield to understand the crustal-scale thermal structure.
How to cite: Roy, A., Naga Durga Prasad, K., Sharma, R. K., Vijayakumar, D., and Kumar, R.: A Convolutional Neural Network-Based Estimation of Depth to the Bottom of Magnetic Sources from Aeromagnetic Data and Its Applications in Southern Peninsular India, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-206, https://doi.org/10.5194/egusphere-egu25-206, 2025.
One of the most interesting properties of the gravity fields generated by ideal sources (e.g., sphere, dyke, sill and contact)is that they are homogeneous functions of integer degree n, ranging from -2 to 1. It is to say that they satisfy the homogeneity equation in the harmonic region. However, when the source distribution is more complex than that of ideal sources, fields are not homogeneous. When analyzed at different distances, these fields will have different homogeneity degrees which can assume also a fractional and distance-dependent value. This results in the multi-homogeneity law which accounts for n varying at each observation site.
Accordingly, we may introduce the multi-homogeneity theory into the Depth From Extreme Points (DEXP) method. DEXP is an imaging method, which is based on field transformations, not involving any inverse matrix, so being faster and simpler to use. An important role in the scaling of the modelled field is played by the exponent N, the structural index. N is a parameter characterizing the type of source and is directly related to n as N=-n+q with q being the differentiation order of the Newtonian potential.
The proposed DEXP transformation for general sources is based on the multi-homogeneity theory so that the field is scaled by the inhomogeneous exponent N (x,y,z).
DEXP imaging of synthetic and real data demonstrated the ability to interpret complex bodies geometries which are brought by the DEXP method with the multi-homogeneity theory.
How to cite: Bianco, L. and Fedi, M.: DEXP imaging of potential fields with multi-homogeneity theory, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16540, https://doi.org/10.5194/egusphere-egu25-16540, 2025.
The geological analysis of rift-sag structures is of significant importance for understanding crustal tectonic evolution, resource exploration, and seismic activity. However, due to the non-uniqueness of gravity and magnetic data inversion and differences in resolution, a single geophysical method often fails to comprehensively reveal the structural characteristics of complex geological bodies. In this study, we propose an optimized gravity-magnetic cross-gradient joint inversion method, introducing several improvements to the weight calculation process. The model weighting matrix and structural constraint weighting matrix are normalized to simplify the calculation formulas, unify the magnitude of the two matrices, and narrow the range for selecting the weighting factors of the cross-gradient term. Furthermore, a dynamic adjustment mechanism for the cross-term weighting factor is adopted, allowing adaptive parameter adjustment based on the variation of model errors, data fitting, and inversion results during the inversion process. This dynamic parameter optimization enhances the inversion results and achieves real-time correction of parameter values, avoiding the limitations of fixed parameters and improving the reliability of the inversion.
The proposed method was applied to measured gravity and magnetic profiles in the southern margin of the Sichuan Basin. By integrating planar gravity and magnetic anomaly characteristics with vertical boundary identification techniques, the gravity field, magnetic field, structural features, deep characteristics, and sedimentary features of the rift-sag structure were systematically analyzed. The results provide reliable evidence for delineating the spatial distribution of rift-sag boundaries and the internal geological features, offering robust support for geological research and geophysical interpretations in complex tectonic environments.
Acknowledgments: This research was funded by the National Natural Science Foundation of China [grant numbers: 42104092], Fundamental Research Funds Program of Chinese Academy of Geological Sciences [grant numbers: JKYQN202351].
How to cite: Xu, M., Yang, Y., Su, Z., Feng, C., Wang, H., and Meng, L.: Optimized Gravity-Magnetic Cross-Gradient Joint Inversion for Characterizing Rift-Sag Geological Structures, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7867, https://doi.org/10.5194/egusphere-egu25-7867, 2025.
Potential field geophysical data are frequently used to image geological features in volcanic systems/areas (faults, lithological contacts, alteration zones, geothermal systems, magmatic reservoirs). However, although crucial, it can prove challenging to accurately simulate data in such regions due to the major influence of strong topographic variations. To accurately account for topography with reasonable computational cost, we develop a numerical tool for the modeling and inversion of these data. The method consists of a numerical integration scheme of the integral equations predicting gravity and magnetic data on deformable hexahedral elements. The integrals are evaluated using high-order Gaussian quadrature. Physical properties of the subsurface are defined on discrete grid points, allowing to model discontinuities in the parameters not only at the surface, but also along surfaces within the models, enabling to represent faults, lithological contacts or cavities. Our method uses non-conformal meshes with automatic local refinements in regions with rapidly varying surface topography and in the vicinity of measurement points. In particular, we have developed a local and self-adaptive iterative refinement scheme based on a local convergence criterion of the numerical integration, allowing to reduce the effect of solution singularities close to observation points. The accuracy of our method is tested by comparing our model predictions with results obtained from the tomofast code (https://doi.org/10.5194/gmd-17-2325-2024) using a fine reference discretization of the topography with rectangular prisms. These tests were performed for the modeling of the gravity and magnetic effects of topography over the geothermal system of Krafla, Iceland for the case of ground-based and airborne data. Our modeling tool will ultimately be used for the independent or joint inversion of potential field data to make use of their different sensitivities in terms of physical parameters and also lateral and depth resolutions.
How to cite: Bellounis, L., Bouligand, C., Brossier, R., Métivier, L., and Garambois, S.: A new numerical tool for the 3D forward modeling of potential field geophysical data in the presence of rugged topography using a numerical integration scheme, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1139, https://doi.org/10.5194/egusphere-egu25-1139, 2025.
A high-resolution aeromagnetic survey using a drone was conducted in June 2024 over the Tajogaite volcano on La Palma, Canary Islands. This survey aims to characterise thermal anomalies associated with magma intrusion and the related fault system.
The drone was equipped with a fluxgate magnetometer operating at a sampling rate of 200 Hz, with two sensors separated by 1 m. The constant altitude flights covered approximately a 2.5 km x 2.5 km area, with N-S lines spaced 30–60 m apart. The survey also included tie lines for quality control and calibration flights at very high altitude (low magnetic gradient) to account for the effects of drone pitch, roll, and yaw on magnetic measurements.
Data preprocessing included deriving the total magnetic field from its components, cleaning flight tracks, and compensating for drone-related influences using calibration data. A low-pass filter removed high-frequency noise from the drone’s electronics, and data from both sensors were averaged. Data from all flights were merged and interpolated using linear triangulation onto a 20 m grid with Gaussian smoothing. Diurnal corrections were considered unnecessary due to short flight durations and minimal diurnal variations at low latitudes. Magnetic anomalies were calculated by subtracting the median value from the processed magnetic map.
The new magnetic anomaly map provided critical insights into the thermal and structural characteristics of the volcanic system. This study is part of the GEOTHERPAL project, further detailed at http://pc213fis.fis.ucm.es/GEOTHERPAL/index.html.
How to cite: Romero-Toribio, M. C., Martín-Hernández, F., and Ledo, J.: High-resolution aeromagnetic survey over the Tajogaite Volcano, La Palma, Canary Islands, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6049, https://doi.org/10.5194/egusphere-egu25-6049, 2025.
Antarctic geothermal heat flux (GHF) is poorly known restricting our ability to assess its influence on subglacial hydrology and ice sheet dynamics. Within the 4D Antarctica and the 3D Earth ESA projects, a new Antarctic aeromagnetic anomaly compilation, conformed at long wavelengths with SWARM satellite magnetic data was complied. All the datasets were levelled, microlevelled and stitched together. We also differentially continued all survey data to 4 km and re-gridded the compilation onto a 4 km grid mesh.
Our new aeromagnetic anomaly compilation enables us to re-assess Antarctic geothermal heat flux (GHF) heterogeneity, a critical basal boundary condition that influences Antarctic ice sheet flow and subglacial melting and hydrology. To estimate GHF we applied Curie Depth Point (CDP) estimation using the centroid, modified centroid and fractal/defractal approaches. We compared our CDP results with independent constraints on crustal and lithosphere thickness derived from seismological, airborne gravity and satellite gravity modelling and effective elastic thickness estimates. We also considered empirical estimates of GHF derived from seismology and recent models of intracrustal heat production from gravity inversion to assess additional uncertainties associated with CDP to GHF conversion. We performed both automated continental scale estimates and nested manual analysis of CDP and GHF with a specific focus on different Antarctic subglacial lake districts.
We found elevated GHF in the West Antarctic Rift System (WARS) beneath the rapidly changing Thwaites (THW) and Pine Island sectors of the West Antarctic Ice Sheet (WAIS) and along the edge of the Marie Byrd Land block. Focussed estimates of GHF were performed over the cascading active lakes beneath THW to provide new constraints for hydrological modelling in this critical sector of the WAIS. We image a large degree of heterogeneity in thermal basal boundary conditions beneath the active subglacial lake districts that underlie the ice streams flowing into the Ross Sea Embayment, which we relate to hitherto poorly known tectono-magmatic segmentation of the WARS.
In East Antarctica, elevated GHF is associated with some of the active lakes underlying the Byrd glacier catchment, but relatively lower GHF values are typical of both the active and static lakes of the northern Wilkes Subglacial Basin (WSB). This suggests limited upper crustal extension beneath this enigmatic subglacial basin compared to major Mesozoic to Cenozoic extension in the WARS. These findings agree with current seismological evidence for well-preserved fast and cold craton margin lithosphere beneath most of the WSB.
We image relatively elevated GHF beneath the Dome C and Dome A subglacial lake districts. This may be caused by cryptic but large-scale provinces of high heat producing Precambrian basement or could reflect major intraplate reactivation of Precambrian fault systems. Elevated GHF is also imaged in Dronning Maud Land and stretching from Enderby Land to Princess Elizabeth Land. We propose that this could reflect Cambrian age lithosphere thinning due to orogenic collapse processes that affected major and yet still cryptic paths of Gondwana-forming orogenic belts fringing East Antarctica. Additionally, Jurassic to Cretaceous thinning was likely superimposed and associated with passive margin formation during Gondwana break-up.
How to cite: Ferraccioli, F., Latorraca, P., Ooi, S. Q., Ford, J., Mather, B., Armadillo, E., Ebbing, J., Eagles, G., Gohl, K., Forsberg, R., Green, C., Fullea, J., and Verdoya, M.: Contrasting geothermal heat flux provinces unveiled beneath Antarctic subglacial lake districts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19366, https://doi.org/10.5194/egusphere-egu25-19366, 2025.
The FIQUgS project represents a transformative step forward in geophysical research, combining cutting-edge quantum gravity sensing technology with advanced software tools to enhance subsurface exploration. A landmark demonstration of these capabilities occurred in October 2024 in Lisbon, Portugal, during a collaborative archaeological study with the Centro de Arqueologia de Lisboa. This case study aimed to detect and characterize shallow tunnels and cavities from the Roman era beneath Lisbon’s historic center, leveraging the Differential Quantum Gravimeter (DQG) and a suite of sophisticated data processing software. The work presented here aims to enter into the details of data processing from the preliminary stage of survey planning to the post processing inversion and interpretation of data.
Central to this first real outdoor application of the DQG, was the FIQUgS survey planning tool, which used statistical inference to optimize survey paths and observation point spacing. This tool minimized data acquisition efforts while maximizing the sensitivity of detection capabilities. Post-survey, the collected data underwent extensive processing using FIQUgS-developed algorithms designed to refine gravity anomaly and vertical gravity gradient measurements. The vertical gravity gradient measurements proved particularly advantageous, significantly reducing the impact of distant mass effects and environmental noise, thereby enhancing the clarity of subsurface features.
An integral part of the data analysis was the automated inversion module, which used the processed measurements to reconstruct the geometry of subsurface structures. The module successfully identified and modeled a Roman-era tunnel with an estimated cross-sectional area of approximately 5 square meters. By integrating additional geophysical data, such as digital terrain models, the inversion tool further improved the accuracy of the subsurface density distribution.
This case study highlights the practical value of FIQUgS software innovations in real-world applications. The seamless integration of advanced survey planning, data processing, and inversion tools allowed for a comprehensive analysis of complex subsurface conditions. The success of the Lisbon study underscores the potential of quantum gravity sensors and associated software to address long-standing challenges in geophysical research and archaeological exploration. As the FIQUgS project continues to develop, these technologies promise broader applicability in areas such as mineral exploration, groundwater management, and structural monitoring.
This achievement demonstrates the synergy between hardware and software in advancing geophysical methodologies, paving the way for more efficient and precise subsurface investigations across diverse scientific and industrial domains.
How to cite: Sampietro, D., Capponi, M., and Janvier, C.: FIQUgS Innovations in Quantum Gravity Sensing: Data Processing for an Archeological Case Study, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16898, https://doi.org/10.5194/egusphere-egu25-16898, 2025.
Posters on site: Wed, 30 Apr, 14:00–15:45 | Hall X3
The province of Quebec (Canada) is regarded as the principal mining Province of Canada due to its substantial exploitable reserves and the significant contribution of its mineral production to the national GDP. Nevertheless, Vast areas, such as northern Quebec, remain insufficiently covered in terms of geoscientific data, limiting the understanding of their mineral exploration potential.
Aeromagnetic data are widely employed for large-scale reconnaissance to map geological structures and guide geologists in identifying exploration targets or defining new prospects. However, the only data that covers the entire area are low-resolution aeromagnetic data, with high-resolution datasets being sporadically available. This low resolution restricts the interpretability of regional data, as certain geological structures remain hidden by coarse sampling intervals. To enhance geological mapping, it is imperative to improve the resolution of aeromagnetic data to reveal structures such as faults, lineaments, and lithological boundaries that are otherwise undetectable in low-resolution geophysical signatures. While acquiring high-resolution data is an ideal solution, the high costs and vast territorial coverage required render this approach challenging in the short term. As an alternative, the advent of artificial intelligence (AI), particularly deep learning, offers promising avenues for exploration. In this study, we adapted and retrained 4 super-resolution deep learning algorithms to generate high resolution aeromagnetic maps from low resolution ones. To avoid bias due to spatial correlation, we split the data sets into a training set covering the southern part of Québec and validation being the Northern part. Each of the AI codes were trained on the same datasets leading to optimal hyperparameters for each algorithm. The AI-generated results for all the 4 algorithms successfully reconstruct high-resolution regional aeromagnetic maps in the training sets compared to measured high resolution data providing reliable high resolution maps for geological mapping. Finally, we generated four high resolution aeromagnetic maps for entire Province including the northern part. This innovative approach holds the potential to revolutionize geophysical exploration, facilitating the discovery of untapped natural resources in underexplored areas
How to cite: Penda biondokin, E., Bavandsavadkoohi, M., Tirdad, S., and Gloaguen, E.: Training Super-Resolution deep learning algorithms for high resolution aeromagnetic maps generation from low resolution aeromagnetic maps., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20682, https://doi.org/10.5194/egusphere-egu25-20682, 2025.
This study wants to show how a Convolutional Neural Network may be trained by models built on a simple but strong a priori information—in this case, the gravitational field of a fault—can allow a good reconstruction of complex 3D structures. The key innovation is to train the algorithm with elementary source models. These elementary blocks consist of fault models with varying parameters such as dip, density contrast, thickness, and depth to the top. For each anomaly, profiles are extracted from the anomaly map, subdivided into two sub-profiles, and interpreted using the fault-based ML algorithm. This workflow follows the idea that gravimetric anomalies, when analysed along a profile crossing the source, can be seen as composed by the constructive interference of anomalies generated by the edges of the source bodies reducible to faults. The interpreted sections are then interpolated to create a reference 3D model, which yields a strong information, as a reference model, for a final 3D inversion process, which refines the model and yields a good data-misfit.
To validate the method, we applied it to two different cases: a synthetic diapir-shaped source and a real geological structure, the Caltanissetta basin in Sicily (Italy). In both cases, the method successfully reconstructed the different structures.
How to cite: Messina, C., Bianco, L., and Fedi, M.: Training a CNN network with powerful but simple models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16657, https://doi.org/10.5194/egusphere-egu25-16657, 2025.
This study aims to analyze the deep structure and depression of the thick sedimentary layers to better understand the
geometry and hydrogeology of the aquifers in the Essaouira basin which have been processed through various filters and
transformations. The residual map provides valuable information on density variation, the observed anomalies in the study
area interpreted in term of the topography of the basement, the present of salt deposit and the thickness variation of the
sedimentary series. The seismic reflection profiles covering a limited area in the central-western part of the basin confirm the
gravimetry results and shows that the basin's structure is characterized by a series of anticlines and synclines., resulting from
the combined influences of Atlas tectonics and diapirism. As a result, the shallow aquifer system is broken up into blocks
lifted and collapsed by faults. The result is discontinuous groundwater flow and variable hydrodynamic distribution.
Based on the gravity data processing the principal deep parts of the basin were delineated, including their probable
interconnections-oriented N-S and NNE-SSW. As well, major density contacts (faults) were derived from the enhanced total
horizontal gravity gradient. Their prevailing direction in the central and northern parts of the basin is also N-S and NNE-
SSW; however, it is rather E-W in the southern side. Not all these gravity-based structural-tectonic features match with
geologically mapped faults of NE-SW and NNW-SSE orientation.
The compiled data allowed us to create a structural map that reveals a compartmentalized aquifer system with clearly defined
sub-basins. Additionally, the faults within the Essaouira basin have been precisely mapped. Their predominantly NNE-SSW
orientation suggests a connection to the Triassic rifting of the Atlantic Ocean. It also reveals that the Essaouira basin was
structured in the Triassic and Jurassic periods by a series of deep faults trending in three main directions: NNE-SSW, N-S and
E-W. These results will be invaluable for future oil exploration and hydrogeological research.
How to cite: Zbiri, A., Kchikach, A., Jaffal, M., Guernouche, M., Charbaoui, A., and Jaouad, G.: Contribution of the Combined Analysis of Gravity and Seismic Data in the Study of the Main Hydrogeological Prospects of the Essaouira Basin (Morocco), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2553, https://doi.org/10.5194/egusphere-egu25-2553, 2025.
The Lake Hazar pull-apart basin, situated along the East Anatolian Fault System, represents a key tectonic structure within one of Turkey's most active seismic zones. This fault system recently generated two catastrophic M7.0+ earthquakes in February 2023, underscoring the importance of understanding its associated geological features. Gravity modeling offers a powerful tool for exploring such basins, providing insights into subsurface geometry and tectonic processes.
This study employs vertical prismatic polyhedra to model the basin. Conventional modelling methods often require a trade-off between computational efficiency and data resolution, either overloading calculations with unnecessary prisms or losing critical detail with coarse sampling. By integrating Voronoi diagrams into the modeling process, we achieve sensitivity to data sampling frequency while maintaining computational efficiency and preserving accuracy.
Approximately 600 newly collected gravity data points from the Sivrice and Gezin provinces were used to construct the two-layer models. Forward modeling with a constant density contrast yielded basin geometries to a maximum depth of 350 meters, achieving root-mean-square errors below 0.1 mGals. Beyond refining the 3D basin structure, this method allowed us to estimate excess mass within different sections, providing additional constraints on sedimentary characteristics and tectonic activity in the region.
Comparison with our previous 2D-to-quasi-3D Talwani models revealed consistent results, including similar sediment thickness variations. However, the vertical prismatic polyhedra method demonstrated superior adaptability to irregularly spaced data and greater computational efficiency, making it especially suitable for complex tectonic environments like the Lake Hazar region. The integration of computationally efficient methods highlights the potential for future applications in similar tectonic settings, advancing our ability to investigate fault-controlled basins in active seismic regions.
How to cite: Aydın, N. G. and İşseven, T.: Exploring the Lake Hazar (Elazığ-Turkey) Basin Geometry with Vertical Prismatic Polyhedra, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9345, https://doi.org/10.5194/egusphere-egu25-9345, 2025.
The continuous advancement of geophysical modeling tools has been pivotal in elucidating the complexities of Earth's lithospheric structures. The latest developments in the software package IGMAS+ have introduced innovative techniques for 3D and 4D gravity and magnetic field modeling, combining interactive user control with cutting-edge optimization algorithms. Among these advancements are the integration of space-warping concepts and the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), which provide enhanced precision in inversion processes while preserving model topology. These methods enable the resolution of previously challenging geological scenarios, such as salt dome geometries and rift basin formations. Case studies illustrate the impact of these developments: the Liguro-Provençal Basin's evolution was revisited using gravity field analysis to assess its rifted nature, while applications in the North German Basin demonstrated the effectiveness of the space-warping technique in refining salt dome structures. These examples highlight the added value of such versatility in addressing regional and global geological challenges through multi-disciplinary modeling approaches. By merging forward modeling and interactive inversion with novel numerical methods, the new version of the software provides a robust tool for geoscientists aiming to integrate diverse datasets into comprehensive models. This work underscores the importance of user-driven innovations in geophysical software, pushing the boundaries of how subsurface structures are explored and understood.
How to cite: Götze, H.-J., Anikiev, D., Plonka, C., Schmidt, S., and Scheck-Wenderoth, M.: Advancements in 3D Potential Field Modeling: Enhancing Lithospheric Insights with IGMAS+, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3292, https://doi.org/10.5194/egusphere-egu25-3292, 2025.
Existing global-scale models of the Earth’s lithospheric magnetic field are composed of short wavelength information (< 100 km) from near-surface survey data and long wavelength information (> 300 km) from satellite data. In oceanic areas, compilations of ship trackline data provide the near-surface measurements used to construct gridded maps of the crustal magnetic anomaly field. Although these maps have been used widely for tectonic and geodynamic studies, advanced applications, including complex inversions, machine learning, and the use of magnetics for alternative (to GPS) navigation, require renewed attention as to how gridded maps are made. Data selection, including detection of anomalous tracklines, knowledge of the sampling and power spectra of the potential field, quantification of uncertainty and an accurate representation of the gradients in the estimated field all represent areas of interest for advanced applications.
We help address the problem of magnetic map-making for advanced applications by developing a means of quantitative comparison of magnetic data which is applied to each length scale of the underlying magnetic measurements and interpolated grids as a function of potential field frequency (spatial wavelength). Coherence analysis provides a technique to make a wavelength-dependent quantitative comparison, which can be used for data selection as well as to measure length-scale dependent attributes, errors, and uncertainties. Coherence can help to assess if individual tracklines are consistent with the overall dataset and help to determine if anomalous tracklines should be included in a final map product. Applied in this way, coherence could help automate or semi-automate the task of trackline selection. Coherence can be used to evaluate gridded maps made using different procedures for interpolation and continuation, helping to identify optimal map-making methods.
The coherence method also can be used to validate map quality in specific locations by comparing single trackline survey data to the reference map in the trackline direction using one-dimensional coherence, evaluating map quality and errors over several length scales. An understanding of the uncertainty at different length scales provides important information for the development and tuning of navigation algorithms and can provide an analytical framework for understanding different methods of map construction. In areas with high-quality reference maps this type of analysis can help inform scale dependent uncertainty models.
How to cite: Duff, P. and Nielsen, A.: Magnetic map-making for advanced applications: Quantitative comparison of frequency dependent features, errors, and uncertainties in gridded magnetic data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14009, https://doi.org/10.5194/egusphere-egu25-14009, 2025.
Magnetization vector inversion is essential for obtaining magnetization vector information from subsurface rocks. To obtain focused inversion results that better match the true magnetization distributions, sparse constraints are considered to constrain the objective function. A compact magnetization vector inversion method is proposed that can provide accurate inversion results for magnetic data with significant remanent magnetization. Considering the sparse constraint and the correlation between the three magnetization components with different directions, the L1-norm is modified and introduced into the inversion algorithm to obtain compact results.Furthermore, to reduce the computational cost, a randomized singular value decomposition is used to replace the traditional singular value decomposition and iteratively minimize the proposed objective function. Finally, the proposed method is applied to igneous rocks with strong remanent magnetization in the Haba River area of northwestern China. The distributions, directions of total magnetization and remanent magnetization of the medium-base igneous rocks are revealed by the sparse magnetization vector inversion method, which provides a wealth of information about the concealed deposits in the area.
How to cite: Li, X. and Liu, S.: High-precision Magnetization Vector Inversion : Application to the Mineral Exploration, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14485, https://doi.org/10.5194/egusphere-egu25-14485, 2025.
The underlying magmatic system in the Xiangshan volcanic basin is crucial in controlling the origin and migration of ore-forming fluids and driving uranium element transport. However, its shallow structure still lacks high-resolution imaging constraints. Gravity and magnetic data are combined in a three-dimensional joint inversion to obtain structurally similar density and magnetic susceptibility models of the Xiangshan shallow magmatic system. As imaged by the obtained model, a steep tubular anomaly characterized by low density and high magnetic susceptibility beneath the main peak of Xiangshan, interpreted to be a volcanic conduit associated with the porphyroclastic lava. A tubular high-magnetic susceptibility anomaly that located approximately 3 km west of the Xiangshan main peak is also imaged, is presumed to be a rhyodacite volcanic conduit. Both of them converge at depth and exhibit a hereditary relationship. In addition, the east-west oriented low-density anomaly is likely a reflection of the depression zone in the metamorphic basement. It is speculated that the imaged regional structural framework could control the emplacement of shallow magmatic system. We argue that the deep magma intrudes along the basement fault zone and ascends through its derived secondary fractures, providing material and heat sources for shallow hydrothermal circulation.
This work was funded by the National Natural Science Foundation of China (grants 42130811, 42304090 and 42374097) and by Jiangxi Provincial Natural Science Foundation (20242BAB20143).
How to cite: Feng, M., Deng, J., Chen, H., Yu, H., and Chen, X.: Imaging the shallow magmatic system of the Xiangshan volcanic basin by the 3-D joint inversion of potential field data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9602, https://doi.org/10.5194/egusphere-egu25-9602, 2025.
Gravity inversion quantitatively provides a 3D model of density contrasts, significantly enhancing the information extracted from acquired data. However, the inherent non-uniqueness of inversion poses challenges in precisely determining the boundaries of anomalous bodies. We have developed an iterative algorithm of gravity inversion that reconstructs the geometric features of the anomalous bodies by discretizing the 3D interpretation model with vertical and juxtaposed prism cells. These prisms incorporate sheet-like initial models which are typically derived from prior information or imaging results. This study proposed a new parameter, the Thickness Factor (TF), which is determined by the thickness of the prism cells under the assumption of homogeneous anomalous bodies. The TF establishes an approximate linear relationship between the source geometry and gravity anomalies, enabling the reconstruction of the source geometry to be formulated as a linear optimization problem. The approach demonstrates the potential for target inversion in the presence of multiple causative sources in synthetic cases and shows insensitivity to noise signals and reliability in reconstructing the geometry of complex sources. The proposed method is then applied to real data from the Galinge iron ore deposit in Northwest China and the drilling data is used as prior information. The inversion results are consistent with previous drilling interpretations and allow a rough estimation of the volume of the ore bodies.
How to cite: Zhang, B. and Liu, S.: 3D Compact Geometry Inversion for Gravity Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14488, https://doi.org/10.5194/egusphere-egu25-14488, 2025.
Most large and easily accessible mineral deposits have been found and exploited. To continue to supply critical mineral resources central to global industries, mineral exploration must move to deposits that are deeper or smaller, and therefore are more challenging to identify and characterize using geophysical methods. To provide reliable imaging results for these challenging scenarios, new inversion techniques are required that can reduce the non-uniqueness of the inverse problem through tight integration of geophysical and geological data.
For this purpose, we are studying surface-geometry inversion (SGI) methods, which parameterize the Earth in terms of surfaces representing interfaces between different rock units. This parameterization is more consistent with geologists' understandings of the Earth, and has high potential to allow the tight integration of geophysical and geological information that we seek. Our SGI approach effectively takes some initial surface-based model, for example a geological model, and alters the position of the surfaces to improve the fit to the geophysical data. Using geophysical inversion to determine the geometry of subsurface targets has a long-established history, tracing back to the early days of geophysical interpretation. These methods continue to gain considerable attention because of the growing demand for more precise and interpretable visual representations of subsurface bodies.
Recently, SGI methods are becoming increasingly common and have been applied to many varied imaging scenarios. However, little work has thoroughly assessed the reliability of these methods. It is important to know whether the solutions obtained from SGI are unique and stable and, if they are not, how to add regularization or constraints to make them so. Without a well-posed problem, any interpretations of the subsurface based on those solutions, and any exploration decisions based on those interpretations, are unreliable. Assessing the numerical characteristics of SGI problems is challenging because they overwhelmingly use global heuristic optimization methods and stochastic sampling in their solution, they are severely nonlinear, and they lack explicit matrix operators and derivatives. A critical aspect is understanding when regularization/stabilization should be incorporated into the SGI optimization problem to create a well-posed problem. In this work, we make headway towards a better understanding of these important issues in the specific context of inverting potential field data for mineral exploration scenarios.
How to cite: Vatankhah, S. and Lelievre, P.: Towards More Reliable Surface Geometry Inversion Methods for Mineral Exploration, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12062, https://doi.org/10.5194/egusphere-egu25-12062, 2025.
Vector geomagnetic survey technique can obtain simultaneously the magnitude and direction information of the geomagnetic field, which can effectively reduce the multiplicity of solutions on the inversion, contribute to the quantitative interpretation of the magnetic body, so as to improves the detection resolution and positioning accuracy of the ore. The development of magnetic component inversion is restricted by factors such as the estimation accuracy of the direction of magnetization, the calculation efficiency of the objective function. According to the analytic solution formula of the magnetic component, three kernel matrices can be constructed to calculate the magnetic components Bx, By, and Bz by using the magnetization intensity, which can not only avoid the prior estimation of the direction of the magnetization, but also the constructed kernel matrix is a blocky toeplitz matrix with the help of the special blocking method of the equivalent geometric architecture. And because of the structureal properties of the blocky toeplitz matrix, the computational of the kernel matrix and magnetization intensity is simplified and the huge storage consumption is reduced.Finally, the regularization method is used to invert the solution. A theoretical model is used to verify the utility and reliability of the method.The result shows that compared with the traditional method, the computational time of the proposed method is reduced greatly, and the inversion results are consistent with the input model.
How to cite: Teng, D., Wang, L., Zheng, J., Wang, G., and Xue, D.: A fast inversion method for magnetic components, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15102, https://doi.org/10.5194/egusphere-egu25-15102, 2025.
This study shows that multiscale imaging methods applied to time-lapse gravity data can be effective to estimate the subsurface stored mass of CO₂. Differently from previous studies based on simplified plume shapes, we show that a multiscale analysis of gravity data is particularly useful to properly estimate the excess mass from gravity anomalies associated with complex plume geometries and characterized by multi-homogeneity properties. With a multiscale approach, in fact, we can exploit the scaling behavior of the potential fields and assess the variation in the degree of homogeneity and, consequently, the estimation of the structural index of the source.
The simulated gravity dataset and the estimated homogeneity degree values at different altitudes showed that, as the distance from the source increases, the gravity field associated with the CO2 plume becomes progressively smooth and can be approximated as homogeneous. Moreover, the multiscale analysis effectively reduces the noise effect, that is particularly advantageous for CO2 storage monitoring, where low signal-to-noise ratios are expected. The excess mass inferred using our approach results closely equal to the true value with accuracy higher than 99%. Our multiscale analysis was also successfully applied to the real time-lapse gravity dataset acquired at the Sleipner site.
This study presents a useful approach for developing new monitoring strategies for CCS purposes. Time-lapse gravity surveying has again proven to be an effective tool for inferring key reservoir properties, complementing seismic monitoring techniques.
How to cite: Milano, M., Bianco, L., and Fedi, M.: Assessing the CO2 stored mass at the Sleipner storage site from time lapse gravity data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19768, https://doi.org/10.5194/egusphere-egu25-19768, 2025.
The Balmuccia peridotite is a well-known outcrop in the Italian Alps, with a surface extent of ca. 4.4 km. by 0.6 km, including a ca. 1000 m elevation change. It is of particular interest for project DIVE (Drilling the Ivrea-Verbano zonE, ICDP expedition 5071) phase 2 as it is a prime site to continuously sample the crust–mantle transition by drilling, and to test the suitability of a natural peridotite body for serpentinization and hydrogen production.
Current models of the subsurface extent of the Balmuccia peridotite differ significantly, depending not only on the geoscience discipline of investigation, but also on the characteristics of the geophysical imaging campaigns. Therefore, in an effort to reduce the uncertainties regarding the geometry of the Balmuccia peridotite body at depth, we have launched an open, participative gravity-modelling challenge (Hetényi et al. 2024): a new gravity dataset of 151 points is shared with anyone interested, accompanied by a geological map, rock densities of the different lithologies, and a digital elevation model. Interested parties can design various 3D model setups and perform modelling and/or inversion, the results of which can then be compared.
In the past year, several groups have shown interest in modelling the target body, and have undertaken processing steps, corrections, and defined model geometry classes for forward modelling. While the initial concept was to let each group work independently, regular meetings allowed to agree on a few steps beyond what was provided with the data (such as an optimized DEM to be used by all participants), and to discuss individual questions regarding the data and the computations. In this contribution we will present the progress of this initiative, compare existing models or their elements, taking into account other geophysical data beyond gravimetric measurements, and outline the remaining questions. Preliminary conclusions regarding the geometry of the Balmuccia peridotite body are planned to be presented.
How to cite: Baron, L., Scarponi, M., Anikiev, D., Barbély, E., Benedek, J., Götze, H.-J., Ismaiel, M., Papp, G., Schmidt, S., Tondi, R., and Hetényi, G.: Participative gravity-modelling of the Balmuccia peridotite body: progress report, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17417, https://doi.org/10.5194/egusphere-egu25-17417, 2025.
Posters virtual: Tue, 29 Apr, 14:00–15:45 | vPoster spot 2
EGU25-3794 | ECS | Posters virtual | VPS28
Identifying Prospective Areas for the Chatree Epithermal Gold Region from Airborne Magnetic Data Using Advanced Analyzing Techniques, with Interpretative CorrelationTue, 29 Apr, 14:00–15:45 (CEST) | vP2.26
The Chatree Region, located in central Thailand, holds significant potential for gold exploration, hosting substantial mineral resources. The complex geological setting of this region, with its diverse lithologies and intricate structural controls, poses both significant opportunities and challenges for successful mineral exploration. Given these challenges, this study utilizes a geophysical approach focusing on magnetic data interpretation to enhance the precision and efficiency of identifying potential gold prospects.
Enhancements to the magnetic data were achieved through the application of Downward Continuation (DWC) and Automatic Gain Correction (AGC), which amplified near-surface features and improved signal clarity. Subsequently, by employing the Centre for Exploration Targeting (CET) Grid Analysis, zones of structural complexity, indicative of epithermal gold deposits were detected, which generated two heat maps, including Contact Occurrence Density (COD) and Orientation Entropy (OE). These maps revealed six major and seven minor potential gold prospect zones, providing a critical dataset for subsequent geological analysis. Geological correlations and lineament interpretation were then conducted to validate and refine the magnetic interpretations by integrating several filtered magnetic images with existing geological knowledge of the region. The results of this integrated approach show that many of the identified magnetic anomalies and lineaments correlate with known geology, highlighting the critical role of synthesizing advanced magnetic data analysis with geological expertise. This integration provides a valuable foundation for future exploration in the region and establishes an applicable methodological approach to other mineral exploration efforts.
How to cite: Pinkaew, K.: Identifying Prospective Areas for the Chatree Epithermal Gold Region from Airborne Magnetic Data Using Advanced Analyzing Techniques, with Interpretative Correlation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3794, https://doi.org/10.5194/egusphere-egu25-3794, 2025.
