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It is known and recognized that Induced Polarization effects can affect the Airborne Electromagnetic measurements. These effects, if not treated properly, can represent a source of artifacts, bad fitting, and false recovered structures during the inversion process. At the same time, recognize and properly model the polarization effects can provide a mapping of the spectral content of the recorded data, adding extra information to the results, and allows to properly model the EM. With this work, we modelled the spectral content of Airborne EM data and compared the results with ground IP measurements acquired in the same area. For the modelling procedure, we propose to use the same approach, in order to be more consistent in the modelling procedure. The data we used are from the Iberian Pyrite Belt, one of the most important mining districts in Europe and with the highest concentration of VMS worldwide. Given the geological complexity of the area and the different signatures of the mineralisation style, with our data integration we aim to evaluate the potentialities of the AIP modelling and its role for exploration., Open-Access Online Publication: May 29, 2023

IP effects can distort airborne EM data, usually producing, faster decays and, under certain conditions, changes in, signal polarity. These effects, if not recognized and, treated with a dispersive resistivity model, often lead to, artefacts in the resistivities recovered. Historically, the IP, effects in fixed-wing AEM systems have been put in the, 'too hard basket'. This was mainly due to their geometric, configuration (and its monitoring) that prevented an, unambiguous relation between negative voltages and IP, effects. Another deterrent was the high ground clearance,, expected to make possible IP effects insignificant. The, rapidly accumulating experience on IP effects in, helicopter EM systems, however, warrants further, research on fixed wing EM and IP. With this work we, therefore investigated the fixed wing EM systems, sensitivity to Induced Polarization effects, presenting, numerical experiments on the SPECTREMPLUS system., We carried out a great number of forward responses,, associated with different combinations of Cole & Cole, parameters in both homogeneous halfspaces and two and, three - layered models. The analysis showed the, SPECTREMPLUS system to be sensitive to the, presence of chargeable material, in several Cole &, Cole parameters domains. These effects vary non, monotonically with resistivity, and become more marked, with variations in the layering, i.e., adding a purely, resistive basement under a shallower chargeable layer., Deep conductors' responses can also be widely affected, by shallow chargeable strata. The result demonstrate that, IP effects are, at times, detectable by the fixed wing EM, systems. As is the case for the helicopter EM systems,, taking IP into consideration during processing and, modelling may increase the accuracy of both data and, derived resistivities., Open-Access Online Publication: March 01, 2023

The interest on Induced Polarization in AEM data (AIP) has significantly increased in recent years, both within the research community and in the industry. However, the inversion of AIP data is particularly ill-posed, especially when spectral modelling, such as Cole-Cole modelling, is used. In this study we present a novel approach for model space definition, in which the AIP inversion parameters are defined on model meshes which do not coincide with the forward meshes used for data modelling: the link between model and forward meshes is obtained interpolating the model mesh parameters into the forward mesh discretization. This spatial decoupling allows for defining the AIP model parameters, e.g. the Cole-Cole ones, on different model meshes, for instance one for each inversion parameter. In this way, it is possible to define the spectral parameters, like the time constant and the frequency exponent in the Cole-Cole model, on meshes coarser than the resistivity and chargeability ones, vertically and/or horizontally, with a significant improvement in parameter resolution. However, the novel approach is completely general, and allows for incorporating any kind of prior information through the definition of parameters in problem-tailored meshes. The novel inversion approach is tested on a VTEM AIP survey, highlighting the improvements in model resolution when compared to standard inversion approaches., Open-Access Online Publication: March 03, 2023

SUMMARY Modelling IP parameters, including dispersive resistivity, from AEM data showing clear IP effects is possible. Using the spatially constrained inversion approach, with forward response that account for the full Cole and Cole model, we recover realistic chargeability and “IP corrected “resistivities sections from two VTEM datasets, from Canada and Australia. The “IP corrected” resistivity sections often show better agreement with known geological features, while improving dramatically the data fit, with respect to those obtained without IP modelling. While the majority of the IP effect originate from shallow chargeable layers, there seems to be some positive correlation between an isolated deep chargeable anomaly and known base metal deposit location.

Accepted manuscript for publication on STOTEN: https://doi.org/10.1016/j.scitotenv.2020.139361

Peatlands play a key role in the global carbon cycle, sequestering and releasing large amounts of carbon. Despite their importance, a reliable method for the quantification of peatland thickness and volume is still missing, particularly for peat deposits located in the tropics given their limited accessibility, and for scales of measurement representative of peatland environments (i.e., of hundreds of km(2)). This limitation also prevents the accurate quantification of the stored carbon as well as future greenhouse gas emissions due to ongoing peat degradation. Here we present the results obtained using the airborne electromagnetic (AEM) method, a geophysical surveying tool, for peat thickness detection at the landscape scale. Based on a large amount of data collected on an Indonesian peatland, our results show that the AEM method provides a reliable and accurate 3-D model of peatlands, allowing the quantification of their volume and carbon storage. A comparison with the often used empirical topographic approach, which is based on an assumed correlation between peat thickness and surface topography, revealed larger errors across the landscape associated with the empirical approach than the AEM method when predicting the peat thickness. As a result, the AEM method provides higher estimates (22%) of organic carbon pools than the empirical method. We show how in our case study the empirical method tends to underestimate the peat thickness due to its inability to accurately detect the large variability in the elevation of the peat/mineral substrate interface, which is better quantified by the AEM method.