The methods used for differentiation of potential field data play an important role in interpretation, as various derivatives are included in many of the transformations often used when interpreting such data (e.g.: Analytical Signal, Tilt Angles, Total Gradient and others). However, the evaluation of horizontal and vertical derivatives is an unstable process. The possible (partial) answer to this instability is the Tikhonov regularization based on incorporating an additional property representing maximum smoothness, which is typically obtained by cascading low-pass filtering - managed by means of a regularization parameter. Here we present and compare several ways to evaluate regularized differentiation operators and compare their properties. Among them, a newly introduced form (named as General Form) plays a very important role. As is typical for regularization algorithms, the crucial step is the setting of a quasi-optimal value of the regularization parameter, which gives the best possible solution. Several methods of its estimation (focused on the utilization of Lp norms) are presented and the resulting utility became the keystone in valuation of the presented regularized operators.

Braided river systems are a substantial source of groundwater recharge in New Zealand. These rivers flow from high relief towards the sea across alluvial plain aquifers, across which the primary groundwater recharge occurs. These aquifers are often used for agricultural irrigation, and overexploitation can occur if there is limited knowledge on aquifer recharge mechanisms. To understand these complex recharge patterns a more detailed knowledge of the lithological controls on surface water-groundwater exchange is necessary. Here we present a case study, where surface nuclear magnetic resonance (SNMR) was employed in braided river systems to identify subsurface structures. We found the method to be efficient in identifying permeability contrasts beneath riverbeds and river berms in multiple river settings. We calibrated a local archetype by coincident borehole lithology and SNMR derived water contents, to find the SNMR signature related to lithological changes. The resulting archetypes were extrapolated to SNMR sites where there is no coinciding borehole information to identify these lithological transitions at multiple sites. We show that a combined borehole and SNMR survey can map transitions from aquifers to low permeability-layers efficiently in three case studies. The small 20 m x 20 m SNMR coil enabled acquisition on small bars within the river while resolving the thin saturated units, previously not resolvable with a larger coil size. The lateral constrained inversion (LCI) improved lateral consistency and the ability to track the features of the braidplain aquifer in all three rivers within the top 10 m. These results demonstrate SNMR as a multisite geophysical method capable of mapping important hydrogeological layers to provide valuable information on recharge to vulnerable aquifers.

Distributed acoustic sensing (DAS) generally records the seismic signals by detecting the axial strain or strain rate that is stimulated by the impinging elastic wavefields along the optical fibers. It has become an important seismic observation technology, especially in vertical seismic profiling (VSP) applications, due to its low cost, easy deployment and high-density spatial sampling. Although current DAS-VSP acquisitions typically offer only a single-component observation, they still provide valuable elastic information about the subsurface. Separating P and S waves from the DAS-VSP data and leveraging these wavefield information is very important for the inversion of elastic parameters and seismic imaging. Therefore, a polarization projection method is introduced to deal with the P/S separation of walkaway DAS-VSP data. Firstly, the polarization directions of P and S waves are estimated using the dispersion relation derived from elastodynamic wave equations. Then, the P/S wave separation is achieved through a non-stationary polarization projection that can take into account the effects of spatially varying wave velocities. Finally, a two-step workflow is proposed to successively separate the P and S waves in common-shot and common-receiver gathers. The results of synthetic and real walkaway DAS-VSP data demonstrate that this method can effectively separate P- and S-wave signals from DAS-VSP data, and provide effective data preconditioning for subsequent velocity model building and seismic imaging.

Perforation is essential for the development of unconventional oil and gas, hydrogen, geothermal energy, and deep subsurface exploration, yet an effective evaluation method has remained elusive. The multiscale tomography (MST) method is applied to analyze downhole perforation, improving inversion accuracy through the multiscale discretization of velocity model grids. Numerical experiments demonstrate the method’s reliability in determining perforation depth intervals, radial penetration depths, and velocity variations outside the well. Simulations before and after perforation reveal significant traveltime changes, supported by logging data showing delays and velocity shifts. A comparison of imaging results with various receiver configurations highlights the critical role of receiver arrangement in achieving accurate subsurface imaging. These findings validate MST as an effective tool for perforation assessment and velocity imaging around wells, with an emphasis on optimal receiver configuration.

The correct interpretation of time-domain electromagnetic (TEM) data acquired in complex geological environments relies on 3D inversion. However, the complexity of the TEM problem makes 3D inversion extremely time-consuming. This is one of the main obstacles to the application of the 3D inversion technique to practical problems. The most time-consuming parts of the 3D inversion are the forward modeling and the calculation of the sensitivity matrix. This is because both operations require dealing with large sparse matrices, which is very time-consuming either by direct or iterative methods. In this paper, we present an algorithm framework designed to accelerate 3D TEM inversion. To solve the forward problem quickly, we use our previously proposed algorithm, BEDS-FDTD, which can downgrade and reconstruct the large sparse matrices into a series of low-order tridiagonal ones. The sensitivity matrix is implicitly computed by adjoint forward modeling to reduce memory requirements. Based on the characterizations of the forward equations and the inverse time series solving of the adjoint field, we derive the control equations for the adjoint forward modeling with low-order tridiagonal coefficient matrices. In the new inversion algorithm, there is no longer a need to solve large sparse matrices, but instead low-order ones, which saves computation time. To further accelerate the 3D inversion, the forward and adjoint equations are solved on graphics processing units (GPUs) in parallel. This inversion algorithm is first tested on two synthetic models. The experiment results demonstrate the effectiveness of the inversion algorithm proposed in this paper, and the time spent on 3D inversion is reduced significantly. Finally, we use this inversion algorithm for field data, and the inversion results agree well with the known information.

Ground-penetrating radar full waveform inversion (GPR-FWI) is a high-resolution inversion technique that quantitatively estimates the subsurface physical parameters (permittivity, conductivity) by matching both waveform amplitude and phase. However, the requirement to meet stability conditions forces the during wave propagation grid dimensions to be at the centimeter level, resulting in significant memory usage when discretizing the full radar wavefield. This makes it challenging to apply the FWI method on large-scale 2D or 3D GPR datasets. Furthermore, most commercial GPR systems record common-offset gathers (COG), so most GPR field data does not need to calculate the full model-space wavefield during the FWI iteration procedure. This work proposes a multi-region full waveform inversion approach (MR-FWI) for common-offset GPR data. The core strategy is to divide the model space into multiple grid regions and dynamically adjust these grids according to the requirements. By focusing on a given spatial range of the wavefield and model gradient, the computational steps are optimized, significantly reducing memory consumption and computational cost. A synthetic model and two raw GPR data examples validate that the multi-region strategy can reduce the computational burden without sacrificing inversion accuracy. The proposed MR-FWI is particularly suitable for limited computing resources and large-scale datasets, which provides a robust and high-resolution approach for most real common-offset GPR applications.

Full waveform inversion (FWI) can be applied to time-lapse (4D) seismic data for subsurface reservoir monitoring. Usually, baseline and monitor velocity models are respectively built through a data fitting process, and the difference of models are used to estimate the time-lapse changes. However, large-scale (or low-wavenumber) velocity structures of deep reservoirs are mainly obtained by fitting the diving waves, which can be unavailable due to limited source-receiver offset apertures. Alternatively, joint full waveform inversion (JFWI) assumes a scale separation in the model space such that low wavenumbers can be recovered from both diving and reflected waves, in addition to high-wavenumber impedance perturbations. We extend JFWI to time-lapse data and improve the sensitivity of waveform inversion approaches to low-wavenumber velocity changes of deep targets. A central-difference strategy is also implemented (CD JFWI), which averages four JFWI velocity models (two baseline and two monitor) to attenuate false changes in the 4D velocity estimate, and which increases the stability of the approach in data fitting. The synthetic 4D SEAM case study shows that CD JFWI followed by 4D FWI leads to a more accurate estimate and better resolution of velocity changes than conventional 4D FWI methods in a reservoir zone that is not penetrated by diving waves.

Multiple reflections significantly influence seismic migration because they can lead to spurious events in traditional methods, such as reverse time migration and Kirchhoff migration. Marchenko imaging represents a transformative advancement in the field of seismic migration that relocates seismic data containing internal multiples to accurate subsurface locations. Through the continuous pursuit of methodological refinement, we develop an innovative approach: incorporation of the Marchenko method within a least-squares migration framework, named least-squares Marchenko imaging (LSMI), based on the steepest descent method to minimize the [Formula: see text] norm of gradient images. In the LSMI, to solve the problem that the conventional Born approximation can only simulate primary waves, we use the Marchenko Green’s function and the Born approximation to construct a Marchenko demigration operator, which can successfully simulate synthetic seismic data containing internal multiples. However, Marchenko demigration based on the Born approximation requires a large amount of calculation, and multiple iterations increase the computation time. Therefore, we introduce a parallel-computing framework implemented in the frequency domain to improve the computational efficiency of the Marchenko demigration. We partition the frequency-domain-transformed Green’s function into discrete chunks and implement parallel computation. This parallel processing significantly accelerates the Marchenko demigration process. The effectiveness of our method is validated by applying it to a layered model. The experimental results show that LSMI converges with the [Formula: see text] norm. Moreover, the superiority of our method over conventional Marchenko imaging is evident from its notable enhancement related to artifact suppression, resolution improvement, and illumination compensation. To further validate the effectiveness of our method, we conduct additional experiments on the Sigsbee2A model, demonstrating that our method is also effective for this complex model. This is a novel approach to seismic migration, particularly in areas with internal multiples.

Taiwan is an active orogen where a west-verging fold-and-thrust belt deforms a Plio-Pleistocene foreland basin sequence. In southwestern Taiwan, the 3-4-km-thick Gutingkeng mudstone, Late Miocene to Early Pleistocene in age, has similar characteristics to mobile shales, such as overpressure conditions and sourcing mud volcanoes. Present uplift rates as fast as 2 cm/yr were observed mainly on the footwall of steep thrusts, including the Gutingkeng Fault, which trace features several mud volcanoes. We integrate surface observations near this fault with regional subsurface data to construct an upper crustal cross-section and evaluate the roles of competing models of fault-related folding and shale tectonics in deforming the region. Field observations show steep and well-preserved bedding on the hanging wall and footwall and a wide reverse fault zone with penetrative shearing, corresponding to the Gutingkeng Fault. No distinct structure explaining footwall uplift were found in the outcrops. At the cross-section scale, surface geology and subsurface data point to a structural style with fairly narrow anticlines with steep limbs, growing above a relatively deep detachment. This geometry is not easily explained using classical fault-related fold models. We infer that folding on the Gutingkeng Fault footwall and in the core of a frontal anticline occurs through layer thickening (pure shear) facilitated by the weak mudstone rheology. The increase in pore-fluid pressure under burial and tectonic compression within the fold cores could lead the mudstone to mobilize and undergo plastic flow, causing inflation of the fold cores. Fold growth, possibly aided by shale tectonics, would have progressively increased the dip of the Gutingkeng thrust, eventually leading to thrust inactivity and uplift mainly occurring on the footwall. Our study area offers a unique opportunity to study an active shale-dominated fold-thrust belt exposed on-land and highlights the importance of combining geodetic observations to investigate on-going deformations in these settings.

Mass transport deposits (MTDs) have attracted widespread attention from scholars because of their powerful sediment transport ability and capping effect on shallow natural gas reservoirs. Due to the rich types and development of MTDs, the Qiongdongnan Basin (QDNB) is considered an excellent place to study the triggering mechanisms of MTDs. Based on 2D seismic data, the types, characteristics, distribution, and sources of the Quaternary MTDs in the QDNB are recorded. In addition, the triggering mechanisms and sedimentary evolutionary patterns are examined. There are three types of MTDs in the study area: shelf-attached MTDs, slope-attached MTDs, and magmatic intrusion-triggered MTDs. The shelf-attached MTDs developed in the northwestern slope of the basin, and they are thick and wide in scale. The slope-attached MTDs developed in the northeastern slope area of the basin, and they are thin and wide in scale. A magmatic intrusion-triggered MTDs are developed in the bulge area of the southern basin, with small in scale and large thickness differences. The transport direction of these MTDs is mainly from the northwest-southeast and southeast-northwest. The analysis of the tectonic-sedimentary evolution of the QDNB reveals that the MTDs may have been controlled by the following five factors: first, the bottom configuration controlled the MTDs’ flow direction; second, the amplitude of the sea-level fluctuation and the reactivation intensity of the main fault in the basin may have triggered the large-scale, attached MTDs in the northern slope area; third, the high sedimentation rate controlled the attached MTDs, the shelf-attached MTDs developed when the source supply was strong, but the slope-attached MTDs developed when the source supply was weak. Furthermore, magmatic activity controlled the development and distribution scale of magmatic intrusion-triggered MTDs in the southern QDNB.

Gas chimneys can often be observed in marine seismic profiles, which are usually related to gas accumulation in shallow layers and their impacts on rock elasticity. In order to clarify the impact of various geological factors to elastic wave propagation, an experimental study is conducted to elucidate the variation of rock elastic parameters in gas accumulated rocks. Gas accumulation simulations and real-time ultrasonic monitoring experiments are conducted in laboratory experiments. The control factors for gas chimney formation, such as pressure, porosity, fractures and fluids, are analyzed. It is found that high pore pressure provides favorable conditions for the formation of gas chimneys. Within the lower range of pore pressures, the P- wave velocity is more sensitive to gas changes, whereas the S- wave velocity is relatively insensitive. When the pore pressure is within a moderate range, the S- wave velocity is more sensitive than the P- wave velocity. At higher pore pressures, the influence of the pore pressure on the P- wave velocity is greater, and the influence on the S- wave velocity is smaller. The experimental results for low-porosity sandstone are significantly influenced by pore pressure, whereas the attenuation of P- and S- waves in high-porosity sandstone is controlled by porosity and less sensitive to changes in pore pressure. The presence of fractures has a significant impact on both velocity and amplitude, and the impact of fractures is no longer significant when the pore pressure is high. Injecting a small amount of gas into water saturated rocks can cause a strong attenuation of wave amplitude, indicating that the influence of mixed fluids on amplitude is more significant than other factors. This study provides a theoretical explanation for gas chimney formations in shallow loose rocks and help to analyze seismic wave propagation properties in the field.

The constant- Q viscoelastic wave equation, which includes decoupled amplitude attenuation and phase dispersion terms, is commonly used for attenuation-compensated reverse time migration (RTM). However, this equation involves fractional Laplacian operators and typically requires computationally intensive spectral methods. Efficient implementation is crucial for practical applications. To address this, we derive a new isotropic viscoelastic wave equation based on the standard linear solid model, which also contains decoupled amplitude attenuation and phase dispersion terms. This new equation can be solved using an efficient finite-difference method in the time domain. Consequently, we develop a viscoelastic RTM with attenuation compensation. Numerical simulations demonstrate that this equation accurately and efficiently simulates the decoupled amplitude loss and phase dispersion characteristics.

Magnetotelluric (MT) data inversion reconstructs the subsurface resistivity structure using measured natural electromagnetic (EM) fields. Due to the attenuation of lowfrequency EM waves in geological conductors, MT inversion has lower sensitivity and resolution for subsurface structures compared with seismic reflection imaging. Seismic reflection provides rich, detailed subsurface information that complements EM data, such as the spatial locations of geological boundaries and fine-scale geophysical attributes. This work presents a super-resolution MT inversion approach incorporating the seismic texture constraint. We develop a multi-resolution model parametrization scheme to represent the unknown model with both the coarse-scale resistivity background and fine-scale resistivity details. A modified, pre-trained VGG19 neural network (NN) serves as an effective texture extraction operator. This inversion method requires no neural network training and simultaneously optimizes MT data misfit, texture discrepancy, and various regularization penalties using the Adaptive Moment Estimation (ADAM) optimizer. Experiments show that the proposed inversion can reduce or at least maintain the data misfit and effectively improve MT inversion resolution to a seismic-like level. This approach has promising application potential in the oil industry for highlighting quasi-layered subsurface structures.

In semiarid climates, precipitation is the most important hydrometeorological event, as it remains the main source of water. In the context of climate change, the analysis of its spatio-temporal trends provides useful information for effective planning and management of water resources. Daily rainfall data collected from 12 meteorological stations in the downstream Mekkera Basin, Northwest Algeria, between 1975 and 2011 were analyzed using the innovative polygon trend analysis method. The analysis focused on trends in average monthly rainfall, average number of rainy days, average daily intensity, maximum daily rainfall, and maximum number of dry days per month. The results reveal a contrasting trend in monthly precipitation averages between dry and wet season months. Precipitation drops by 55 times during the spring months, with a significant decrease in February and March. In winter, there was a less noticeable decrease, though the intensity of maximum daily events increased. August and September show a significant increase in maximum daily precipitation across all stations, consistent with the overall 52 detected cases of increasing rainfall in the dry season. In addition, 70% of time series show that an increase in rainy days led to a decrease in the maximum number of dry days, whereas 52% of time series with fewer rainy days experienced more dry days. These findings offer crucial insights that can assist water managers in developing adaptive strategies to tackle the changing precipitation patterns in the region.

The exploration of gas in the presalt reservoirs of the Ordovician Majiagou Formation in the Ordos Basin indicates considerable potential; however, the gas accumulation history remains a matter of significant debate. This paper focuses on well cores from the northern Ordos Basin to address these uncertainties. By using reservoir petrographic research and a comprehensive analysis of fluid inclusions, the periods and times of petroleum accumulation are determined, and the gas accumulation history of the Ordovician Majiagou Formation in the region is analyzed. The results suggest that gas from marine hydrocarbon source rocks and the cracking of oil contribute significantly to the gas accumulation in the Ordovician Majiagou Formation. Two stages of oil and gas accumulation in the presalt reservoirs of the study area are identified. In the initial stage, a minor liquid oil charging event occurred between 215 and 170 Ma. In the subsequent stage, gas is generated from the Carboniferous-Permian coal-measure and marine hydrocarbon source rocks, supplemented by the thermal cracking of the earlier liquid oil accumulations in the Ordovician Majiagou Formation. This gas then migrates into the presalt reservoirs during the period from 125 to 80 Ma, resulting in substantial gas accumulation in the presalt reservoirs of the Ordovician Majiagou Formation in the study area.

Marine controlled-source electromagnetic (CSEM) inversion can produce useful resistivity models for offshore hydrocarbon surveys. However, traditional inversion techniques often face a trade-off between stability and resolution in resistivity imaging. To improve the imaging quality, we develop a novel image-guided regularization technique that works on an unstructured mesh. This approach adjusts the model penalty intensity following the eigenvectors derived from available seismic images, considering both the relative positions and features between adjacent cells. This modification guides the reconstructed resistivities to align with the seismic structures. We evaluate its effectiveness using the flattest model and the minimum gradient support (MGS) constraints within the framework of Occam’s inversion. Both synthetic and field data examples from the Troll West Oil Province (TWOP) demonstrate that the image-guided inversion effectively unveils subsurface resistivity structures and delineates the true shape and lower boundaries of resistive targets. The robustness and high-resolution imaging capability of the proposed method underscore its potential as a promising tool for offshore reservoir exploration.

Coherent noise separation stands as a critical step in seismic data processing. The Morphological Component Analysis (MCA)-based separation method, treating coherent noise and signal as distinct components and representing them sparsely with dictionaries, has found widespread application in the effective suppression of coherent noise. In practice, when constructing effective fixed dictionaries for MCA-based separation methods, a common approach involves conducting numerous experiments to meticulously select appropriate transform basis functions from an extensive dictionary library and tune their parameters. To mitigate time consumption and ensure optimal dictionary construction, we introduce a framework for adaptive identification of the optimal dictionaries used in MCA-based coherent noise separation. Specifically, we initially characterize the notion of a fixed dictionary library, which encompasses dictionaries constructed using various transform basis functions and their corresponding parameters. Then, we present a Relative Sparsity Minimization Problem (RSMP), formulated to identify the optimal fixed dictionaries that lead to minimum relative sparsity within the predefined library. Finally, we design a genetic algorithm to solve RSMP. The optimal dictionaries obtained for representing signal and coherent noise, respectively, are applied to MCA-based coherent noise separation. Synthetic and field data examples demonstrate the effectiveness of the proposed method.

In this article, the Editor of Geophysics provides an overview of all technical articles in this issue of the journal.

Although computer science has seen remarkable advancements in foundation models, they remain underexplored in geoscience. Addressing this gap, we introduce a workflow to develop geophysical foundation models, such as data preparation, model pretraining, and adaption to downstream tasks. From 192 globally collected 3D seismic volumes, we create a carefully curated data set of 2,286,422 2D seismic images. To fully use these unlabeled images, we use self-supervised learning to pretrain a transformer-based seismic foundation model for producing all-purpose seismic features that work across various tasks and surveys. Through experiments on seismic facies classification, geobody identification, interpolation, denoising, and inversion, our pretrained model demonstrates versatility, generalization, scalability, and superior performance compared with baseline models. In conclusion, we provide a foundation model and vast data set to advance artificial intelligence (AI) in geophysics, addressing the challenges (poor generalization, a lack of labels, and repetitive training for task-specific models) of applying AI to geophysics and paving the way for future innovations in geoscience.

Seismic migration is an effective technique for reconstructing the subsurface geological structure. Focusing on common-image gathers (CIGs) produced by pre-stack depth migration, the imaging result is usually obtained by mean stacking CIGs from different shot-receiver pairs. For optimal results, the desired CIGs should exhibit consistent depth and waveform of the imaging wavelet across different angles or offsets. However, raw CIGs often suffer from misalignment due to inaccuracies in the migration velocity model and mad physical limitations. Additionally, factors such as complex topography, intricate subsurface structures, irregular acquisition geometries, and space-variant seismic wavelets contribute to uneven illumination and migration artifacts within CIGs. As a result, directly stacking CIGs does not yield high-resolution imaging. To address these challenges, we propose a novel imaging method based on CIGs. First, we analyze the high-resolution imaging process and identify residual depth, residual phase, and uneven illumination in CIGs as the primary factors affecting the stacking quality. To obtain high-resolution imaging, it is crucial to ensure that CIGs are flat and consistent in depth. Therefore, we have developed an improved dynamic programming method to flatten the CIGs. Next, to account for the uneven illumination across different angles and offsets, we propose an illumination-based weighted operator to optimize the CIGs, complemented by a similarity coefficient method for generating the stacking image. Finally, we present results from a synthetic model and field dataset to demonstrate the effectiveness of the proposed method. The results indicate that our approach significantly enhances imaging resolution and amplitude preservation, thereby improving imaging quality in complex exploration areas.

The formation of folds often leads to the emergence of subsidiary faults, thereby creating intricate fault-fold systems with fractures. While existing literature on fault-fold systems predominantly relies on field observations, there has been scant research focusing on their subsurface structures. Utilizing three-dimensional seismic data, this study endeavors to identify and quantify the principal fault-fold systems within the No. 3 coal seam of the Shanxi Formation and the No. 15 coal seam of the Taiyuan Formation, in the southern Qinshui Basin, China. The findings reveal: (1) The presence of five principal fault-fold systems, with four exhibiting a North-South orientation and one aligning East-West; (2) The establishment of an asymmetric model for the fault-fold system through a quantitative analysis of seismic attributes, particularly focusing on the high-angle normal faults along the folds' limbs; (3) The asymmetrical fault damage zone width (No. 3 fault-fold system) is quantitatively measured at approximately 200 meters on the west side, in contrast to the east side where widths range from 50 to 500 meters. These initial assessments show the great potential of an attribute-enhanced geological model, which may provide insights for analyses of the continuity of coal seams, the propagation of fractures, and the migration of gas within fractured reservoirs.#xD;

We conduct reflection and Love-wave imaging on three two-dimensional (2D), three-component (3C) land-streamer seismic lines to characterize a buried bedrock valley underlying glacial deposits situated within southern Ontario, Canada. Understanding the valley’s characteristics is important for designing above-ground structures, investigating groundwater and surface water interactions, and erosion processes driven by glacial cycles. These characteristics include width, extension, overburden thickness, spatial facies distribution, and geometrical configuration of the overburden-bedrock contact. Reflection processing on the WSW-ENE trending profiles reveals the bedrock geometry and Quaternary sediment stratigraphy, including a shallow reflection associated with a lithostratigraphic transition zone. We utilize the dispersive properties of Love waves to derive pseudo-2D shear-wave velocity profiles along the seismic transects. The inversion process is constrained by the P-wave refraction velocities from reflection processing. We emphasize the significance of data preconditioning prior to surface wave analysis and propose an optimal processing sequence for moderately to highly noisy gathers. Likewise, we construct bedrock-reaching velocity profiles for depth conversion of reflectivity sections by using shear-wave velocity from Love-wave inversion, regression analysis, and water well data. The proposed signal preconditioning and integrated velocity modeling approach can be implemented in other areas where land-streamer seismic surveys are available, enhancing quantitative imaging and depth conversions. Blind borehole records demonstrate average depth-conversion errors of less than 2% following this approach. The Love-wave velocity imaging and the body-wave reflection imaging correlate well with each other and with lithological changes observed in water wells. This is demonstrated by the alignment of velocity contrasts with the geometry of the shallow reflection event at the lithostratigraphic transition zone. We find that the bedrock valley is approximately 60 m deep with a southward thinning width, possibly due to the valley’s geometry shifting from a north-south to an east-west orientation.

In recent decades, global technological expansion, alongside significant shifts in information technology, energy supply and mobility, has dramatically increased the demand for certain raw materials, especially minerals. To meet future demand, new strategies and solutions are being sought. Semi-airborne electromagnetics, as an emerging method to sense conductive subsurface structures, holds high potential for mineral exploration and can be applied to uncover untapped ore deposits or re-evaluate exploited ones. This technique has been successfully implemented in multiple studies and is a core part of the DESMEX (Deep Electromagnetic Sounding for Mineral Exploration) joint project. To date, promising sites are being surveyed either employing crewed aircraft or using ground-based methods, both of which come with limitations concerning site access, survey period, achievable resolution and cost. By utilizing uncrewed aerial vehicles (UAVs) some constraints and expenses can be overcome. Taking advantage of a battery-powered 25 kg maximum takeoff weight octocopter and two complementary magnetometers, an optically pumped total-field magnetometer and an induction coil triple, we have surveyed the Hope deposit, a known, unexploited massive sulfide mineralization in Western Namibia. Time-varying electromagnetic fields, excited by grounded electric-dipole transmitters, were measured and evaluated discretely in frequency domain. Based on two-dimensional inverse modeling, we were able to image the Hope ore body and to trace it down to a depth of more than 300 m. Combined sensor data inverted along adjacent profile lines reveal an imposing, contiguous dipping conductor that can be clearly assigned to the Hope structure. To assess the significance of our results, we inverted data from the two sensor systems individually as well as jointly and carried out detailed modeling studies. Our findings are supported by available resistivity models based on audio magnetotelluric data and yield an excellent match to existing borehole probes.

Modern measurement systems for geophysical exploration are increasingly based on uncrewed aerial vehicles. For performing semi-airborne electromagnetics, they offer a cost-efficient alternative to helicopters as carrier for receiver systems with reduced logistical efforts and a greater flexibility in survey layouts. We present inversion results of controlled-source electromagnetic data recorded with two different sensors, a scalar and a vector magnetometer, acquired in two mining areas, namely, the Hope deposit in Namibia and the Poderosa mine in the Eastern Iberian pyrite belt, Spain. The scalar magnetometer is more sensitive at lower frequencies while the vector magnetometer is more sensitive at higher frequencies. The Hope demonstration site is easily accessible with almost no vegetation and topography, allowing for optimized regular survey layouts and dense data sets to cover the region of interest. In contrast, the Poderosa test site is characterized by poor accessibility, topographic undulations up to 300m, and thick vegetation. For simulating and inverting scalar data projected to the local total magnetic field direction, we consider a resource-saving simulation approach using mesh rotation. We further extended the capabilities of the open-source tools custEM/pyGIMLi to invert the combined data sets of both receiver systems in both, 2.5D and 3D. As the two applied sensors are sensitive in different frequency ranges, combining the two data sets in inversion with a common frequency range of 1 to 1024 Hz provides the advantage of enhanced near-surface resolution together with investigation depths up to 1 kilometer. We assess the reliability of the inversion results by performing misfit and resolution analysis as well as comparing the inverted conductive zones with additional information about the two deposits. The results from both test sites demonstrate the capability of the proposed measurement design to recover comparatively small but elongated conductors associated with known massive sulfide deposits.