José Perrin

Fast mapping of magnetic basement depth, structure and nature using aeromagnetic and gravity data: combined methods and their application in the Paris Basin

Assessment of deep buried basin/basement relationships using geophysical data is a challenge for the energy and mining industries as well as for geothermal or CO2 storage purposes. In deep environments, few methods can provide geological information; magnetic and gravity data remain among the most informative and cost-effective methods. Here, in order to derive fast first-order information on the basement/basin interface, we propose a combination of existing and original approaches devoted to potential field data analysis. Namely, we investigate the geometry (i.e., depth and structure) and the nature of a deep buried basement through a case study SW of the Paris Basin. Joint processing of new high-resolution magnetic data and up-to-date gravity data provides an updated overview of the deep basin. First, the main structures of the magnetic basement are highlighted using Euler deconvolution and are interpreted in a structural sketch map. The new high-resolution aeromagnetic map actually offers a continuous view of regional basement structures and reveals poorly known and complex deformation at the junction between major domains of the Variscan collision belt. Second, Werner deconvolution and an ad hoc post-processing analysis allow the extraction of a set of magnetic sources at (or close to) the basin/basement interface. Interpolation of these sources together with the magnetic structural sketch provides a Werner magnetic basement map displaying realistic 3D patterns and basement depths consistent with data available in deep petroleum boreholes. The last step of processing was designed as a way to quickly combine gravity and magnetic information and to simply visualize first-order petrophysical patterns of the basement lithology. This is achieved through unsupervised classification of suitably selected gravity and magnetic maps and, as compared to previous work, provides a realistic and updated overview of the cartographic distribution of density/magnetization of basement rocks. Altogether, the three steps of processing proposed in this paper quickly provide relevant information on a deep buried basement in terms of structure, geometry and nature (through petrophysics). Notwithstanding, limitations of the proposed procedure are raised: in the case of the Paris Basin for instance, this study does not provide proper information on Pre-Mesozoic basins, some of which have been sampled in deep boreholes.

Slopes of an airborne electromagnetic resistivity model interpolated jointly with borehole data for 3D geological modelling

ABSTRACT We investigate a novel way to introduce resistivity models deriving from airborne electromagnetic surveys into regional geological modelling. Standard geometrical geological modelling can be strengthened using geophysical data. Here, we propose to extract information contained in a resistivity model in the form of local slopes that constrain the modelling of geological interfaces. The proposed method is illustrated on an airborne electromagnetic survey conducted in the region of Courtenay in France. First, a resistivity contrast corresponding to the clay/chalk interface was interpreted confronting the electromagnetic soundings to boreholes. Slopes were then sampled on this geophysical model and jointly interpolated with the clay/chalk interface documented in boreholes using an implicit 3D potential‐field method. In order to evaluate this new joint geophysical–geological model, its accuracy was compared with that of both pure geological and pure geophysical models for various borehole configurations. The proposed joint modelling yields the most accurate clay/chalk interface whatever the number and location of boreholes taken into account for modelling and validation. Compared with standard geological modelling, the approach introduces in between boreholes geometrical information derived from geophysical results. Compared with conventional resistivity interpretation of the geophysical model, it reduces drift effects and honours the boreholes. The method therefore improves what is commonly obtained with geological or geophysical data separately, making it very attractive for robust 3D geological modelling of the subsurface.

Frame Effective Tilt Correction for HEM Data Acquired over Rugged Terrain

In a traditional HEM inversion scheme, the voltage data are usually normalized by the effective area of the system. This effective area depends on the tilt of the frame; the pitch and the roll of the frame are monitored during the survey with tilt-meters and used to calculate a correction term. However, using the measured tilt to calculate this term, it is assumed that the terrain is flat, which may lead to inaccuracies on the inversion results. Thus, though the correction term is generally small, it can prove important to accurately compute it in rugged terrain when high resolution is needed. The measured tilt has then to be corrected by the apparent slope of the ground in order to determine an effective tilt at each measurement location. In this work we compute the effective tilt and evaluate its contribution on inversion results. This was achieved on a recent survey conducted over La Reunion, which has a very rugged terrain. The inversion results obtained using the effective tilt were compared to the ones obtained with the measured tilt. Using the effective tilt in such environment has a clear effect in the inversion results, both on resistivity patterns and on the DOI.

3D Geological Modelling Improvement with Airborne Time Domain Electromagnetism

Standard geological modelling based on boreholes and geological maps can be strengthened using geophysical data. Constrains such as gravity, magnetic and seismic data have already been used. We propose a novel method combining boreholes and the resistivity model resulting from inversion of airborne time domain electromagnetic data. First, the “geophysical” top of the chalk has been identified in the resistivity model after a detailed cross-analysis of resistivities versus boreholes. Then, we jointly interpolated slopes extracted from this geophysical surface together with the top of the chalk in boreholes. Comparison of uncertainties between this model together with pure geological and geophysical models shows that the joint modelling yields the most accurate top of the chalk. A cross-section, intersecting five boreholes (two used as control boreholes) and displaying each of the three surfaces, highlights the usefulness to take into account “geophysical slopes” when modelling. The proposed joint modelling improves what is commonly obtained with geological or geophysical data. This makes the method very attractive for detailed 3D geological modelling.