Julien Guillemoteau

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.

Influence of grain size, shape and compaction on georadar waves: examples of aeolian dunes

SUMMARY Many ground penetrating radar (GPR) profiles acquired in dry aeolian environment have shown good reflectivity inside present-day dunes. We show that the origin of this reflectivity is related to changes in grain size distribution, packing and/or grain shape in a sandy material. We integrate these three parameters into analytical models for bulk permittivity in order to predict the reflections and the velocity of GPR waves. We consider two GPR cross-sections acquired over aeolian dunes in the Chadian desert. The 2D migration of GPR data suggests that dunes contain different kinds of bounding surfaces. We discuss and model three kinds of reflections using reasonable geological hypothesis about aeolian sedimentation processes. The propagation and the reflection of radar waves are calculated using the 1D wavelet modelling method in spectral domain. The results of the forward modelling are in good accordance with real observed data.

Regularization strategy for the layered inversion of airborne transient electromagnetic data: application to in-loop data acquired over the basin of Franceville (Gabon)

Airborne transient electromagnetic (TEM) is a cost‐effective method to image the distribution of electrical conductivity in the ground. We consider layered earth inversion to interpret large data sets of hundreds of kilometre. Different strategies can be used to solve this inverse problem. This consists in managing the a priori information to avoid the mathematical instability and provide the most plausible model of conductivity in depth. In order to obtain fast and realistic inversion program, we tested three kinds of regularization: two are based on standard Tikhonov procedure which consist in minimizing not only the data misfit function but a balanced optimization function with additional terms constraining the lateral and the vertical smoothness of the conductivity; another kind of regularization is based on reducing the condition number of the kernel by changing the layout of layers before minimizing the data misfit function. Finally, in order to get a more realistic distribution of conductivity, notably by removing negative conductivity values, we suggest an additional recursive filter based upon the inversion of the logarithm of the conductivity. All these methods are tested on synthetic and real data sets. Synthetic data have been calculated by 2.5D modelling; they are used to demonstrate that these methods provide equivalent quality in terms of data misfit and accuracy of the resulting image; the limit essentially comes on special targets with sharp 2D geometries. The real data case is from Helicopter‐borne TEM data acquired in the basin of Franceville (Gabon) where borehole conductivity loggings are used to show the good accuracy of the inverted models in most areas, and some biased depths in areas where strong lateral changes may occur. Keyword: Airborne electromagnetic,Transient electromagnetic, Imaging. Inversion. Regularization.

Regularization strategy for the layered inversion of airborne TEM data: application to VTEM data acquired over the basin of Franceville (Gabon).

Airborne transient electromagnetic (TEM) is a cost‐effective method to image the distribution of electrical conductivity in the ground. We consider layered earth inversion to interpret large data sets of hundreds of kilometre. Different strategies can be used to solve this inverse problem. This consists in managing the a priori information to avoid the mathematical instability and provide the most plausible model of conductivity in depth. In order to obtain fast and realistic inversion program, we tested three kinds of regularization: two are based on standard Tikhonov procedure which consist in minimizing not only the data misfit function but a balanced optimization function with additional terms constraining the lateral and the vertical smoothness of the conductivity; another kind of regularization is based on reducing the condition number of the kernel by changing the layout of layers before minimizing the data misfit function. Finally, in order to get a more realistic distribution of conductivity, notably by removing negative conductivity values, we suggest an additional recursive filter based upon the inversion of the logarithm of the conductivity. All these methods are tested on synthetic and real data sets. Synthetic data have been calculated by 2.5D modelling; they are used to demonstrate that these methods provide equivalent quality in terms of data misfit and accuracy of the resulting image; the limit essentially comes on special targets with sharp 2D geometries. The real data case is from Helicopter‐borne TEM data acquired in the basin of Franceville (Gabon) where borehole conductivity loggings are used to show the good accuracy of the inverted models in most areas, and some biased depths in areas where strong lateral changes may occur. Keyword: Airborne electromagnetic,Transient electromagnetic, Imaging. Inversion. Regularization.

1D sequential inversion of portable multi-configuration electromagnetic induction data

We present an algorithm that performs sequentially one-dimensional inversion of subsurface magnetic permeability and electrical conductivity by using multi-configuration electromagnetic induction sensor data. The presented method is based on the conversion of the in-phase and out-of-phase data into effective magnetic permeability and electrical conductivity of the equivalent homogeneous half-space. In the case of small-offset systems, such as portable electromagnetic induction sensors, for which in-phase and out-of-phase data are moderately coupled, the effective half-space magnetic permeability and electrical conductivity can be inverted sequentially within an iterative scheme. We test and evaluate the proposed inversion strategy using synthetic and field examples. First, we apply it to synthetic data for some highly magnetic environments. Then, the method is tested on real field data acquired in a basaltic environment to image a formation of archaeological interest. These examples demonstrate that a joint interpretation of in-phase and out-of-phase data leads to a better characterisation of the subsurface in magnetic environments such as volcanic areas.

Modelling an arbitrarily oriented magnetic dipole over a homogeneous half-space for a rapid topographic correction of airborne EM data

Most airborne electromagnetic (EM) processing programs assume a flat ground surface. However, in mountainous areas, the system can be at an angle with regard to the ground. As the system is no longer parallel to the ground surface, the measured magnetic field has to be corrected and the ground induced eddy current has to be modelled in a better way when performing a very fine interpretation of the data. We first recall the theoretical background for the modelling of a magnetic dipole source and study it in regard to the case of an arbitrarily oriented magnetic dipole. We show in particular how transient central loop helicopter borne data are influenced by this inclination. The result shows that the effect of topography on airborne EM is more important at early time windows and for systems using a short cut-off source. In this paper, we suggest that an estimate be made off the locally averaged inclination of the system to the ground and then to correct the data for this before inverting it (whether the inversion assumes a flat 1D, 2D or 3D sub-surface). Both 1D and 2D inversions are applied to synthetic and real data sets with such a correction. The consequence on the ground imaging is small for slopes with an angle less than 25° but the correction factor can be useful for improving the estimation of depths in mountainous areas.

Processing of Densely Sampled Electromagnetic Induction Data Collected across Peat Deposits

Subsurface conductivity imaging with mobile electromagnetic sensor is of growing interest for characterizing soils across large areas of several hectares. In this study, we evaluate the feasibility of characterizing peat deposits with densely sampled electromagnetic induction (EMI) data acquired by a four-configuration SLINGRAM sensor on a well-controlled test-site near Paulinenaue (Germany). We specially discuss the signatures of 2D/3D subsurface structures and the removal of their effects on the 1D inversion results. At this test-site, we performed 62 boreholes in order to collect ground-truth information regarding the spatial distribution of the peat layers. We also compare our inversion results to ground penetrating radar (GPR) data recorded along one selected profile across the peat body.

Comparison between 1D Inversion of Geophilus Data and 2D Inversion of Wenner Array Data

Summary When comparing the sensitivity function of the automatic resistivity profiler GEOPHILUS to the one of the WENNER array, one can see that the GEOPHILUS system is especially well designed for a 1D interpretation. In this study, we therefore compare the 1D inversion of GEOPHILUS data to the 2D inversion of WENNER data on a selected test site where the ground trust is known. The results show that the 1D inversion of GEOPHILUS data provides similar tomograms as the 2D inversion of WENNER data. In the future, the 1D interpretation will be a first choice for processing large GEOPHILUS data sets.

Fast 2D Inversion of Airborne Transient Electromagnetic Data: a Synthetic Case

Airborne transient electromagnetic surveying provides data sections with a sufficient coverage to perform 2D imaging of electrical conductivity within the ground. Full 2D inversion using numerical modeling with finite differences or finite elements is still a time-consuming method to process the large amount of data acquired during an airborne survey. We present a new 2D interpretation strategy and apply it on synthetic data. The results show that this method produces satisfying outcomes with a small computation time cost.

Influence of Grain Size Distribution and Shape on GPR Waves – Study of Aeolian Dunes

Ground penetrating radar (GPR), a geophysical method based on electromagnetic (EM) wave propagation, can provide very detailed and continuous images of the internal structures of aeolian dunes. In order to model and explain the origin of observed reflections, we build a model of electric permittivity which accounts for the grain size distribution and shape. By modelling the propagation of GPR waves in frequency domain, we have shown that grain size and grain shape have an influence on GPR reflectivity and we confirmed it by adjusting the modelled data to the real GPR data acquired in arid zones.