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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.

Summary The top 0–50 m of the subsurface are critical for infrastructure, water supply, artificial infiltration, farming, waste deposits, construction, etc. Yet, the tools for imaging this zone are limited to boreholes or geophysical methods such as electrical resistivity imagining (ERT) with a limited applicability for area-covering surveys larger than a few hectares. We present a new highly efficient towed transient electromagnetic system, tTEM, which bridges the gap in coverage and resolution between point or line measurements and airborne electromagnetics. The system yields images in full 3D with a lateral resolution down to 10 × 10 m. The system is towed by and All-Terrain Vehicle, uses a 2 × 4 m2 transmitter coil and has a z-component receiver 9 m offset from the transmitter. The first bias-free gate is as early as 4 µs from ramp beginning (1.4 µs after ramp-end). The turn-off time is 2.6 µs. Data are processed and inverted using methods directly adopted from airborne electromagnetics. We discuss the system design and present a case study where the system has been used to map complex subsurface geology in large detail to build 3D geological/hydrogeological models.

Surface nuclear magnetic resonance is a technique capable of providing insight into subsurface aquifer properties. To produce estimates of aquifer properties (such as the spatial distribution of water content and parameters controlling the duration of the nuclear magnetic resonance signal), an inversion is required. Essential to the reliable interpretation of the estimated subsurface models is an understanding of the uncertainty and correlation between the parameters in the estimated models. To quantify parameter uncertainty and correlation in the surface nuclear magnetic resonance inversion, a Markov chain Monte Carlo approach is demonstrated. Markov chain Monte Carlo approaches have been previously employed to invert surface nuclear magnetic resonance data, but the primary focus has been on quantifying parameter uncertainty. The focus of this paper is to further investigate whether the parameters in the estimated models exhibit correlation with one another; equally important to building a reliable interpretation of the subsurface is an understanding of the parameter uncertainty. The utility of the Markov chain Monte Carlo approach is demonstrated through the investigation of three questions. The first question investigates whether the parameters describing the water content and thickness of a layer exhibit a strong correlation. This question stems from applying concepts known to electromagnetic surveys (that the layer thickness and layer resistivity parameters are strongly correlated) to the surface nuclear magnetic resonance inversion. A water content–layer thickness correlation in surface nuclear magnetic resonance would not have large effects for quantifying total water content but would affect the ability to identify layer boundaries. The second question examines whether the parameter controlling the duration of the nuclear magnetic resonance signal exhibits a correlation with the water content and layer thickness parameters. The resolution of surface nuclear magnetic resonance typically does not consider the duration of the signal and focuses primarily on the distribution of current amplitudes that form the suite of transmit pulses. It is common to treat regions with short-duration signal with greater uncertainty, but it is important to understand whether the signal duration controls resolution for medium to long duration signals as well. The third question explores if the parameter uncertainty produced by the Markov chain Monte Carlo approach is consistent with that produced by an alternative approach based upon the posterior covariance matrix (for the linearised inversion). The ability of the Markov chain Monte Carlo approach to more thoroughly explore the model space provides a means to improve the reliability of surface nuclear magnetic resonance aquifer characterisations by quantifying parameter uncertainty and correlation.

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.

We present a 2D inversion code for frequency-domain HEM data designed for inverting field scale surveys on normal desktop computers. The fundamental algorithm is a 2.5D algorithm with field separation into primary and secondary fields. Due to limited memory, as well as performance concerns, sectioning is introduced for splitting large surveys into smaller sections. Sectioning is only done when calculating the 2D forward and derivatives, and it is done with a sufficient overlap, such that vital 2D information is preserved. The algorithm uses a hybrid scheme which i) starts with 1D forward and inverse calculations, ii) then switches to 2D forward calculations and 1D derivatives, and iii) finally ends with full 2D calculations. The result of this is a code which produces results like a 2D code, but with a substantially shorter computational time.

Summary Knowledge of the sensitivity function of an electromagnetic (EM) system helps to assess the advantages and shortcomings of the system set-up. We have computed 3D sensitivity functions of three different EM systems – one airborne (SkyTEM) and two ground-based systems (tTEM and GCM) – in order to compare the sensitivity distribution of the different transmitter-receiver set-ups. The results show that the GCM has the highest sensitivity to near-surface structures, but also has a very limited footprint depth. The SkyTEM and tTEM systems have comparable sensitivities vertically in the ground with a 90% footprint depth around 5 m for early time measurements. However, the sensitivity of the SkyTEM system is distributed must wider horizontally than the tTEM.

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.

Summary The SkyTEM data provides a comprehensive three-dimensional picture of the subsurface. The low moment data ensured the high resolution mapping of the near surface and the high moment data to the deeper level. The dual moment AEM data provided high resolution mapping of subsurface from top to ∼ 250 m depths. The results revealed significant contrast between the B-G layers that has a resistivity range of 10–15 Ωm and generally has groundwater yields of 6–8 lps. It is also noted that the groundwater yield (> 6 lps) increases for deeper (

In the present study, we have used 3D ERT for detailed mapping of a polluted site at a challenging river site in the southern part of the Denmark. The survey layout involves several crossings of the meander of a river where a leachate plume from an old chemical factory site is expected to reach the river. Both resistivity and time domain induced polarization data were acquired, and full 3D inversion was performed for the resistivity data and 2D inversion of the IP data. Two sets of 3D data were acquired; one at a larger scale covering total area 410x90m2 and one at small scale covering 126x42m2, which enabled both details in the shallow part while covering a large area. 3D DC data were inverted using the inversion package BERT and 2D DC-IP data were inverted using AarhusInv. 3D DC inversion models show the presence of low resistivity anomaly at the northern bank of the stream interpreted as a contaminant plume. The contaminant plume is also seen in a deeper aquifer, which is separated by a low permeable clay layer to the upper aquifer. We could not discriminate the clay-lithology from the contamination using only resistivity model however, including the 2D inversions of the IP data we clearly separate the clay layer from the contaminated aquifer.

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.

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.

Modern airborne transient electromagnetic surveys typically span thousands of line kilometres requiring careful data processing. When surveys are flown in populated areas, data processing becomes particularly time consuming, since the acquired data is contaminated by couplings to man made conductors (power lines, fences, pipes, etc.). Coupled soundings must be removed from the dataset prior to inversion, but since the signature of couplings can be subtle and difficult to describe in general terms it has so far remained mostly a manual task. We train an artificial neural network to recognize coupled soundings in previously processed data and use this network to identify couplings in other data. The approach provides a dramatic reduction in the time required for data processing, since one can directly apply the network to the raw data. We present the training state and performance of the network and compare inversions based on manually processed data and ANN processed data. The results show that a well trained network can produce a high quality processing of ATEM data, which are either ready for inversion or in need of minimal manual processing. The results are very promising and can significantly reduce the processing time and cost of large ATEM surveys.

While full 2D and 3D inversion schemes are emerging for airborne TEM datasets, the workhorse of large scale surveying still remains the well established 1D forward formulation. Modern airborne TEM surveys typically span several thousand line kilometers of data, which can be very time consuming to invert even within the framework of 1D forward modeling. Here, we present how we have modified our existing inversion code to offload its 1D forward computations to massively parallel Intel Xeon Phi co-processors. A prerequisite for good performance on this type of next generation technology is for a code to provide not only good parallel scaling, but also make efficient use of vector instructions. The latter is not possible without modification to the established framework of 1D forward modeling and we demonstrate how this problem can be overcome in a straight forward manner. We show how the modified algorithm provides virtually ideal parallel scaling and almost ideal use of vector instructions on both multi-core processors and massively parallel Intel Xeon Phi co-processors. The use of vector instructions alone provide a speed-up of almost 8x on the co-processor, allowing for full inversion of several thousand line kilometers of data per hour.

Airborne electromagnetic methods (AEM) have in the last decade undergone immense hardware and software developments. 10 years ago high resolution shallow surveys for geotechnical engineering, aquifer mapping, landslides etc, could only be done by frequency domain methods whereas time domain methods were more suited for deep measurements. Today, the development of the time domain methods has reached a level where the same or even better data from an airborne platform is obtained compared to the best groundbased system. Also, data inversion has changed from being dominated by approximate algorithms to full solutions modelling the complete system characteristics with inversion of thousands of line kilometers of data in one run. These inversions are possible because the algorithms use multithreaded architecture, which efficiently runs on small workstations or severs. In this paper we discuss the newest hardware developments of the SkyTEM system and also how these developments are accompanied by inversion algorithms closely adapted to the hardware. The SkyTEM system, as shown in Figure 1, originally developed at Aarhus University, is now operated and developed by an independent spin-off company, SkyTEM Surveys, while inversion and processing algorithms are developed at Aarhus University. However, there are fruitful collaborations and SkyTEM Surveys identify themselves as a high-tech company with an ambitious research and development (R/D) program.

Precision agriculture applications rely on highly detailed information on variations in soil properties. This demand has led to recent developments in EMI instrumentation, resulting in stable and high data quality. The reliability of the data enables real non-linear inversion providing true formation resistivity with depth. With the aim of mapping soil heterogeneity, an EMI survey has been carried out in the central part of Jutland, Denmark. The collected data were carefully processed prior to inversion in order to remove any couplings from man-made conductors such as buried electrical cables, which can cause errors in the lithological interpretation. The data were subsequently modelled with a 1D layered spatially constrained inversion which takes the entire EMI data geometry into account. The inversion results gives a detailed quasi tree-dimensional image of the survey area, revealing several small scale resistivity variations which corresponds well with existing geological knowledge.

One of the main limiting factors to the accuracy of large scale groundwater models is the scarcity of hydraulic data. High-resolution Airborne Electromagnetic Methods (AEM) are capable of mapping the electrical resistivity structure of the subsurface in great detail and covering large areas in short time and on a limited budget. As such, there is great potential in integrating AEM data in groundwater modeling as a supplementing source of an extensive amount of information. We have developed several novel techniques that in combination allows for bringing groundwater and AEM models much closer together, i.e.: (1) a novel, scalable inversion engine that allows the AEM inversion to handle arbitrarily large areas at a time; (2) the spatially-decoupled inversion approach, which decouples the inversion model from the acquisition points and can operate on the same grid/voxel cells as the groundwater model; (3) a custom regularization scheme that allows for producing geophysical models with sharp vertical/horizontal resistivity transitions. In this study we present the very first application of the sharp spatially-decoupled inversion on an AEM survey flown for improving the groundwater model in the Kasted area, in the north of Aarhus (Denmark).

Regional hydrological models are important tools in water resources management. Model prediction uncertainty is primarily due to structural (geological) non-uniqueness which makes sampling of the structural model space necessary to estimate prediction uncertainties. Geological structures and heterogeneity, which spatially scarce borehole lithology data may overlook, are well resolved in AEM surveys. This study presents a semi-automatic sequential hydrogeophysical inversion method for the integration of AEM and borehole data into regional groundwater models in sedimentary areas, where sand/clay distribution govern groundwater flow. The coupling between hydrological and geophysical parameters is managed using a translator function with spatially variable parameters followed by a 3D zonation. The translator function translates geophysical resistivities into clay fractions and is calibrated with observed lithological data. Principal components are computed for the translated clay fractions and geophysical resistivities. Zonation is carried out by k-means clustering on the principal components. The hydraulic parameters of the zones are determined in a hydrological model calibration using head and discharge observations. The method was applied to field data collected at a Danish field site. Our results show that a competitive hydrological model can be constructed from the AEM dataset using the automatic procedure outlined above.

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.

We present a comparison between two different regularisation schemes for multi-layer inversion of the MRS data. The two regularizations consist of the norm (Occam’s inversion) and the support (focused inversion) of the variation of the water content and relaxation time. The focused regularization provides a sharp inversion as it minimizes the area (the support) where the variations of the model parameters occur, and not the (L2) norm of the variations. Clearly, when sharp vertical transitions of the inversion parameters are present, the focused inversion retrieves the interfaces with higher precision and reconstructs more effectively the physical property values as well. This is a quite common situation in hydrogeophysics, e.g. in correspondence with the water table and/or at the boundary between aquifers and aquitards.

We present a geophysical inversion algorithm working directly in a voxel grid disconnected from the actual measuring points, which allows for straightforward integration of different data types in joint inversion, for informing geological/hydrogeological models directly and for easier incorporation of prior information. Inversion of geophysical data usually refers to a model space being linked to the actual observation points. For airborne surveys the spatial discretization of the model space reflects the flight lines. Often airborne surveys are carried out in areas where other ground-based geophysical data are available. The model space of geophysical inversions is usually referred to the positions of the measurements, and ground-based model positions do not generally coincide with the airborne model positions. Consequently, a model space based on the measuring points is not well suited for jointly inverting airborne and ground-based geophysical data. Furthermore, geological and groundwater models most often refer to a regular voxel grid not correlated to the geophysical model space, and incorporating the geophysical data into the geological/hydrological modelling grids is problematic. We present a voxel grid inversion routine that overcomes these problems and we discuss in detail the algorithm implementation.

The SkyTEM system is being developed for almost ten years in Denmark and has been specially designed for the groundwater mapping. Through the years more and more early gates are becoming interpretable, and for almost two years gates below 10 µs have been used generically. The electronics and processing developments end recently with the new Mini-SkyTEM system which provides a first gate at 5-6 µs. This new system can also be flown up to a speed of 140 km/h, allowing a same coverage at a lower cost compared to the larger systems. The first pilot survey of the new Mini-SkyTEM was flown in June 2011 inside the NiCA project where the purpose is to model the oxydo-reduction of the nitrates in the near-surface aquifers for pollution management. Despite its very low transmitter moment, the Mini-SkyTEM system provides a depth of investigation of 100 m considering a mean resistivity of 50 Ωm. But more importantly, a good correlation between the resistivity boundaries and the geological interfaces defined in the borehole logs is observed in the upper 20 m. This gives us confidence in the future use of this transient airborne EM system for the mapping of the very near-surface aquifers.

In the computation of the forward response for Time Domain Induced Polarization the incomplete description of the transmitter waveform causes dramatic errors in the estimation of the magnitude and time characteristic of the IP phenomenon. In fact both the duration of the current pulse and the sequence of pulses used for the stacking procedure have a strong effect in the magnitude and shape of the IP decays. Furthermore, it is important to model, if present, the low-pass filters of the receivers, in order to use all the information contained in the acquired data. For these reasons, a new 1D forward and inversion algorithms have been developed using the full time decay of the IP response and the receiver transfer function to reconstruct the distribution of the four Cole-Cole parameters of the earth. The waveform implementation in the forward response for TDIP is a significant improvement that allows moving from a qualitative interpretation of TDIP data for recognition of anomaly patterns towards a quantitative analysis, able to discriminate soil lithotypes and, if present, some contamination patterns.

Airborne electromagnetics (AEM) is an efficient tool for mapping the subsurface. AEM delivers a very high data coverage compared to the costs, and the direct outputs are high-resolution resistivity images of the subsurface. In particular the time domain methods (TEM) are well suited for mapping of the salt-fresh water boundary in coastal zones, aquifers, paleo-channels, mineralisations and general structural geological mapping. The development of AEM systems and data processing systems has been intensive during the past 10– 15 years because of better electronics and faster and more flexible computers. While most AEM systems in the 1980s were limited to detection of mineralisations, modern system generations measures full spectra, yields absolutely calibrated data and accurate descriptions of the system transfer function. This, in combination with much enhanced inversion and forward algorithms, makes AEM a suitable candidate for mapping targets which so far have not be possible.

Accuracy and stability of data from airborne electromagnetic systems is an issue addressed in numerous publications and conference presentations. We have recently done a comprehensive and well documented comparison of data from ground based measurements and repeated SkyTEM lines from different altitudes. the ground based test line was made on the National Danish Test Site and consists in two perpendicular lines each of a length of 1.0 km. On each of these lines 25 soundings with a 40x40 m2 TEM system was made. the TEM system measures the first time gate in 8 micro sec from begin of ramp and was prior to the measurements calibrated at the test site. Comparing Inversion results form the SkyTEM and the groundbased data shows that the model repeatability of the SkyTEM system is excellent in both the same altitude and in different altitudes. Also, there are no directional problems, i.e. it does not matter in which direction the lines are flown. the agreement to the groundbased reference sections is also very good, showing that the SkyTEM-system yields data of same high quality as the groundbased system. A validation of the SkyTEM system at the data level was set up to examine the responses gate by gate, which, among other things, rules out the equivalent model issue. the different comparisons in the data space show that the SkyTEM system repeats the test lines equally good in different altitudes, and the agreement to the ground based responses is very good and in general within the data standard deviation of 5%. the validation serves as a quality assurance of the high-precision modeling of the SkyTEM system, together with the robust processing and Inversion scheme developed for the data. the validation of the SkyTEM system now set the standard for the data quality expected for any airborne system to qualify for the Danish national groundwater mapping effort.

During the last decades the scope of Time Domain Induced Polarization (TDIP) has considerably broadened from mineral exploration to environmental geophysics, mainly to clay identification and landfill characterization. Furthermore modern instruments allow multi-channel acquisition of IP data with multi-core cables and steel electrodes. for TDIP surveys the acquisition time is shorter and the logistic simpler in comparison with Spectral Induced polarization (SIP) surveys. Despite this the Inversion techniques have not undertaken consequential enhancements: TDIP data are usually inverted using only integral chargeability, without considering the effective shape of the transmitter pulse or the system transfer function of the receiver. for these reasons a new Inversion algorithm has been developed using the full time decay of the IP response to reconstruct the distribution of the Cole-Cole parameters of the Earth. the forward response is computed modeling the full current waveform (in terms of sequence of positive and negative pulses) and instrumental low-pass filters. Even when stacking, needed for noise reduction and self potential removal, the signal changes significantly during the process and the finite numbers of pulses have to be modeled to obtain accurate time decays. the new approach allows moving from a qualitative Interpretation of TDIP data for recognition of anomaly patterns to a quantitative analysis, able to discriminate soil lithotypes and, if present, the type/grade of contamination: a case history from a landfill-stream interaction supports this conclusion, correlating pollution and Inversion parameters. the forward response has been implemented in the 1D Laterally Constrained Inversion scheme (1D-LCI), producing layered sections of the subsurface with lateral smooth variations. Currently a 2D and 3D implementation are being developed.

In this abstract we show the results from a comparison of models from the SkyTEM-system with the ground based models at the extended test site. The comparison will also be carried out in data space by an upward continuation of the reference models to a SkyTEM-system response at nominal height. Furthermore, the repeatability of the SkyTEM-system at different heights is demonstrated. The national TEM test site was established to ensure that any TEM system used in the ongoing Danish groundwater mapping campaign can reproduce the reference models and match the upward continued responses of the reference model. The site was established in 2001. In 2009 the test site was extended from a point location with a known reference response and resistivity model to two crossing lines. This makes calibration and validation possible for airborne TEM-systems that cannot make hovering spot measurements. SkyTEM and VTEM have been on the new test lines so far. For the SkyTEM system we can conclude that it reproduces the ground-based TEM data and models very good and that SkyTEM data shows consistent results for different altitudes. In the data space we calculate an upward-continued dataset to perform the comparisons.

Airborne ElectroMagnetic methods (AEM) have been used for geophysical surveys for several decades, in particular due to its ability to cover large areas on a limited budget and in relatively little time. Ever since the method was first deployed the tendency has been for the typical survey size to be growing at a very rapid rate, in particular during the last decade. AEM surveys of today are often in the order of tens of thousands of flight line kilometres, producing huge datasets that needs to be inverted. Performing a full non-linear inversion of such datasets is a tremendous computational burden and consequently, these datasets are very often inverted using approximate inversion schemes. Several full non-linear inversion codes for AEM data is reported in the literature, however, most of these codes operate on single soundings only and are not optimized for large datasets. We discuss how the existing constrained inversion code em1dinv has been optimized for modern parallel computing and show performance results. The parallel optimized code is capable of handling very large datasets and provides a significant reduction in the total inversion time. Furthermore, we show how the optimized code eliminates inversion artefacts inherent of the previous implementation.

A large amount of new geophysical and geological data has been collected in the central part of Vendsyssel, Denmark, as a part of a large groundwater investigation.

We describe the challenges for the realization of a transient EM (TEM) system capable of measuring both the z- and x-components. This involves significant changes to instrumentation as well as to the processing and inversion algorithms. Geophysical mapping of groundwater resources using TEM involves both delineation of the aquifer structure and the aquifer protection. The demands for the instrumentation and the processing algorithms are quite different for the two tasks. Structural mapping requires large depth penetration and thereby a large transmitter moment while aquifer protection mapping requires early time measurements and extremely accurate determination of the system transfer function. Furthermore, the inversion software must be capable of modelling this system transfer function. For an airborne TEM system systematic analysis of the resolution capabilities of relatively thin low resistive layers in the upper 30 - 50 m of the subsurface has shown that the resolution is enhanced if not only the transient z-component but also the transient x-component of the induced fields in the Earth is measured and included in the inversion. The abstract will describe and discuss three major challenges related to the inclusion of the x-component in an airborne TEM system.

A033 Geostatistical estimation of structural vulnerability Summary 1 In this abstract we present a newly developed concept using geostatistical estimation and nonlinear inversion to optimize a function translating geophysical resistivity models to geophysical clay thickness. The algorithm uses information on reported clay thicknesses in drill holes. We call it geoStatistical estimation of Structural Vulnerability (SSV). The clay thickness in the upper part of the subsurface is an important factor for the water infiltration speed and thereby the vulnerability of underlying aquifers to pesticides nitrate etc. Drill hole information contains the most detailed information on clay thicknesses but most often drill

A035 INTERPRETATION OF A HYDROGEOPHYSICAL SURVEY – DATA FROM THE HIGH- RESOLUTION SKYTEM SYSTEM Abstract 1 During the last decade approximately 50 000 ground-based TEM soundings have been carried out in Denmark for groundwater investigations. This number will increase in the future and therefore we have developed a new time-domain electromagnetic (TEM) helicopter system SkyTEM. In the development and design of the SkyTEM system it has been an unchangeable demand that the data quality of the SkyTEM system should be the same or better than the data quality of ground-based systems e.g. the Protem 47 system (40 x 40 m

A033 INTEGRATED INVERSION OF CVES AND TEM DATA USING LATERAL CONSTRAINTS Summary 1 We present a mutually and laterally constrained inversion between transient electromagnetic (TEM) and geoelectric (DC) data sets. Although both methods measure in some sense the electrical resistivity or conductivity of the subsurface they sample different volumes and have different sensitivities. The different sampling volumes and different sensitivities are exploited by the mutually and laterally constrained inversion algorithm combining the coinciding profile data sets. The output model incorporates the information from both profile data sets to obtain the optimum layered 1D models fitting both data types. All data

2D laterally constrained inversion (2D-LCI) is a new approach to interpretation of continuous resistivity data. The 2D-LCI enables a layered 2D inversion with sharp layer boundaries as compared to traditional smooth inversion types. However, the full 2D solution is quite time consuming when calculating the derivatives in the Jacobian matrix. To reduce the computation times we suggest using 1D derivatives, Broyden's update formula (Quasi- Newton) or combinations of Broyden's update formula and 1D derivatives together with the full 2D solution. The reduction in computation time is between 7 and 30 times dependent on the combination of approximations.

In this paper we present how a 2D least squares algorithm, Res2Dinv (Loke and Dahlin, 2002), and the 2D Lateral Constrained Inversion (2D-LCI) algorithm (Christiansen et al., 2003) can be applied in geotechnical site investigations. The 2D-LCI algorithm performs a parameterized 2D Laterally Constrained Inversion (Auken and Christiansen, 2003) on resistivity data.

2D laterally constrained inversion (2D LCI) is a new approach to interpretation of continuous resistivity data using an inversion scheme similar to that used for 1D LCI. The only difference is that the forward code in the inversion scheme is 2D. This enables a layered 2D inversion in sedimentary areas where the layering has been disturbed in a degree, that a 1D model is inadequate, but a layered model is still applicable. The layered 2D inversion provides a full analysis of the model, and can include a priori information just as in the 1D case. Preliminary results on synthetic data show that a layered 2D approach enables a more detailed description of 2D structures, which the 1D formulation can not resolve. The model complexity is controlled and balanced by the lateral constraints on depths and resistivities.

In time domain electromagnetic, TDEM, it is a wide spread practice to model the current waveform (e.g. Asten, 1987), where as the effect of low pass filters (LP) in the receiver system is neglected. In this paper we show that when the TDEM method is used in hydrogeological and environmental investigations it is mandatory to include the filters in the forward and inverse modeling scheme to obtain avalid geological model for the survey site. IDEM systems is normally band-limited as input signals from amplitude modulated radio transmitters operating in the target bandwidth of the system often dominate the noise characteristic of the system over several decades in time. Band-limiting the input signals significantly improves the signal-to-noise ratio and thereby the depth of exploration. However, the LP filters distort the early and medium part of the decay curve due to damping of the high frequency content. The level of distortion depends on several factors such as cut-off frequency and subsurface resistivities. Therefore, the LP filters must be incorporated in the inversion scheme such that the calculated forward response is subject to the same filtering as the measured response. In this paper we (1) quantify the distortion of responses due to band-limitation for a number of typical resistivity models. The band-limitations are based on cut-off frequencies typically used in commercial instruments. (2) We demonstrate that distortion due to band-limitation can be modeled in the inversion scheme by including the LP filters in the forward response. This approach is tested on theoretical data.

For continuous methods there is a trade-off between lateral resolution and the size of the data stack, or average width. A narrow average (small stack) results in a high lateral resolution, a wide average (large stack) results in a better signal-to-noise ratio but reduces the lateral resolution. We present inversion results of synthetic TEM-data with different averaging widths to explore the influence on the lateral resolution. The study shows that for the deeper parts of the model it is possible to use a very large average width without loosing lateral resolution. Averaging airborne data adds another issue, because the data entering the average interval originates from different flight altitudes (aircraft movement). The question is whether the error introduced by assigning the average flight altitude to the average dataset is acceptable? This is relevant because the altitude enters the inversion scheme as a fixed or strongly constrained parameter. We show that a linear correlation between altitude and data response for TEM-data exist. Due to the linearity the error introduced by using average data with the average altitude is very small. In the worst case, the error is 3% and negligible for the late time gates.

This study uses time domain IP for the delineation and the characterization of the former Eskelund landfill, Denmark. With optimized acquisition parameters combined with a new inversion algorithm it is now possible to use the full content of the decay curve and retrieve spectral information from the time domain IP data. Thirteen IP/DC profiles were collected, supplemented by en el-log drilling for an 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 with an impressive agreement to 15 boreholes. The thickness and the depths have been validated by el-log measurements giving in-situ values for the Cole-Cole parameters. The 3-D shape of the waste body has been delineated with a very high accuracy, and the south boundary of the landfill has been redefined based on these results. The inversion of the IP data also allows reconstruction of the waste history combining aerial maps with the results. Thus, this case study shows the relevance and the full benefits of using the TDIP data for the recognition and the characterization of landfill areas.

We have developed a new, robust 2D inversion approach for modelling time domain induced potential data. Instead of considering the integral chargeability, the full IP waveform is modelled allowing inversion for spectral content in terms of the Cole-Cole parameters. The method is based on a finite element complex resistivity forward response, which is transformed to the time domain using a Fast Hankel Transform. The forward response is implemented in a general inversion code where constraints can be applied on all model parameters to allow migration of information along the profile. A priori information from e.g. boreholes may also be included to constrain the inversion.

We present a new inversion methodology for large area-covering datasets. Many new data acquisition systems are capable of covering large areas with densely sampled data sets. However, it is not possible to apply 2D or 3D inversion algorithms on a routine basis because of computational problems. We propose a Spatially Constrained Inversion (SCI) inversion scheme using a local 1D model description ensuring fast computation times. Information on the geological variability is included as constraints between model parameters applied on an all-to-all basis. The 1D formulation means that the SCI works best on a sub-horizontal layered geology. To ensure flexibility even for very large surveys we sub-divide the area in hexagons, which are independently inverted and afterwards stitched together. Continuity over hexagon edges is ensured by applying an overlap between neighbouring hexagons. A field example demonstrates that the SCI enables better resolution of otherwise poorly resolved model parameters. Lineations observed in line-inversion are removed.

We present an automatic method for parameterization of a 3D model of the subsurface, integrating lithological information from boreholes with resistivity models through an inverse optimization, with the objective of further detailing for geological models or as direct input to groundwater models. The parameter of interest is the clay fraction, expressed as the relative length of clay-units in a depth interval. The clay fraction is obtained from lithological logs and the clay fraction from the resistivity is obtained by establishing a simple petrophysical relationship, a translator function, between resistivity and the clay fraction. Through inversion we use the lithological data and the resistivity data to determine the optimum spatially distributed translator function. Applying the translator function we get a 3D clay fraction model, which holds information from the resistivity dataset and the borehole dataset in one variable. We apply the concept to the Norsminde survey in Denmark integrating approximately 700 boreholes and more than 100,000 resistivity models from an airborne survey in the parameterization of the 3D model covering 156 km2. The final 3D model differentiates between clay materials and different high resistive materials from information held in resistivity model and borehole observations respectively

We present a new scheme for joint and laterally constrained inversion (LCI) of magnetic resonance sounding (MRS) data and transient electromagnetic (TEM) data, which greatly improves the estimation of the MRS model parameters. MRS is a non-invasive geophysical technique which directly quantifies the water content distribution from surface measurements. The resistivity information of the subsurface is obtained from a complementary geophysical method such as TEM or DC resistivity methods. The conventional inversion of MRS data assumes the resulting resistivity structure to be true and considers a constant MRS kernel through the inversion. We show that this assumption may introduce an error to the forward modeling and consequently result in erroneous parameter estimations. We discuss the advantage of TEM for the joint inversion compared to DC resistivity. A fast and numerically efficient MRS forward routine makes it possible to invert the MRS and TEM data sets simultaneously along profiles. As results, a more reliable and robust estimation of all parameters is achieved. We examine the approach through a field example in Denmark where good agreement with borehole data is demonstrated with clear correlation between the relaxation time T_2^* and the grain size distribution of a sandy aquifer.

The spatially constrained inversion (SCI) is a robust methodology for quasi-3D modeling of geoelectrical and EM data of varying spatial density, using a 1D forward solution. Information migrate horizontally through spatial constraints applied between nearest neighboring soundings, and allow resolution of layers that would be locally poorly resolved. The constraints are built using the Delaunay triangulation, which ensures automatic adaptation to data density variations. In this study the SCI was applied to airborne Time domain EM soundings, but it can be implemented also with other data types. The field case study proves that the SCI produces laterally smooth results that respect the 3D geological variations of sedimentary settings, while suppressing the elongated artifacts commonly seen in profile oriented data sets.

Key to the effective management of natural ecosystems that characterise the floodplains of the Murray Basin in south eastern Australia, and maintenance of river health (a critical water resource) in a setting where severe salinisation is an ever-present threat, requires a sound understanding of surface water-groundwater processes. This paper presents results from an examination of hydrogeophysics, specifically airborne electromagnetics (AEM) data acquired by the SkyTEM time domain helicopter EM system, as a means for improving our knowledge of spatial patterns associated with inter-aquifer mixing where groundwater flow is complex. In the south-eastern part of the Murray Basin, AEM data shows considerable promise as a means for understanding of groundwater quality and its lateral variability. In the Bookpurnong and Loxton irrigation areas the high moment capability of SkyTEM permits us to investigate variations in the quality of groundwater at depth (>100m), which in turn allows us to visualise how groundwater may be moving across aquitards and within particular aquifer systems.

We tested a new robust concept for the calculation of depth of investigation (DOI) that is valid for any 1D electromagnetic (EM) geophysical model. A good estimate of DOI is crucial when building geologic and hydrological models from EM data sets because the validity of the models varies strongly with data noise and the resistivity of the layers themselves. For diffusive methods, such as ground-based and airborne electromagnetic, it is not possible to define an unambiguous depth below which there is no information on the resistivity structure and a measure of DOI is therefore to what depth the model can be considered reliable. The method we presented is based on the actual model output from the inversion process and we used the actual system response, contrary to assuming, e.g., planar waves over a homogeneous half-space, the widely used skin depth calculation. Equally important, the data noise and the number of data points are integrated into the calculation. Our methodology is based on a recalculated sensitivity (Jacobian) matrix of the final model and thus it can be used on any model type for which a sensitivity matrix can be calculated. Unlike other sensitivity matrix methods, we defined a global and absolute threshold value contrary to defining a relative (such as 5%), sensitivity limit. The threshold value will apply to all 1D inverted data and will thus produce comparable numbers of DOI.

Geophysical dataset from areas with substantial topography cause problems to many inversion routines. Commonly, the cells or layers of the model follow the topography which then favors layers boundaries of the inverted model that are topography-parallel. In many cases the geological layering is not connected to the overall topography, e.g. an erosional environment over a horizontal sub-stratum. Inverting data from such areas are penalized if the topography is not taken into account when dealing with the constraints We present a simple way of correcting the constraints entering the roughness matrix of the inversion problem so that topography is neutralized and horizontal layering is favored. Synthetic modeling confirms the superiority of the topography neutralization over traditional depth referenced inversion. Field examples will be shown in the talk.

We present a comprehensive study of the parameter determination of magnetic resonance sounding (MRS) models in a joint MRS and transient electromagnetic (TEM) data analysis scheme. The parameter determination is assessed by calculating the model parameter uncertainties based on an a posteriori model covariance matrix. An entire MRS data set, dependent on pulse moment and time gate values, together with TEM data, is used for all analyses and realistic noise levels are assigned to the data. Sensitivity analyses are studied for the determination of water content as a key parameter estimated during inversion of MRS data. We show the results for different suites of (three-layer) models, in which we investigate the effect of resistivity, water content, relaxation time, loop side length, number of pulse moments and measurement dead time on the determination of water content in a water-bearing layer. For all suites of models the effect of a top conductive and a top resistive layer are compared. Moreover, we analyse all models for a long (40 ms) and short (10 ms) measurement dead time. The effect of noise level on the parameter determination is also analysed. We conclude that, in general, the resistivity of the water-bearing layer (layer of interest, LOI) does not affect the determination of water content in the LOI but the resistivity of the top layer increases depth resolution; the water content of the LOI does not influence its determination considerably in cases where the signal has a relatively long relaxation time in the LOI; determination of the water content in the LOI is improved by increasing the relaxation time of the signal in the LOI; short measurement dead time will improve the parameter determination for signals with a relatively short relaxation time; increasing loop side length and the number of pulse moments do not necessarily improve the parameter determination.

We present a new forward modelling routine, which can calculate the secondary magnetic field for all times – also during the transmitter turn-off. This is done by convolving the step response with the time derivative of the system response. The calculations can be compared to the SkyTEM primary field corrected data to obtain a better sensitivity to the near surface, which are probed by the earliest gates in the measured signal from 0 to 10 µs. We describe the implementation of the new routine and compare it to results with the previous routine and to data measured at the Danish test site. The agreement is very good even though the system is described in two completely different ways.