Esben Auken

Layered and laterally constrained 2D inversion of resistivity data

In a sedimentary environment, quasi-layered models often can represent the actual geology more accurately than smooth minimum-structure models. We present a 2D inversion scheme with lateral constraints and sharp boundaries (LCI) for continuous resistivity data. All data and models are inverted as one system, producing layered solutions with laterally smooth transitions. The models are regularized through lateral constraints that tie interface depths or thicknesses and resistivities of adjacent layers. A priori information, used to resolve ambiguities and to add, for example, geological information, can be added at any point of the profile and migrates through the lateral constraints to parameters at adjacent sites. Similarly, information from areas with well-resolved parameters migrates through the constraints to help resolve areas with poorly constrained parameters. The estimated model is complemented by a full sensitivity analysis of the model parameters supporting quantitative evaluation of the inversion result. A simple synthetic model proves the need for a quasilayered, 2D inversion when compared with a traditional 2D minimum-structure inversion. A 2D minimum-structure inversion produces models with spatially smooth resistivity transitions, making identification of layer boundaries difficult. A continuous vertical electrical sounding field example from Sweden with a depression in the depth to bedrock supports the conclusions drawn from the synthetic example. A till layer on top of the bedrock, hidden in the traditional inversion result, is identified using the 2D LCI scheme. Furthermore, the depth to the bedrock surface is easily identified for most of the profile with the 2D LCI model, which is not the case with the model from the traditional minimumstructure inversion.

Quasi-3D modeling of airborne TEM data by spatially constrained inversion

We present a new methodology, spatially constrained inversion (SCI), that produces quasi-3D conductivity modeling of electromagnetic (EM) data using a 1D forward solution. Spatial constraints are set between the model parameters of nearest neighboring soundings. Data sets, models, and spatial constraints are inverted as one system. The constraints are built using Delaunay triangulation, which ensures automatic adaptation to data density variations. Model parameter information migrates horizontally through spatial constraints, increasing the resolution of layers that would be poorly resolved locally. SCI produces laterally smooth results with sharp layer boundaries that respect the 3D geological variations of sedimentary settings. SCI also suppresses the elongated artifacts commonly seen in interpretation results of profile-oriented data sets. In this study, SCI is applied to airborne time-domain EM data, but it can also be implemented with other ground-based or airborne data types.

A review of helicopter-borne electromagnetic methods for groundwater exploration

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.

An integrated processing scheme for high-resolution airborne electromagnetic surveys, the SkyTEM system

The SkyTEM helicopter-borne transient electromagnetic system was developed in 2004. The system yields unbiased data from 10 to 12 μs after transmitter current turn-off. The system is equipped with several devices enabling a complete modelling of the movement of the system in the air, facilitating excellent high-resolution images of the subsurface. An integrated processing and inversion system for SkyTEM data is discussed. While the authors apply this system with SkyTEM data, most of the techniques are applicable for airborne electromagnetic data in general. Altitude data are processed using a simple recursive filtering technique that efficiently removes reflections from trees. The technique is completely general and can be used to filter altitude data from any airborne system. Raw voltage data that are influenced by electromagnetic coupling to man-made structures are culled from the dataset to avoid uncoupled data being distorted by coupled data, and geometrical corrections are applied to correct for pitch and roll of the transmitter frame. Data are de-spiked and averaged using trapezoid-shaped filter kernels. A Laterally Constrained Inversion using smooth models is actively used to evaluate the processing, and the final inversion is tightly connected to the processing procedures.

A survey of current trends in near-surface electrical and electromagnetic methods

ElectricalandelectromagneticE&EMmethodsfornearsurface investigations have undergone rapid improvements over the past few decades. Besides the traditional applications in groundwater investigations, natural-resource exploration, and geological mapping, a number of new applications have appeared. These include hazardous-waste characterizationstudies,precision-agricultureapplications,archeological surveys, and geotechnical investigations. The inclusion of microprocessors in survey instruments, development ofnewinterpretationalgorithms,andeasyaccesstopowerful computers have supported innovation throughout the geophysical community and the E&EM community is no exception. Most notable are development of continuous-measurement systems that generate large, dense data sets efficiently. These have contributed significantly to the usefulness of E&EM methods by allowing measurements over wide areas without sacrificing lateral resolution. The availability of theseluxuriantdatasetsinturnspurreddevelopmentofinterpretation algorithms, including: Laterally constrained 1D inversionaswellasinnovative2D-and3D-inversionmethods. Taken together, these developments can be expected to improve the resolution and usefulness of E&EM methods and permit them to be applied economically. The trend is clearly towarddensesurveyingoverlargerareas,followedbyhighly automated, post-acquisition processing and interpretation to provide improved resolution of the shallow subsurface in a cost-effectivemanner.

A Review of the Principles and Applications of the NMR Technique for Near-Surface Characterization

Abstract This paper presents a comprehensive review of the recent advances in nuclear magnetic resonance (NMR) measurements for near-surface characterization using laboratory, borehole, and field technologies. During the last decade, NMR has become increasingly popular in near-surface geophysics due to substantial improvements in instrumentation, data processing, forward modeling, inversion, and measurement techniques. This paper starts with a description of the principal theory and applications of NMR. It presents a basic overview of near-surface NMR theory in terms of its physical background and discusses how NMR relaxation times are related to different relaxation processes occurring in porous media. As a next step, the recent and seminal near-surface NMR developments at each scale are discussed, and the limitations and challenges of the measurement are examined. To represent the growth of applications of near-surface NMR, case studies in a variety of different near-surface environments are reviewed and, as examples, two recent case studies are discussed in detail. Finally, this review demonstrates that there is a need for continued research in near-surface NMR and highlights necessary directions for future research. These recommendations include improving the signal-to-noise ratio, reducing the effective measurement dead time, and improving production rate of surface NMR (SNMR), reducing the minimum echo time of borehole NMR (BNMR) measurements, improving petrophysical NMR models of hydraulic conductivity and vadose zone parameters, and understanding the scale dependency of NMR properties.

An overview of a highly versatile forward and stable inverse algorithm for airborne, ground-based and borehole electromagnetic and electric data

We present an overview of a mature, robust and general algorithm providing a single framework for the inversion of most electromagnetic and electrical data types and instrument geometries. The implementation mainly uses a 1D earth formulation for electromagnetics and magnetic resonance sounding (MRS) responses, while the geoelectric responses are both 1D and 2D and the sheet’s response models a 3D conductive sheet in a conductive host with an overburden of varying thickness and resistivity. In all cases, the focus is placed on delivering full system forward modelling across all supported types of data. Our implementation is modular, meaning that the bulk of the algorithm is independent of data type, making it easy to add support for new types. Having implemented forward response routines and file I/O for a given data type provides access to a robust and general inversion engine. This engine includes support for mixed data types, arbitrary model parameter constraints, integration of prior information and calculation of both model parameter sensitivity analysis and depth of investigation. We present a review of our implementation and methodology and show four different examples illustrating the versatility of the algorithm. The first example is a laterally constrained joint inversion (LCI) of surface time domain induced polarisation (TDIP) data and borehole TDIP data. The second example shows a spatially constrained inversion (SCI) of airborne transient electromagnetic (AEM) data. The third example is an inversion and sensitivity analysis of MRS data, where the electrical structure is constrained with AEM data. The fourth example is an inversion of AEM data, where the model is described by a 3D sheet in a layered conductive host. We present an overview of a mature and general algorithm for inversion of most electromagnetic and geoelectrical data, ground-based and airborne. The implementation uses a 1D formulation for electromagnetics and MRS responses, geoelectric responses are 1D and 2D, and the 3D sheet’s response implements an overburden of varying thickness and resistivity.

Spatially constrained inversion for quasi 3D modelling of airborne electromagnetic data – an application for environmental assessment in the Lower Murray Region of South Australia

We present an application of spatially constrained inversion (SCI) of SkyTEM (airborne electromagnetic) data for defining spatial patterns of salinisation in the Bookpurnong irrigation area located in the lower Murray Basin of South Australia. SCI uses Delaunay triangulation to set 3D constraints between neighbouring soundings, taking advantage of the spatial coherency that may be present in the dataset. Conductivity information for individual soundings is linked through the spatial constraints, from well determined parameters to locally poorly determined parameters. For the survey presented here, SCI generated maps detail the spatial variability of floodplain salinisation, the extent of floodplain sediments influenced by lateral recharge and flushing along stretches of the Murray River, and the variable quality of groundwater in deeper semi-confined aquifers of the Murray Group. Available borehole and other ancillary information, such as vegetation density and health patterns, match the observed conductivity variations seen in the SCI results, even at the very near surface (≈2m depth). The SCI provides more accurate and spatially consistent results compared with those from single site inversions. They are also more uniform and detailed than maps obtained with single point Layered Earth Inversions or a laterally constrained inversion. In this example, the SCI provided reliable quasi 3D modelling, that confirmed and improved the hydrogeological knowledge of the area, indicating that the technique would have application with helicopter electromagnetic data in similar settings throughout the lower Murray Basin of Australia.

Nitrate reduction in geologically heterogeneous catchments--a framework for assessing the scale of predictive capability of hydrological models.

In order to fulfil the requirements of the EU Water Framework Directive nitrate load from agricultural areas to surface water in Denmark needs to be reduced by about 40%. The regulations imposed until now have been uniform, i.e. the same restrictions for all areas independent of the subsurface conditions. Studies have shown that on a national basis about 2/3 of the nitrate leaching from the root zone is reduced naturally, through denitrification, in the subsurface before reaching the streams. Therefore, it is more cost-effective to identify robust areas, where nitrate leaching through the root zone is reduced in the saturated zone before reaching the streams, and vulnerable areas, where no subsurface reduction takes place, and then only impose regulations/restrictions on the vulnerable areas. Distributed hydrological models can make predictions at grid scale, i.e. at much smaller scale than the entire catchment. However, as distributed models often do not include local scale hydrogeological heterogeneities, they are typically not able to make accurate predictions at scales smaller than they are calibrated. We present a framework for assessing nitrate reduction in the subsurface and for assessing at which spatial scales modelling tools have predictive capabilities. A new instrument has been developed for airborne geophysical measurements, Mini-SkyTEM, dedicated to identifying geological structures and heterogeneities with horizontal and lateral resolutions of 30-50 m and 2m, respectively, in the upper 30 m. The geological heterogeneity and uncertainty are further analysed by use of the geostatistical software TProGS by generating stochastic geological realisations that are soft conditioned against the geophysical data. Finally, the flow paths within the catchment are simulated by use of the MIKE SHE hydrological modelling system for each of the geological models generated by TProGS and the prediction uncertainty is characterised by the variance between the predictions of the different models.

Quantification of modeling errors in airborne TEM caused by inaccurate system description

Beingabletorecoveraccurateandquantitativedescriptionsof the subsurface electrical conductivity structure from airborne electromagneticdataisbecomingmoreandmorecrucialinmany applications such as hydrogeophysical and environmental mapping, but also for mining exploration. The effect on the inverted models of inaccurate system description in the 1D forward modeling of helicopter time-domain electromagnetic TEM data was studied. The most important system parameters needed for accurate description of the subsurface conductivity were quantified using a nominal airborne TEM system and three different reference models to ensure the generality of the conclusions. By calculating forward responses, the effect of changing the system transfer function of the nominal airborneTEM system was studied in detail. The data were inverted and the consequences of inaccuratemodelingofthesystemtransferfunctionwerestudiedin themodelspace.Errorsinthedescriptionofthetransferfunction influence the inverted model differently. The low-pass filters, current turn-off, and receiver-transmitter Rx-Tx timing issues primarily influenced the early time gates. The waveform repetition, gate integration, altitude, and geometry mainly influenced thelatetimegates.Depthofinvestigationishighlymodeldependent, but in general the early times hold information on the shallower parts of the model and the late times hold information on thedeeperpartsofthemodel.Amplitude,gain,andcurrentvariations affect the entire sounding and therefore the entire model. The results showed that all of these parameters should be measured and modeled accurately during inversion of airborneTEM data. If not, the output model can differ quite dramatically from the true model. Layer boundaries can be inaccurate by tens of meters, and layer resistivities by as much as an order of magnitude. In the worst cases, the measured data simply cannot be fittedwithinnoiselevel.