Andrea Viezzoli

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.

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.

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.

Breaks in lithology: Interpretation problems when handling 2D structures with a 1D approximation

Most airborne electromagnetic AEM data are processed using successive 1D approximations to produce stitched conductivity-depthsections.Becausethecurrentinducedinthenearsurface by an AEM system preferentially circulates at some radial distancefromahorizontallooptransmittersometimescalledthe footprint, the section plotted directly below a concentric transmitter-receiver system actually arises from currents induced in the vicinity rather than directly underneath. Detection of paleochannels as conduits for groundwater flow is a common geo

Airborne electromagnetic modelling options and their consequences in target definition

Given the range of geological conditions under which airborne EM surveys are conducted, there is an expectation that the 2D and 3D methods used to extract models that are geologically meaningful would be favoured over 1D inversion and transforms. We do after all deal with an Earth that constantly undergoes, faulting, intrusions, and erosive processes that yield a subsurface morphology, which is, for most parts, dissimilar to a horizontal layered earth. We analyse data from a survey collected in the Musgrave province, South Australia. It is of particular interest since it has been used for mineral prospecting and for a regional hydro-geological assessment. The survey comprises abrupt lateral variations, more-subtle lateral continuous sedimentary sequences and filled palaeovalleys. As consequence, we deal with several geophysical targets of contrasting conductivities, varying geometries and at different depths. We invert the observations by using several algorithms characterised by the different dimensionality of the forward operator. Inversion of airborne EM data is known to be an ill-posed problem. We can generate a variety of models that numerically adequately fit the measured data, which makes the solution non-unique. The application of different deterministic inversion codes or transforms to the same dataset can give dissimilar results, as shown in this paper. This ambiguity suggests the choice of processes and algorithms used to interpret AEM data cannot be resolved as a matter of personal choice and preference. The degree to which models generated by a 1D algorithm replicate/or not measured data, can be an indicator of the data’s dimensionality, which perse does not imply that data that can be fitted with a 1D model cannot be multidimensional. On the other hand, it is crucial that codes that can generate 2D and 3D models do reproduce the measured data in order for them to be considered as a plausible solution. In the absence of ancillary information, it could be argued that the simplest model with the simplest physics might be preferred. Given the range of geological conditions under which airborne EM surveys are conducted, there is an expectation that 2D and 3D methods used to extract models of geological significance would be favoured over 1D inversion and transforms. We analyse data from the Musgrave province, South Australia, used for mineral and for hydro-geological prospecting.

The Impact on Geological and Hydrogeological Mapping Results of Moving from Ground to Airborne TEM

In the past three decades, airborne electromagnetic (AEM) systems have been used for many groundwater exploration purposes. This contribution of airborne geophysics for both groundwater resource mapping and water quality evaluations and management has increased dramatically over the past ten years, proving how these systems are appropriate for large-scale and efficient groundwater surveying. One of the major reasons for its popularity is the time and cost efficiency in producing spatially extensive datasets that can be applied to multiple purposes. In this paper, we carry out a simple, yet rigorous, simulation showing the impact of an AEM dataset towards hydrogeological mapping, comparing it to having only a ground-based transient electromagnetic (TEM) dataset (even if large and dense), and to having only boreholes. We start from an AEM survey and then simulate two different ground TEM datasets: a high resolution survey and a reconnaissance survey. The electrical resistivity model, which is the final geophysical product after data processing and inversion, changes with different levels of data density. We then extend the study to describe the impact on the geological and hydrogeological output models, which can be derived from these different geophysical results, and the potential consequences for groundwater management. Different data density results in significant differences not only in the spatial resolution of the output resistivity model, but also in the model uncertainty, the accuracy of geological interpretations and, in turn, the appropriateness of groundwater management decisions. The AEM dataset provides high resolution results and well-connected geological interpretations, which result in a more detailed and confident description of all of the existing geological structures. In contrast, a low density dataset from a ground-based TEM survey yields low resolution resistivity models, and an uncertain description of the geological setting.

3D modeling of buried valley geology using airborne electromagnetic data

Buried valleys are important hydrogeologic features of glaciated terrains. They often contain valuable groundwater resources; however, they can remain undetected by borehole-based hydrogeologic mapping or prospecting campaigns. Airborne electromagnetic (AEM) surveys provide high-density information that can allow detailed features of buried valleys to be efficiently mapped over large geographic areas. Using AEM data for the Spiritwood Valley Aquifer system in Manitoba, Canada, we developed a 3D electric property model and a geologic model of the buried valley network. The 3D models were derived from voxel-based segmentation of electric resistivity obtained via spatially constrained inversion of two separate helicopter time-domain electromagnetic data sets (AeroTEM and versatile time-domain electromagnetic [VTEM]) collected over the survey area. Because the electric resistivity do not provide unequivocal information on subsurface lithology, we have used a cognitive procedure to interpret the electric property models of the aquifer complex, while simultaneously incorporating supporting information for the assignment of lithology in the 3D geologic model. For the Spiritwood model, supporting information included seismic reflection data and borehole records. These data constrained valley geometry and provided lithologic benchmarks at specific borehole sites and along seismic transects. The large-scale AeroTEM survey provided the basis for modeling the regional extent and connectivity of the Spiritwood Valley Aquifer system, whereas the local-scale VTEM survey provided higher near-surface resolution and insight into a detailed shallow architecture of individual buried valleys and their fill.

Shallow Geothermal Exploration by Means of SkyTEM Electrical Resistivity Data: An Application in Sicily (Italy)

A novel procedure for estimating the geothermal energy exchanged by a unit volume was tested in northern Sicily (Italy), where public well data for depicting the complex geological setting were insufficient. An airborne electromagnetic survey was carried out in 2011, providing a 3D cell distribution of resistivity values. The integrated analysis of geological and resistivity data was used to identify six Litho-Electrical Units and to build a 3D geological model. This model was integrated with laboratory thermal conductivity measurements on rock samples, and was used to characterize the heat exchange at depths of up to 200 m, which in turn can be exploited for planning and designing geothermal heating and cooling plants using GSHP (Ground Source Heat Pump).