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A key aspect of protecting aquatic ecosystems from agricultural nitrogen (N) is to locate (i) farmlands where nitrate leaches from the bottom of the root zone and (ii) denitrifying zones in the aquifers where nitrate is removed before entering the surface water (N-retention). N-retention affects the choice of field mitigation measures to reduce delivered N to surface water. Farmland parcels associated with high N-retention gives the lowest impact of the targeted field measures and vice versa. In Denmark, a targeted N-regulation approach is currently implemented on small catchment scale (approx. 15 km2). Although this regulatory scale is much more detailed than what has been used previously, it is still so large that regulation for most individual fields will be either over- or under-regulated due to large spatial variation in the N-retention. The potential cost reduction for farmers is of up to 20–30% from detailed retention mapping at the field scale compared to the current small catchment scale. In this study, we present a mapping framework (N-Map) for differentiating farmland according to their N-retention, which can be used for improving the effectiveness of targeted N-regulation. The framework currently only includes N-retention in the groundwater. The framework benefits from the incorporation of innovative geophysics in hydrogeological and geochemical mapping and modelling. To capture and describe relevant uncertainties a large number of equally probable realizations are created through Multiple Point Statistical (MPS) methods. This allows relevant descriptions of uncertainties of parts of the model structure and includes other relevant uncertainty measures that affects the obtained N-retention. The output is data-driven high-resolution groundwater N-retention maps, to be used by the individual farmers to manage their cropping systems due to the given regulatory boundary conditions. The detailed mapping allows farmers to use this information in the farm planning in order to optimize the use of field measures to reduce delivered agricultural N to the surface water and thereby lower the costs of the field measures. From farmer interviews, however, it is clear that not all farms will have an economic gain from the detailed mapping as the mapping costs will exceed the potential economic gains for the farmers. The costs of N-Map is here estimated to 5–7 €/ha/year plus implementation costs at the farm. At the society level, the N-retention maps allow authorities to point out opportunities for a more targeted implementation of field measures to efficiently reduce the delivered N-load to surface waters.

Two efficient implementations of 3D and 2.5D modeling and inversion are presented to be applicable to large-scale transient electromagnetic (TEM) method explorations. The key novel features are (1) forward response and Jacobian calculations are implemented using the octree-based finite-element method, (2) a mirror approach is used to build a 2.5D inversion scheme for further efficiency, and (3) a flexible link between the forward mesh and inversion model is applied on 3D and 2.5D schemes based on the voxel formulation. We compare the performance of the new implementations with 3D modeling using tetrahedral meshes, with respect to speed and memory requirements. The 3D octree algorithm requires less than 1/3 of the computational time compared with a 3D tetrahedral scheme for equivalent accuracy. The 2.5D octree algorithm further speeds up the process by reducing the computational time by another factor of two. The inversion uses the Levenberg-Marquart approach minimizing the least-squares criterion of the objective function. We determine the utility of our inversion approach on a synthetic example and a field example. In the synthetic example, the 3D octree inversion result finds superior resolution of a 3D anomaly compared with a 1D result, whereas the 2.5D inversion result is, expectedly, between the 1D and 3D results, but with favorable computational expenses compared with the full 3D solution. The field data set contains 200 soundings, and we perform a 3D inversion on the full survey. A 24-sounding section is then selected for the 2.5D inversion. The 2.5D inversion result finds resistivity features similar to the 3D inversion result at the selected profile. Hence, we conclude that the presented implementations are capable of handling relatively large TEM surveys on modern computational platforms. This could be smaller subsets of production-size surveys where 2D and 3D effects are pronounced.

Imaging geological layers beneath lakes, rivers, and shallow seawater provides detailed information critical for hydrological modeling, geologic studies, contaminant mapping, and more. However, significant engineering and interpretation challenges have limited the applications, preventing widespread adoption in aquatic environments. We have developed a towed transient electromagnetic (tTEM) system for a new, easily configurable floating, transient electromagnetic instrument (FloaTEM) capable of imaging the subsurface beneath both freshwater and saltwater. Based on the terrestrial tTEM instrument, the FloaTEM system utilizes a similar philosophy of a lightweight towed transmitter with a trailing offset receiver pulled by a small boat. The FloaTEM system is tailored to the specific freshwater or saltwater application as necessary, allowing investigations down to 100 m in freshwater environments and up to 20 m on saline waters. Through synthetic analysis, we show how the depth of investigation of the FloaTEM system greatly depends on the resistivity and thickness of the water column. The system has been successfully deployed in Denmark for a variety of hydrologic investigations, improving the ability to understand and model processes beneath water bodies. We present two freshwater applications and a saltwater application. Imaging results reveal significant heterogeneities in the sediment types below the freshwater lakes. The saline water example demonstrates that the system is capable of identifying and distinguishing clay and sand layers below the saline water column.

Airborne time-domain electromagnetic surveys produce extremely large data sets with thousands of line kilometers of data and millions of possible models to explain the data. Inversion of such data sets to obtain the resistivity structures of the subsurface is computationally intensive and involves calculation of a significant number of forward and derivative responses for solving the least-squares inverse problem. The flight altitude of the airborne system needs to be included in the modeling, which adds further complexity. We propose to integrate neural networks in a damped iterative least-squares inversion framework to expedite the inversion process. We train two separate neural networks to predict the forward responses and partial derivatives independently for a broad range of resistivity structures and flight altitudes. Data inversion is not only used for producing the final subsurface models but also used during data processing, or to produce intermediate results during a survey. With these purposes in mind, we provide three inversion schemes with a tunable balance between computational time and modeling accuracy: (1) numerical forward responses used initially in combination with neural network derivatives, and the derivatives switched to a numerical solution in final iterations, (2) numerical forward responses in combination with neural network derivatives used throughout the inversion, and (3) only neural network forward responses and derivatives used in inversion. Experiments on field data find that we improve inversion speed without any loss in modeling accuracy with our first approach, whereas the second scheme gives a significant speedup at the cost of minor and often acceptable deviations in the inversion results from the conventional nonlinear inversion. The last approach is the fastest and captures the overall resistivity structures quite well. Therefore, depending on the modeling accuracy, inversion speedup factors of up to 50 are realized by using the proposed schemes.

The nature of Yellowstone National Park’s plumbing system linking deep thermal fluids to its legendary thermal features is virtually unknown. The prevailing concepts of Yellowstone hydrology and chemistry are that fluids reside in reservoirs with unknown geometries, flow laterally from distal sources and emerge at the edges of lava flows. Here we present a high-resolution synoptic view of pathways of the Yellowstone hydrothermal system derived from electrical resistivity and magnetic susceptibility models of airborne geophysical data. Groundwater and thermal fluids containing appreciable total dissolved solids significantly reduce resistivities of porous volcanic rocks and are differentiated by their resistivity signatures. Clay sequences mapped in thermal areas and boreholes typically form at depths of less than 1,000 metres over fault-controlled thermal fluid and/or gas conduits. We show that most thermal features are located above high-flux conduits along buried faults capped with clay that has low resistivity and low susceptibility. Shallow subhorizontal pathways feed groundwater into basins that mixes with thermal fluids from vertical conduits. These mixed fluids emerge at the surface, controlled by surficial permeability, and flow outwards along deeper brecciated layers. These outflows, continuing between the geyser basins, mix with local groundwater and thermal fluids to produce the observed geochemical signatures. Our high-fidelity images inform geochemical and groundwater models for hydrothermal systems worldwide. This work was supported by the US Geological Survey Mineral and Energy Resources and Volcanic Hazards Programs, NSF grant no. EPS-1208909 and the University of Wyoming Office of Research and Economic Development. Published version Authored by U.S. government employees and therefore in the public domain.

SUMMARY Airborne systems collecting transient electromagnetic data are able to gather large amounts of data over large areas in a very short time. These data are most often interpreted through 1-D inversions, due to the availability of robust, fast and efficient codes. However, in areas where the subsurface contains complex structures or large conductivity contrasts, 1-D inversions may introduce artefacts into the models, which may prevent correct interpretation of the results. In these cases, 2-D or 3-D inversion should be used. Here, we present a 2.5-D inversion code using 3-D forward modelling combined with a 2-D model grid. A 2.5-D inversion is useful where the flight lines are spaced far apart, in which case a 3-D inversion would not add value in relation to the added computational cost and complexity. By exploiting the symmetry of the transmitter and receiver system we are able to perform forward calculations on a reduced 3-D mesh using only half the domain transecting the centre of the transmitter and receiver system. The forward responses and sensitivities from the reduced 3-D mesh are projected onto a structured 2-D model grid following the flight direction. The difference in forward calculations is within 1.4 per cent using the reduced mesh compared to a full 3-D solution. The inversion code is tested on a synthetic example constructed with complex geology and high conductivity contrasts and the results are compared to a 1-D inversion. We find that the 2.5-D inversion recovers both the conductivity values and shape of the true model with a significantly higher accuracy than the 1-D inversion. Finally, the results are supported by a field case using airborne TEM data from the island of Mayotte. The inverted flight line consisted of 418 soundings, and the inversion spent an average of 6750 s per iteration, converging in 16 iterations with a peak memory usage of 97 GB, using 18 logical processors. In general, the total time of the 2-D inversions compared to a full 3-D inversion is reduced by a factor of 2.5 while the memory consumption was reduced by a factor of 2, reflecting the half-mesh approach.

High-bandwidth magnetic data are normally distorted by ubiquitous 50- or 60-Hz noise from powerlines and similar sources. The powerline noise can be orders of magnitude larger than the magnetic signal from targets and must be culled from data sets prior to interpretation. Suppression of the powerline noise by simple filtering can result in artifacts and an unacceptable reduction in resolution of ground-based and unmanned aerial vehicle magnetic surveys. Removal approaches such as those based on Biot-Savart modeling are sensitive to the estimated position of the powerline systems, in addition to their limited applicability due to the requirement of a DC source. Moreover, the powerline noise in data acquired from a moving platform is inherently nonstationary and removal techniques must be specifically developed with this in mind. We propose a model-based method that does not rely on a priori knowledge of the powerline system by fitting and subtracting a set of sinusoids to the data. These sinusoids are computed on small windows of data, tied together with regularization terms within the fitting process to reduce discontinuities between segments. We further incorporate powerline frequency as a nonlinear parameter, allowing for fluctuations in the fundamental frequency as loads on the power grid change. Through synthetic and field examples, we show that periodic noise can be reliably removed automatically without the need for filtering or significant alterations of the frequency content. Powerline noise is reduced by over 98% in the field example.

Since the 1960s, a deep groundwater system in Wright Valley, Antarctica, has been the hypothesized source of brines to hypersaline Don Juan Pond and Lake Vanda, both of which are rich in calcium and chloride. Modeling studies do not support other possible mechanisms, such as evaporative processes, that could have led to the current suite of ions present in both waterbodies. In 2011 and 2018, an airborne electromagnetic survey was flown over Wright Valley to map subsurface resistivity (down to 600 m) in exploration of liquid water. The surveys revealed widespread unfrozen brine in the subsurface near Lake Vanda, Don Juan Pond, and the North Fork of Wright Valley. While our geophysical survey can neither confirm nor deny deep groundwater connectivity between Lake Vanda and Don Juan Pond, it does point to the potential for deep valley-wide brine, likely within the Ferrar Dolerite formation.

For several decades, induced polarization (IP) effects on transient electromagnetic (TEM) responses have been observed. These effects can manifest as late-time negative transients or as rapidly decaying curves and are usually associated with highly polarizable bodies. If neglected, IP effects can lead to erroneous resistivity models. Recent work allows IP effects to be incorporated into the inversion of TEM data on a more routine basis. In a recent field survey in western Tanzania, strongly IP-affected TEM signals are observed using a towed-transient electromagnetic (tTEM) system. The survey have been carried out to locate drinking water resources in a weathered regolith setting. In these settings, an inversion of tTEM data using a resistivity-only forward model (i.e., IP neglected) cannot fit the data and severely limits the value of the TEM data for hydrogeologic interpretation. To account for IP effects, we have applied a modified version of the Cole-Cole model called the maximum phase angle (MPA) model to invert IP-affected tTEM data. The MPA model incorporates four inversion model parameters: resistivity ([Formula: see text]), MPA ([Formula: see text]), relaxation time ([Formula: see text]), and frequency exponent ([Formula: see text]). The MPA model fits the data well and improves the reliability of the resistivity model. In much of the surveyed region, the inverted models using MPA display a three-layer system consisting of an upper resistive laterite layer of varying thickness and an intermediate polarizable conductive unit overlying more resistive weathered basement rocks. The conductive polarizable layer is interpreted as a chemically weathered saprolite separating the surficial and deeper aquifers. Overall, tTEM inversion results provide a local understanding of groundwater systems, especially in such regions with very limited subsurface knowledge.

International audience; On 30 September 2017, an Air France Airbus A380-800 suffered a failure of its fourth engine while over Greenland. This failure resulted in the loss of the engine fan hub, fan blades and surrounding structure. An initial search recovered 30 pieces of light debris, but the primary part of interest, a ~220 kg titanium fan hub, was not recovered because it had a different fall trajectory than the light debris, impacted into the ice-sheet's snow surface, and was quickly covered by drifting snow. Here we describe the methods used for the detection of the fan hub and details of the field campaigns. The search area included two crevasse fields of at least 50 snow-covered crevasses 1 to ~30 m wide with similar snow bridge thicknesses. After 21 months and six campaigns, using airborne synthetic aperture radar, ground-penetrating radar, transient electromagnetics and an autonomous vehicle to survey the crevasse fields, the fan hub was found within ~1 m of a crevasse at a depth of ~3.3 to 4 m and was excavated with shovels, chain saws, an electric winch, sleds and a gasoline heater, by workers using fall-arrest systems.

Surface nuclear magnetic resonance (NMR) is emerging as a competitive method for aquifer exploration due to its direct sensitivity to subsurface water, but the method still has several shortcomings, for example, a signal-to-noise ratio that is often poor, long survey times, and bulky equipment. We have developed Apsu, a new surface NMR system designed for near-surface groundwater investigations. It provides several features such as a compact transmitter unit, separated, small receiver coils, wireless connections between multiple receivers, quasi-zero dead time, and robust phase determination. The transmitter unit is powered by a lightweight generator, and it drives a triangular current in an untuned [Formula: see text] transmitter coil. The peak current of the triangular waveform is up to 145 A, with an effective peak current of 105 A at a Larmor frequency of 2 kHz, corresponding to a 30 m depth of investigation. The frequency and amplitude in each half-oscillation of the transmit pulses can be modulated independently, which gives great flexibility in the pulse design. The receiver uses low-noise preamplifiers and multiple receivers linked to a central unit through Wi-Fi. The use of small receiver coils and wireless connections to multichannel receivers greatly improves the layout configuration flexibility and survey efficiency. The performance of the system under field conditions is demonstrated with high-quality data collected near Silkeborg, Denmark, using on-resonance and numerically optimized modulation pulses.

Imagining geological layers beneath lakes, rivers, and shallow seawater provides detailed information critical for hydrological modelling, geologic studies, contaminant mapping, and more. However, significant engineering and interpretation challenges have limited the applications, preventing widespread adoption in aquatic environments. We have developed a towed transient electromagnetic (tTEM) system to a new, easily configurable floating, transient electromagnetic instrument (FloaTEM) capable of imaging the subsurface beneath both fresh and saltwater water bodies. Based on the terrestrial tTEM instrument, the FloaTEM system utilizes a similar philosophy of a lightweight towed transmitter with a trailing, offset receiver, pulled by a small boat. The FloaTEM system is tailored to the specific fresh or saltwater application as necessary, allowing investigations down to 100 m in freshwater environments, and up to 20 m on saline waters. Through synthetic analysis we show how the depth of investigation of the FloaTEM system greatly depends on the resistivity and thickness of the water column. The system has been successfully deployed in Denmark for a variety of hydrologic investigations, improving the ability to understand and model processes beneath water bodies. We present two freshwater applications and a saltwater application. Imaging results reveal significant heterogeneities in the sediment types below the freshwater lakes. The saline water example demonstrates that the system is capable to identify and distinguish clay and sand layers below the saline water column.

SUMMARYAirborne electromagnetics (EM) is a geophysical tool well suited to mapping glacial and hydrogeological structures in polar environments. This non-invasive method offers significant spatial coverage without requiring access to the ground surface, enabling the mapping of geological units to hundreds of metres depth over highly varied terrain. This method shows great potential for large-scale surveys in polar environments, as common targets such as permafrost, ice and brine-rich groundwater systems in these settings can be easily differentiated because of their significant contrasts in electrical properties. This potential was highlighted in a 2011 airborne EM survey in the McMurdo Dry Valleys that mapped the existence of a large-scale regional groundwater system in Taylor Valley. A more comprehensive airborne EM survey was flown in November 2018 to broadly map potential groundwater systems throughout the region. Data collected in this survey displayed significant perturbations from a process called induced polarization (IP), an effect that can greatly limit or prevent traditional EM workflows from producing reliable geological interpretations. Here, we present several examples of observed IP signatures over a range of conditions and detail how workflows explicitly designed to handle IP effects can produce reliable geological interpretations and data fits in these situations. Future polar EM surveys can be expected to encounter strong IP effects given the likely presence of geological materials (e.g. ice and permafrost) that can accentuate the influence of IP.

Previous studies of the lakes of the McMurdo Dry Valleys have attempted to constrain lake level history, and results suggest the lakes have undergone hundreds of meters of lake level change within the last 20,000 years. Past studies have utilized the interpretation of geologic deposits, lake chemistry, and ice sheet history to deduce lake level history, however a substantial amount of disagreement remains between the findings, indicating a need for further investigation using new techniques. This study utilizes a regional airborne resistivity survey to provide novel insight into the paleohydrology of the region. Mean resistivity maps revealed an extensive brine beneath the Lake Fryxell basin which is interpreted as a legacy groundwater signal from higher lake levels in the past. Resistivity data suggests that active permafrost formation has been ongoing since the onset of lake drainage, and that as recently as 1,000–1,500 yr BP, lake levels were over 60 m higher than present. This coincides with a warmer than modern paleoclimate throughout the Holocene inferred by the nearby Taylor Dome ice core record. Our results indicate mid to late Holocene lake level high stands which runs counter to previous research finding a colder and drier era with little hydrologic activity throughout the last 5,000 years.

The mineral exploration industry is again in a boom to provide new resources of critical raw materials as well as base and precious metals. This is evident from the globally increased expenditure reported for 2018 (International Mining 2018). Global demand towards green technologies requires sustainable flow of primary raw materials into the so‐called whole value chain. Without exploring in new areas (greenfields), the chance of finding giant deposits or providing fresh resources to the market and sustaining the value‐chain loop would be minimal. However, it is convenient in the short term to explore in brownfield areas and near mines to make use of existing infrastructures and to avoid new environmental footprints. In such circumstances, the mineral exploration industry is further challenged to not only provide high‐quality and high‐resolution deep‐targeting solutions but also to do it in a cost‐ and environmentally effective way. This is particularly significant in the European Union (EU) and in regions with thick cover, requiring new and much more sensitive exploration technologies for direct deposit targeting and geological characterization. In addressing these, there are several research and innovation initiatives worldwide trying to tackle some of these challenges like, to list a few, Smart Exploration in the EU and Metal Earth in Canada. There are also a number of cooperative research centre (CRC) projects in Australia as well as in Africa where favourable geology exists but exploration is challenged to find new “tier 1” deposits at depth (+500 m). This Special Issue of Geophysical Prospecting contains 18 articles and is coordinated by a number of experts involved in the Smart Exploration project (Malehmir et al. 2019). Eight of the included articles are from the project itself, and highlight the progress being made in this topic with a particular focus on legacy data and the value and potential such data have for deep‐targeting and high‐resolution imaging. The Special Issue, through showcases, reports the remarkable progress being made in overcoming the perceived high exploration cost for mineral exploration particularly for deeper targets. In the following, we provide a brief introduction to the papers included in this Special Issue. The included articles are divided into three main categories: legacy and exploration data, innovative solutions and state‐of‐the‐art equipment. Interested readers are also encouraged to check the three earlier special volumes on similar topics by Eaton, Milkereit and Salisbury (2003 and the references therein), Malehmir et al. (2012 and the references therein) and Buske, Bellefleur and Malehmir (2015 and the references therein).

The induced polarization (IP) response in airborne electromagnetic data has recently received attention due to its potential significance for mineral exploration and envi-ronmental applications, while also holding the prospect of improved geophysical models. A typical IP response produces negative transients in the late time gates. How-ever, under certain circumstances, the presence of overly steep decays in themselves indicate the presence of chargeable material in the subsurface, i.e. where the chargeability is not strong enough to reverse the sign above the noise level, although it still decreases the sig-nal. In this contribution, we analyse a survey in the Howards East District in Northern Territory, Australia, and synthetic data. After a standard processing and removal of all noisy and negative data, we proceeded with a standard inversion that resulted in poor fit and unrealistic high resistivity in deeper layers in parts of the survey. Next, we inverted the data with a dispersive earth model, i.e. including the IP parameters. In the parts of the survey where the data could be fitted well with the “resistivity only” inversion the models changed minimally. In the remaining part, mostly with overly steep decays, the inverted models show chargeable, relatively shallow layers, the unrealistic high resistivity was not present anymore and in general, the data residuals dropped to be within the uncertainty of the data. We further analysed the data, specifically: 1) the sound-ings linked to chargeable areas; 2) the loss of information due to neglecting the negative or late time data with synthetic models; and 3) we explored the ability of the IP inversion models to recover the moderately chargeable layers. In conclusion, a large-scale airborne IP inversion was executed without any specific processing. Until now a time-consuming specific processing seemed to be a necessary step towards a successful IP inversion with airborne data.

This paper presents the results of airborne electromagnetic induced polarisation inversions using the Maximum Phase Angle (MPA) model for a helicopter time domain survey in the Quadrilátero Ferrífero area, Minas Gerais State (MG), Brazil. The inversions were conducted using a laterally constrained robust scheme, in order to decrease the difficulties to recover the multi-parametric model in a very ill-posed inverse problem, often found in induced polarisation studies. A set of six flight lines over the Lamego gold mine mineralised structure were inverted using the MPA re-parameterisation of the Cole–Cole model and also the classical resistivity-only parameterisation, in order to understand the implications of the induced polarisation effect in the data and, consequently, in the resistivity model. A synthetic study was also conducted, seeking to understand what to expect from the resistivity-only inversions in the real data. According to borehole lithological data and previous structural knowledge from the literature, the results from the Maximum Phase Angle approach indicate an important chargeable body that seems to be in good agreement with a sulfide enriched carbonaceous/graphite and altered mafic unities, which are important markers for the gold mineralisation.

The signal level and shape of induced polarization responses are significantly affected by the current pulse duration and waveform. If not accounted for, this data dependency on the current will propagate trough the inversion to results rendering unquantifiable subsurface models. While this problem has been addressed in full-response induced polarization modelling, questions remain as to how to accurately retrieve quantitative induced polarization inversion models from the types of apparent integral chargeability data often used in data interpretation. Although several methodologies have been proposed for handling and inverting apparent resistivity and integral chargeability, these cannot compensate for the data dependency on the current waveform and pulse duration. This paper presents a novel inversion method for such data. The method considers current waveform and receiver transfer functions for retrieving quantitative IP models unbiased by transmitter waveform. The method uses the constant phase angle model, expressed in terms of the medium resistivity and phase. Specifically, four field data sets for the same profile but with different 100 per cent duty cycle pulse durations (4, 2, 1 and 0.5 s) serve as examples of data sets giving models dependant on current waveform when inverted with standard approaches. The novel inversion method presented here gives quantifiable models independent on the current waveform and pulse duration. These results resemble models retrieved with existing, full-response induced polarization inversions. The results still contain some degree of uncertainty in relation to underlying assumptions and parametrizations. Managing this source of uncertainty is considered in terms of full-response induced polarization inversions with constant phase angle and maximum phase angle inversions.

Limited knowledge of local groundwater systems often results in the failure of boreholes to yield water of the required quantity and quality. This is particularly problematic in the developing world, where financial resources are often limited, and failed wells represent a significant financial burden. To enhance understanding of local hydrological systems, noninvasive geophysical methods can aid the understanding of hydrogeological structures and identification of groundwater sources needed to optimize siting of wells. Here, we highlight the utility of a relatively new towed-transient electromagnetic system, called tTEM. This system is a rapidly deployable mobile geophysical method well-suited to cost-efficient characterization of local-to-regional groundwater systems. Results from tTEM surveys conducted in two refugee camps and several host communities in western Tanzania demonstrate the capability of the method to characterize shallow aquifer systems with high lateral and vertical resolution, with data collection typically exceeding 15 to 20 line-kilometers (km) per day. This work focuses on tTEM's ability to provide semiquantitative insights into regional hydrogeological settings when supporting data required for more rigorous interpretation/modeling is lacking. The system provided useful data within communities with low density of electrification and near buildings with metal roofs and walls. tTEM-derived resistivity profiles were correlated with limited local borehole lithologic information to develop conceptual models of the local groundwater systems. These models were used to successfully guide the siting of a production well and to identify future drilling targets in the refugee camps and surrounding communities.

Inversion of large-scale time-domain electromagnetic surveys are computationally expensive and time consuming. Deterministic or probabilistic inversion schemes usually require calculations of forward responses, and often thousands to millions of forward responses are computed. We propose a machine learning based forward modelling approach as a computationally feasible alternative to approximate numerical forward modelling where a neural network is employed to model the relationship between the resistivity models and corresponding forward responses. For training of the neural network, we generated forward responses using conventional numerical algorithm for 93,500 resistivity models derived from different surveys conducted in Denmark representing typical resistivities of sedimentary geological layers. The input resistivity models and the network target outputs, i.e. forward responses, are scaled using a novel normalization strategy to ensure each gate is equally prioritized. The performance of the network is evaluated on two test datasets consisting of 8942 resistivity models by comparing the forward responses generated by the neural network and the conventional algorithm. We also measure the performance for the time derivatives of forward responses, i.e. dB/dt, by incorporating a system response. The results show that the proposed strategy is at least 13 times faster than commonly used accurate modelling methods and achieves an accuracy of 98% within 3% relative error, which is comparable to data uncertainty. Additional experiments on surveys from two other continents show that the results generalize in similar geological settings. Thus, under certain geological constraints, the proposed methodology may be incorporated into the pre-existing inversion structures, allowing for significantly faster inversion of large datasets.

The nature of Yellowstone National Park's plumbing system linking deep thermal fluids to its legendary thermal features is virtually unknown. The prevailing concepts of Yellowstone hydrology and chemistry are that fluids reside in reservoirs with unknown geometries, flow laterally from distal sources and emerge at the edges of lava flows

Geophysical modelling and data inversion are important tools for interpreting the physical properties of Earth's subsurface. Solving the inverse problem involves several computational steps and is generally a time consuming task. Artificial neural networks have the potential to speed up large computations. Such networks provide the means to model the relationship between the inputs and outputs without needing to know the physical model of the underlying problem. There are two main aspects that affect the performance of neural networks: optimization of network architecture and pre-processing of data. In this article, we investigate several traditional pre-processing techniques including the min-max scaling, z-score scaling, and the logarithmic transform scaling, and propose some novel data pre-processing approaches for the 1-D forward modelling of time-domain electromagnetic data based on signal characteristics. We evaluate the performance of the conventional and the proposed pre-processing methods against a 3% relative error metric, which corresponds to the typical data uncertainty, to show that forward data pre-processing has significant effect on the performance of neural networks. The proposed gate-wise min-max scaling achieves the best performance with 96% of gates within a 3% relative error, while the commonly used logarithmic transform results only in 75% of gates within a 3% relative error. We provide insights into how various pre-processing methods affect the performance of these networks and recommend optimal pre-processing strategies that may be used where similar data content is encountered to achieve superior performance. Finally, we show the effect of forward modelling accuracy in inverse modelling.

Worldwide, soil contamination due to industrial activities is a major issue. One method for remediation of contaminated sites is in situ chemical oxidation, where an oxidizing agent is injected into the contaminated soil. Normally, monitoring wells are established in the remediation area for tracking the oxidizing agent. However, wells only provide point information of the injectant spread. This issue can be addressed using cross‐borehole resistivity and induced polarization tomography, by mapping the electrical properties in the entire remediation volume and by deriving, through petrophysical relations, the hydraulic properties of the medium. Here we present a proof‐of‐concept study, performed over one year as part of a larger remediation project, where resistivity and time‐domain induced polarization data were acquired among 10 boreholes, before and after two rounds of injection of oxidizing agents. The time‐lapse resistivity models, obtained through a focusing inversion scheme that favours compact time‐lapse changes, clearly show the oxidizing agent spread as highly conductive anomalies and confirmed by water conductivity measurements in boreholes. The time‐lapse inversions also show spatial variability in the injectant spread, with some areas not reached. The induced polarization data quality decreased significantly just after the injection rounds, because of the decrease in resistivity and induced polarization signal level, so that induced polarization time‐lapse inversions were not feasible. However, the induced polarization data were used for background characterization and to estimate permeability. In particular, there is a good match between the imaged low‐permeability zones and the areas in which the injectant did not spread, identified by the time‐lapse resistivity inversions. Furthermore, geological samples confirm the presence of fine‐grained sediments in the estimated low‐permeability zones. While time‐lapse resistivity tomography may be used for documenting the injectant spread, induced polarization permeability estimates prior to injection can be used to better tailor the remediation in terms of dimension and location of injection filters.

The transient electromagnetic (TEM) method is a non-invasive geophysical tool well-suited for subsurface imaging in cold and polar regions, where common targets are associated with strong contrasts in electrical resistivity. By imaging the electrical properties of the subsurface, the TEM methods can discriminate between geological units such as frozen ground (permafrost), fresh/saline groundwater systems, and bedrock/glacier ice. In this study, we compare TEM data acquired with ground-based and airborne TEM systems. We demonstrate the mapping capabilities of these two approaches in high latitude polar environments with datasets from Taylor Glacier, Lake Vanda, and Canada Glacier in the McMurdo Dry Valleys of Antarctica. The results show a high consistency between the airborne and ground-based TEM data, both with a high resolution and a deep penetration depth down to hundreds of meters due to the resistive background material, which makes both approaches capable of mapping hydrological systems and identifying the base of glaciers. The airborne TEM approach offers an unmatched spatial data coverage in difficult terrain and a far improved lateral resolution compared to the static ground-based system. The ground-based TEM system offers the possibility for using larger transmitter coils and longer stacking times and therefore has potential for reaching deeper penetration depths. The ground-based TEM approach is hence a valuable tool that can provide consistent imaging results while also being far more accessible in terms of cost and field logistics compared to an airborne TEM campaign.

Summary Understanding the top 100 m of the near subsurface using geophysical sensors has gained momentum over the last couple of decades but we are also in great need to better understand this region of the subsurface. In recent years, there has been several advancements in new geophysical sensors greatly pushed by new advanced electronic, powerful computers and integrated data processing algorithms. This has enabled us to move from single point 1D measurements to full 3D coverage. Specially EM sensors have become much more applicable for solving real world problems, thanks to the integration of data processing algorithms with instrumentation. One of the most recent and advanced tools that has created big difference in near-surface mapping is the tTEM system. Using the tTEM system one can achieve comprehensive continuous images of the sub surface’s electrical properties — extremely valuable information to map water flow pathways for many different applications. Also new geoelectrical sensors can be efficiently used to monitor the dynamic processes in the subsurface. The potential of TEM sensors can be fully exploited to monitor the groundwater table in water deficit regions. Machine learning algorithms are paving the way to handle the huge amount of data in real time.

Summary Locating safe drinking water sources in remote settings can be a challenging task, especially in regions where one has little to no pre-existing knowledge of local groundwater systems. In these cases, it is common that boreholes are drilled that fail to deliver on desperately needed water resources. Non-invasive geophysical approaches show great promise to address this problem — capable of informing conceptual models of local groundwater systems and helping guide siting of wells. In this work, we demonstrate the utility of a towed transient electromagnetic system for rapid cost-efficient mapping of groundwater systems in remote conditions. Results from two campaigns in Tanzania and South Africa are presented to highlight the value the system can bring to well-siting workflows.

SUMMARYWe present a new algorithm for 3-D forward modelling and spectral inversion of resistivity and time-domain full-decay induced polarization (IP) data. To our knowledge, all algorithms available for handling 3-D spectral inversion of full-decay IP data use a time-domain approximation to Poisson's equation in the forward response. To avoid this approximation, we compute the response in the frequency domain solving the full version of Poisson's equation for a range of frequencies (10–8–104 Hz) and then transform the response into the time domain, where we account for the transmitted current waveform. Solving Poisson's equation in 3-D is computationally expensive and in order to balance accuracy, time, and memory usage we introduce the following: (1) We use two separate meshes for the forward response and the model update, respectively. The forward mesh is an unstructured tetrahedral mesh allowing for local refinements whereas the model (inversion) mesh is a node-based structured mesh, where roughness constraints are easily implemented. By decoupling the two meshes, they can be tuned for optimizing the forward accuracy and the inversion resolution, independently. (2) A singularity removal method known from resistivity modelling has been adapted to the complex IP case and is applied to minimize the numerical errors caused by the fast changing potential close to the source electrodes. The method includes splitting the potential field into a primary part (response of a homogenous background) and a secondary part (from the anomalies). Two different forward meshes are then used to compute the forward response: a dense mesh for the primary potential field (only computed once for each frequency) and a coarser mesh for the secondary potential field (computed in each iteration step of the inversion). With this method, the singularity is minimized and the memory usages is decreased significantly at the same time. (3) Finally, we are sparsing (downsampling) the Jacobian matrix based on a threshold value of the normalized sensitivity. The Jacobian computation is performed by time-transforming the frequency-domain Jacobian obtained through the adjoint method. The Jacobian downsampling is carried out before the time-transform in the frequency domain, thus avoiding the time-transformation of the Jacobian elements with negligible sensitivity. We invert resistivity data and all IP time-gates simultaneously and use the Gauss–Newton model update to minimize the L2 misfit function. We invert the resistivity data and all IP time-gates simultaneously and use the Gauss–Newton model update to minimize the L2 misfit function. We demonstrate the performance of our inversion approach with a synthetic data example with 3-D anomalies and a field example, where lithology logs verify the results. The data sets contain 1256 quadrupole measurements with 33 IP time-gates each. The inversions results show good data fits and model retrieval. The inversion takes approximately one hour per iteration using four CPUs. With this speed and accuracy, we believe this modelling and inversion approach will be a strong tool for 3-D spectral inversion of resistivity and full-decay IP field data for both surface and borehole applications.

There is a growing need for detailed investigation of the top 30–50 m of the subsurface, which is critical for infrastructure, water supply, aquifer storage and recovery, farming, waste deposits, and construction. Existing geophysical methods are capable of imaging this zone; however, they have limited efficiency when it comes to creating full 3D images with high resolution over dozens to hundreds of hectares. We have developed a new and highly efficient towed transient electromagnetic (tTEM) system, which is capable of imaging the subsurface up to depth of 70 m at a high resolution, horizontally and vertically. Towed by an all-terrain vehicle, the system uses a [Formula: see text] transmitter coil and has a [Formula: see text]-component receiver placed at 9 m offset from the transmitter. The tTEM uses dual transmitter moment (low and high moment) measurement sequence to obtain the early and late time gates corresponding to shallow and deep information about the subsurface layers. The first bias-free gate is as early as [Formula: see text] from beginning of the ramp ([Formula: see text] after end of ramp). Data are processed and inverted using methods directly adopted from airborne electromagnetics. The system has been successfully used in Denmark for various purposes, e.g., mapping raw materials, investigating contaminated sites, and assessing aquifer vulnerability. We have also used the tTEM system in the Central Valley of California (United States) for locating artificial recharge sites and in the Mississippi Delta region, to map complex subsurface geology in great detail for building hydrogeologic models.

One of the primary shortcomings of the standard surface nuclear magnetic resonance (NMR) measurement, called the free-induction decay (FID), is the uncertainty about the link between the signal’s time dependence and the geometry of the pore space. Ideally, the FID signal’s time dependence, described by the parameter T2*, carries an intimate link to the geometry of the pore space allowing robust estimation of pore-size and permeability. However, T2* can also be strongly influenced by background magnetic field (B0) inhomogeneity, which can mask the link to pore geometry. To improve the utility of surface NMR FID measurements, we investigate whether complex inversion of surface NMR data can be used to provide insight into the link between T2* and T2 (the parameter carrying the link to pore geometry). Synthetic and field measurements are presented to demonstrate that an alternative forward modelling approach that involves direct modelling of relaxation during pulse (RDP) effects can help constrain the relationship between T2* and T2. Complex inversions are performed using forward models that include RDP for varying magnitudes of B0 inhomogeneity (consistent with observed T2* values) and it is observed that satisfactory data fits can only be obtained given reliable T2 estimates. Thus providing insight into the T2*-T2 relationship. We aim to demonstrate that an alternative forward modelling approach may help improve the utility of FID measurements for estimation of pore-scale properties.

Surface NMR is a unique tool in groundwater geophysics due to its ability to directly measure the depth-resolved water content in the near sub-surface and provide depth-resolved estimates of the hy...

Adiabatic half-passage (AHP) pulses show great promise for significantly enhancing the signal-to-noise ratio of the surface nuclear magnetic resonance (NMR) free-induction decay measurement. Performing an AHP requires that the frequency sweep terminates when the transmit frequency is equal to the Larmor frequency, a condition that demands accurate knowledge of the true Larmor frequency. If the frequency sweep is terminated at an incorrect frequency, i.e., with an unknown offset between the transmit and Larmor frequency at the end of the pulse, the net excitation is affected and it can differ from that predicted by modeling that assumes a 0 Hz offset at the end of the sweep. Surface NMR surveys using a traditional single-frequency pulse have previously been shown to display degraded performance in the presence of an uncertain Larmor frequency estimate; the AHP pulse is also likely susceptible to such degraded performance. To ensure that reliable results can be produced by AHP pulses in the presence of an uncertain Larmor frequency estimate, we have developed an approach that adapts the frequency-cycling scheme for use with AHP pulses. We hypothesize that data collected using two similar AHP pulses, each with the exact same frequency sweep but where one sweeps toward the Larmor frequency from higher frequencies and the other from lower frequencies, can be stacked in such a manner that the impact of an unknown frequency offset is significantly reduced. We present synthetic and field results to demonstrate that frequency-cycling AHP pulse surface NMR data can ensure reliable performance even in the presence of an uncertain Larmor frequency estimate.

The development of multichannel instrumentation was a significant step forward for surface nuclear magnetic resonance (NMR). Multichannel instruments allow data to be recorded on multiple receivers simultaneously, thus facilitating the exploitation of Wiener filtering techniques that provide significant signal-to-noise increases and allow two- and three-dimensional images of the subsurface properties to be produced. When working in challenging environments (e.g. forested/brushy terrain), difficult noise conditions, or when using complicated survey designs it can become quite cumbersome to deploy multiple coils, which often require substantial lengths of cable to be deployed. As such, it would be advantageous if the dimensions of typical receive coils could be greatly reduced from the current standards (~25–100 m). The use of small receive coils would lead to more rapid survey deployment and may advance the utility of methods requiring multiple receivers. The objectives of this work are two-fold. The first aims to quantify limits on the feasible dimensions of small receive coils in surface NMR, aiming to provide an estimate of the minimum effective area of a functional surface NMR receiver. The second aims to demonstrate that the use of multiple additional small receive coils (when used in conjunction with the standard large coincident transmit/receive coil) can help to improve the resolution of estimated water content and relaxation time depth profiles. Synthetic results are presented to quantify lower effective area limits and to demonstrate potential resolution improvements provided by small receivers. The feasibility of a small receiver (400 m2 and 200 m2) is demonstrated in a field setting.

Accurate modelling of the conductivity structure of mineralisations can often be difficult. In order to remedy this, a parametric approach is often used. We have developed a parametric thin-sheet code, with a variable overburden. The code is capable of performing inversions of time-domain airborne electromagnetic data, and it has been tested successfully on both synthetic data and field data. The code implements an integral solution containing one or more conductive sheets, buried in a half-space with a laterally varying conductive overburden. This implementation increases the area of applicability compared to, for example, codes operating in free space, but it comes with a significant increase in computational cost. To minimise the cost, the code is parallelised using OpenMP and heavily optimised, which means that inversions of field data can be performed in hours on multiprocessor desktop computers. The code models the full system transfer function of the electromagnetic system, including variable flight height. The code is demonstrated with a synthetic example imitating a mineralisation buried underneath a conductive meadow. As a field example, the Valen mineral deposit, which is a graphite mineral deposit located in a variable overburden, is successfully inverted. Our results match well with previous models of the deposit; however, our predicted sheet remains inconclusive. These examples collectively demonstrate the effectiveness of our thin-sheet code.

At contaminated sites, knowledge about geology and hydraulic properties of the subsurface and extent of the contamination is needed for assessing the risk and for designing potential site remediation. In this study, we have developed a new approach for characterizing contaminated sites through time-domain spectral induced polarization. The new approach is based on: (1) spectral inversion of the induced polarization data through a reparametrization of the Cole–Cole model, which disentangles the electrolytic bulk conductivity from the surface conductivity for delineating the contamination plume; (2) estimation of hydraulic permeability directly from the inverted parameters using a laboratory-derived empirical equation without any calibration; (3) the use of the geophysical imaging results for supporting the geological modelling and planning of drilling campaigns. The new approach was tested on a data set from the Grindsted stream (Denmark), where contaminated groundwater from a factory site discharges to the stream. Two overlapping areas were covered with seven parallel 2-D profiles each, one large area of 410 m × 90 m (5 m electrode spacing) and one detailed area of 126 m × 42 m (2 m electrode spacing). The geophysical results were complemented and validated by an extensive set of hydrologic and geologic information, including 94 estimates of hydraulic permeability obtained from slug tests and grain size analyses, 89 measurements of water electrical conductivity in groundwater, and four geological logs. On average the IP-derived and measured permeability values agreed within one order of magnitude, except for those close to boundaries between lithological layers (e.g. between sand and clay), where mismatches occurred due to the lack of vertical resolution in the geophysical imaging. An average formation factor was estimated from the correlation between the imaged bulk conductivity values and the water conductivity values measured in groundwater, in order to convert the imaging results from bulk conductivity to water conductivity. The geophysical models were actively used for supporting the geological modelling and the imaging of hydraulic permeability and water conductivity allowed for a better discrimination of the clay/lignite lithology from the pore water conductivity. Furthermore, high water electrical conductivity values were found in a deep confined aquifer, which is separated by a low-permeability clay layer from a shallow aquifer. No contamination was expected in this part of the confined aquifer, and confirmation wells were drilled in the zone of increased water electrical conductivity derived from the geophysical results. Water samples from the new wells showed elevated concentrations of inorganic compounds responsible for the increased water electrical conductivity in the confined aquifer and high concentrations of xenobiotic organic contaminants such as chlorinated ethenes, sulfonamides and barbiturates.

The principle of equivalence is known to cause nonuniqueness in interpretations of direct current (DC) resistivity data. Low- or high-resistivity equivalences arise when a thin geologic layer with a low/high resistivity is embedded in a relative high-/low-resistivity background formation causing strong resistivity-thickness correlations. The equivalences often make it impossible to resolve embedded layers. We found that the equivalence problem could be significantly reduced by combining the DC data with full-decay time-domain induced polarization (IP) measurements. We applied a 1D Markov chain Monte Carlo algorithm to invert synthetic DC data of models with low- and high-resistivity equivalences. By applying this inversion method, it is possible to study the space of equivalent models that have an acceptable fit to the observed data, and to make a full sensitivity analysis of the model parameters. Then, we include a contrast in chargeability into the model, modeled in terms of spectral Cole-Cole IP parameters, and invert the DC and IP data in combination. The results show that the addition of IP data largely resolves the DC equivalences. Furthermore, we present a field example in which DC and IP data were measured on a sand formation with an embedded clay layer known from a borehole drilling. Inversion results show that the DC data alone do not resolve the clay layer due to equivalence problems, but by adding the IP data to the inversion, the layer is resolved.

We implemented an edge-based finite element time domain (FETD) modeling algorithm for simulating controlled-source electromagnetic (CSEM) data. The modeling domain is discretized using unstructured tetrahedral mesh and we consider a finite difference discretization of time using the backward Euler method which is unconditionally stable. We solve the diffusion equation for the electric field with a total field formulation. The finite element system of equation is solved using the direct method. The solutions of electric field, at different time, can be obtained using the effective time stepping method with trivial computation cost once the matrix is factorized. We try to keep the same time step size for a fixed number of steps using an adaptive time step doubling (ATSD) method. The finite element modeling domain is also truncated using a semi-adaptive method. We proposed a new boundary condition based on approximating the total field on the modeling boundary using the primary field corresponding to a layered background model. We validate our algorithm using several synthetic model studies.

The application of time-domain induced polarization (TDIP) is increasing with advances in acquisition techniques, data processing and spectral inversion schemes. An inversion of TDIP data for the spectral Cole-Cole parameters is a non-linear problem, but by applying a 1-D Markov Chain Monte Carlo (MCMC) inversion algorithm, a full non-linear uncertainty analysis of the parameters and the parameter correlations can be accessed. This is essential to understand to what degree the spectral Cole-Cole parameters can be resolved from TDIP data. MCMC inversions of synthetic TDIP data, which show bell-shaped probability distributions with a single maximum, show that the Cole-Cole parameters can be resolved from TDIP data if an acquisition range above two decades in time is applied. Linear correlations between the Cole-Cole parameters are observed and by decreasing the acquisitions ranges, the correlations increase and become non-linear. It is further investigated how waveform and parameter values influence the resolution of the Cole-Cole parameters. A limiting factor is the value of the frequency exponent, C. As C decreases, the resolution of all the Cole-Cole parameters decreases and the results become increasingly non-linear. While the values of the time constant, tau, must be in the acquisition range to resolve the parameters well, the choice between a 50 per cent and a 100 per cent duty cycle for the current injection does not have an influence on the parameter resolution. The limits of resolution and linearity are also studied in a comparison between the MCMC and a linearized gradient-based inversion approach. The two methods are consistent for resolved models, but the linearized approach tends to underestimate the uncertainties for poorly resolved parameters due to the corresponding non-linear features. Finally, an MCMC inversion of 1-D field data verifies that spectral Cole-Cole parameters can also be resolved from TD field measurements.

Surface nuclear magnetic resonance is a geophysical technique providing non-invasive aquifer characterization. Two approaches are commonly used to invert surface nuclear magnetic resonance data: (1) inversions involving many depth layers of fixed thickness and (2) few-layer inversions without predetermined layer thicknesses. The advantage of the many-layer approach is that it requires little a priori knowledge. However, the many-layer inversion is extremely ill-posed and regularisation must be used to produce a reliable result. For optimal performance, the selected regularisation scheme must reflect all available a priori information. The standard regularisation scheme for many-layer surface nuclear magnetic resonance inversions employs an L2 smoothness stabiliser, which results in subsurface models with smoothly varying parameters. Such a stabiliser struggles to reproduce sharp contrasts in subsurface properties, like those present in a layered subsurface (a common near-surface hydrogeological environment). To investigate if alternative stabilisers can be used to improve the performance of the many-layer inversion in layered environments, the performance of the standard smoothness stabiliser is compared against two alternative stabilisers: (1) a stabiliser employing the L1-norm and (2) a minimum gradient support stabiliser. Synthetic results are presented to compare the performance of the many-layer inversion for different stabiliser functions. The minimum gradient support stabiliser is observed to improve the performance of the many-layer inversion for a layered subsurface, being able to reproduce both smooth and sharp vertical variations of the model parameters. Implementation of the alternative stabilisers into existing surface nuclear magnetic resonance inversion software is straightforward and requires little modification to existing codes.