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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).

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.

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.

Modern airborne transient electromagnetic surveys typically produce datasets of thousands of line kilometres, requiring careful data processing in order to extract as much and as reliable information as possible. When surveys are flown in populated areas, data processing becomes particularly time consuming since the acquired data are contaminated by couplings to man-made conductors (power lines, fences, pipes, etc.). Coupled soundings must be removed from the dataset prior to inversion, and this is a process that is difficult to automate. The signature of couplings can be both subtle and difficult to describe in mathematical terms, rendering removal of couplings mostly an expensive manual task for an experienced geophysicist. Here, we try to automate the process of removing couplings by means of an artificial neural network. We train an artificial neural network to recognize coupled soundings in manually processed reference data, and we use this network to identify couplings in other data. The approach provides a significant reduction in the time required for data processing since one can directly apply the network to the raw data. We describe the neural network put to use and present the inputs and normalizations required for maximizing its effectiveness. We further demonstrate and assess the training state and performance of the network before finally comparing inversions based on unprocessed data, manually processed data, and artificial neural network automatically processed data. The results show that a well-trained network can produce high-quality processing of airborne transient electromagnetic data, which is either ready for inversion or in need of minimal manual processing. We conclude that the use of artificial neural network scan significantly reduce the processing time and its costs by as much as 50%.

The increased application of airborne electromagnetic surveys to hydrogeological studies is driving a demand for data that can consistently be inverted for accurate subsurface resistivity structure from the near surface to depths of several hundred metres. We present an evaluation of three commercial airborne electromagnetic systems over two test blocks in western Nebraska, USA. The selected test blocks are representative of shallow and deep alluvial aquifer systems with low groundwater salinity and an electrically conductive base of aquifer. The aquifer units show significant lithologic heterogeneity and include both modern and ancient river systems. We compared the various data sets to one another and inverted resistivity models to borehole lithology and to ground geophysical models. We find distinct differences among the airborne electromagnetic systems as regards the spatial resolution of models, the depth of investigation, and the ability to recover near-surface resistivity variations. We further identify systematic biases in some data sets, which we attribute to incomplete or inexact calibration or compensation procedures.

Time-domain electromagnetic data are conveniently inverted by using smoothly varying 1D models with fixed vertical discretization. The vertical smoothness of the obtained models stems from the application of Occam-type regularization constraints, which are meant to address the ill-posedness of the problem. An important side effect of such regularization, however, is that horizontal layer boundaries can no longer be accurately reproduced as the model is required to be smooth. This issue can be overcome by inverting for fewer layers with variable thicknesses; nevertheless, to decide on a particular and constant number of layers for the parameterization of a large survey inversion can be equally problematic. Here, we present a focusing regularization technique to obtain the best of both methodologies. The new focusing approach allows for accurate reconstruction of resistivity distributions using a fixed vertical discretization while preserving the capability to reproduce horizontal boundaries. The formulation is flexible and can be coupled with traditional lateral/spatial smoothness constraints in order to resolve interfaces in stratified soils with no additional hypothesis about the number of layers. The method relies on minimizing the number of layers of non-vanishing resistivity gradient, instead of minimizing the norm of the model variation itself. This approach ensures that the results are consistent with the measured data while favouring, at the same time, the retrieval of horizontal abrupt changes. In addition, the focusing regularization can also be applied in the horizontal direction in order to promote the reconstruction of lateral boundaries such as faults. We present the theoretical framework of our regularization methodology and illustrate its capabilities by means of both synthetic and field data sets. We further demonstrate how the concept has been integrated in our existing spatially constrained inversion formalism and show its application to large-scale time-domain electromagnetic data inversions.

Over the past decade the typical size of airborne electromagnetic data sets has been growing rapidly, along with an emerging need for highly accurate modelling. Onedimensional approximate inversions or data transform techniques have previously been employed for very large-scale studies of quasi-layered settings but these techniques fail to provide the consistent accuracy needed by many modern applications such as aquifer and geological mapping, uranium exploration, oil sands and integrated modelling. In these cases the use of more time-consuming 1D forward and inverse modelling provide the only acceptable solution that is also computationally feasible. When target structures are known to be quasi layered and spatially coherent it is beneficial to incorporate this assumption directly into the inversion. This implies inverting multiple soundings at a time in larger constrained problems, which allows for resolving geological layers that are undetectable using simple independent inversions. Ideally, entire surveys should be inverted at a time in huge constrained problems but poor scaling properties of the underlying algorithms typically make this challenging. Here, we document how we optimized an inversion code for very large-scale constrained airborne electromagnetic problems. Most importantly, we describe how we solve linear systems using an iterative method that scales linearly with the size of the data set in terms of both solution time and memory consumption. We also describe how we parallelized the core region of the code, in order to obtain almost ideal strong parallel scaling on current 4-socket shared memory computers. We further show how model parameter uncertainty estimates can be efficiently obtained in linear time and we demonstrate the capabilities of the full implementation by inverting a 3327 line km SkyTEM survey overnight. Performance and scaling properties are discussed based on the timings of the field example and we describe the criteria that must be fulfilled in order to adapt our methodology for similar type problems.

Very early times in the order of 2–3 μs from the end of the turn-off ramp for time-domain electromagnetic systems are crucial for obtaining a detailed resolution of the near-surface geology in the depth interval 0–20 m. For transient electromagnetic systems working in the off time, an electric current is abruptly turned off in a large transmitter loop causing a secondary electromagnetic field to be generated by the eddy currents induced in the ground. Often, however, there is still a residual primary field generated by remaining slowly decaying currents in the transmitter loop. The decay disturbs or biases the earth response data at the very early times. These biased data must be culled, or some specific processing must be applied in order to compensate or remove the residual primary field. As the bias response can be attributed to decaying currents with its time constantly controlled by the geometry of the transmitter loop, we denote it the ‘Coil Response’. The modelling of a helicopter-borne time-domain system by an equivalent electronic circuit shows that the time decay of the coil response remains identical whatever the position of the receiver loop, which is confirmed by field measurements. The modelling also shows that the coil response has a theoretical zero location and positioning the receiver coil at the zero location eliminates the coil response completely. However, spatial variations of the coil response around the zero location are not insignificant and even a few cm deformation of the carrier frame will introduce a small coil response. Here we present an approach for subtracting the coil response from the data by measuring it at high altitudes and then including an extra shift factor into the inversion scheme. The scheme is successfully applied to data from the SkyTEM system and enables the use of very early time gates, as early as 2–3 μs from the end of the ramp, or 5–6 μs from the beginning of the ramp. Applied to a large-scale airborne electromagnetic survey, the coil response compensation provides airborne electromagnetic methods with a hitherto unseen good resolution of shallow geological layers in the depth interval 0–20 m. This is proved by comparing results from the airborne electromagnetic survey to more than 100 km of Electrical Resistivity Tomography measured with 5 m electrode spacing.

This study uses time-domain induced polarization data for the delineation and characterization of the former landfill site at Eskelund, Denmark. With optimized acquisition parameters combined with a new inversion algorithm, we use the full content of the decay curve and retrieve spectral information from time-domain IP data. Thirteen IP/DC profiles were collected in the area, supplemented by el-log drilling for accurate correlation between the geophysics and the lithology. The data were inverted using a laterally constrained 1D inversion considering the full decay curves to retrieve the four Cole-Cole parameters. For all profiles, the results reveal a highly chargeable unit that shows a very good agreement to the findings from 15 boreholes covering the area, where the extent of the waste deposits was measured. The thickness and depth of surface measurements were furthermore validated by el-log measurements giving in situ values, for which the Cole-Cole parameters were computed. The 3D shape of the waste body was pinpointed and well-defined. The inversion of the IP data also shows a strong correlation with the initial stage of the waste dump and its composition combining an aerial map with acquired results.

Understanding the hydrologic seƫ ng of any given area is a challenging task, especially considering that the amount of available informaƟ on is oŌ en very sparse relaƟ ve to the size of the area and the complexity of the problem. We used geophysical transient electromagneƟ c (TEM) data from an airborne SkyTEM instrument to invesƟ gate discharge of freshwater from a river catchment into a coastal lagoon area, in support of large-scale hydrologic mapping of the HOBE hydrology research center. ExisƟ ng hydrologic data indicate possible ouƞ low from the catchment underneath the survey area, a hypothesis that was indeed backed up by our geophysical results. The results revealed a straƟ fi ed geologic seƫ ng frequently incised by buried valleys beneath the lagoon. They also showed that the valleys are saturated with sea water, unlike the layers at the same depth that are probably saturated with brackish water. The salinity decreases with depth in large parts of the lagoon. The salinity distribuƟ on in the seƫ ng indicates the presence of intricate fl ow systems beneath the coastal area and the lagoon, and we propose that it is governed by the heterogeneity in the geologic seƫ ng. We also demonstrated how water depth as well as salinity can be accurately mapped using SkyTEM in combinaƟ on with a robust and fl exible inversion scheme.

For about three decades, airborne electromagnetic (AEM) systems have been used for groundwater exploration purposes. Airborne systems are appropriate for large-scale and efficient groundwater surveying. Due to the dependency of the electrical conductivity on both the clay content of the host material and the mineralization of the water, electromagnetic systems are suitable for providing information about the aquifer structures and water quality, respectively. More helicopter than fixed-wing systems are used in airborne groundwater surveys. Helicopter-borne frequency-domain electromagnetic (HEM) systems use a towed rigid-boom. Helicopter-borne time-domain (HTEM) systems, which use a large transmitter loop and a small receiver within or above the transmitter, are generally designed for mineral exploration purposes but recent developments have made some of these systems usable for groundwater purposes as well. The quantity measured, the secondary magnetic field, depends on the subsurface conductivity distribution. Due to the skin-effect, the penetration depths of the AEM fields depend on the system characteristics used: high-frequency data/early-time channels describe the shallower parts of the conducting subsurface and the low-frequency data/late-time channels the deeper parts. Typical investigation depths range from some ten metres (conductive grounds) to several hundred metres (resistive grounds), where the HEM systems are appropriate for shallow to medium deep (about 1–100 m) and the HTEM systems for medium deep to deep (about 10–400 m) investigations. Generally, the secondary field values are inverted into resistivities and depths using homogeneous or layered half-space models. As the footprint of AEM systems is rather small, one-dimensional interpretation of AEM data is sufficient in most cases and single-site inversion procedures are widely used. Laterally constrained inversion of AEM data often improves the stability of the inversion models, particularly for noisy data. Higher dimensional inversion is still not possible for standard-size surveys. Based on typical field examples the advantages as well as the limitations of AEM surveys compared to long-established ground-based geophysical methods used in groundwater surveys are discussed. In a case history from a German island an airborne frequency-domain system is used to successfully locate freshwater lenses on top of saltwater. An example from Denmark shows how a time-domain system is used to locate large-scale buried structures forming ideal groundwater aquifers.

Traditional approaches to surveying well catchments usually involve investigations at two quite different spatial scales: very high resolution borehole-based studies and low resolution tracer and pump tests. In recent years, various researchers have attempted to fill the wide gap between the two scales of acquired data by using a variety of geophysical tools that have high-to-medium resolution capabilities. Although geophysical surveying may be relatively straightforward at many locations, there are numerous regions where topography, the presence of ubiquitous metal objects and/or a lack of suitably placed boreholes cause the acquisition, processing, inversion and interpretation of certain types of geophysical data to be extremely challenging. It was neces- sary for us to address such problems in an investigation of an active well catchment near Zurich, Switzerland. The principal goals of our project were to determine the geometries and physical properties of the shallow sedimentary layers, with emphasis on a key water-bearing gravel unit. To achieve these goals, four different geophysical methods were employed. In a first step, frequency-domain electromagnetic measurements allowed the locations of buried metal pipes to be established. A 2D tomographic seismic refraction survey then provided information on the interface between the low-velocity surface loamy topsoil and underlying high-velocity morainal material. The high electrical resistivity of the important gravel unit allowed its upper boundary to be outlined in 2D models derived from geoelectric data and its lower boundary to be deline- ated in models based on 1D linked inversions of geoelectric and transient electromagnetic data.

It is shown that the electromagnetic (EM) spectrum is characterized by strong amplitude-modulated transmitters operating in the target bandwidth of transient electromagnetic (TEM) measurements. As these transmitters cause significant noise in TEM soundings, it is mandatory to band-limit the input signals to improve the signal-to-noise ratio and thereby the depth of exploration. Band-limitation will distort the TEM responses, which leads to erroneous inversion results if the applied low-pass filters are not accounted for in the inversion scheme. We incorporate the low-pass filters in the inversion scheme and test the inversion approach on theoretical and field data. Inversion of band-limited theoretical responses results in recovery of erroneous resistivity models if the filters are not included in the inversion scheme. By contrast, inversion of band-limited theoretical and field data, for which the applied low-pass filters are included in the inversion scheme, leads to recovery of similar resistivity models, independent of the applied cut-off frequencies.