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A method for cognitive 3D geological voxel modelling of AEM data

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Abstract

Airborne electromagnetic (AEM) data have proven successful for the purpose of near-surface geological mapping and are increasingly being collected worldwide. However, conversion of data from measured resistivity to lithology is not a straightforward task. Therefore, it is still challenging to make full use of these data. Many limitations must be considered before a successful geological interpretation can be performed and a reasonable 3D geological model constructed. In this paper, we propose a method for 3D geological modelling of AEM data in which the limitations are jointly considered together with a cognitive and knowledge-driven data interpretation. The modelling is performed iteratively by using voxel modelling techniques with tools developed for this exact purpose. Based on 3D resistivity grids, the tools allow the geologist to select voxel groups that define any desirable volumetric shape in the 3D model. Recent developments in octree modelling ensure exact modelling with a limited number of voxels.

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Acknowledgments

The software development is a part of the HYACINTS research project funded by The Danish Council for Strategic Research, Danish Agency for Science Technology and Innovation. Jens Christian Refsgaard is thanked for his helpful comments on an early version of the paper. Two anonymous reviewers are thanked for their reviews and helpful comments.

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Correspondence to Flemming Jørgensen.

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Jørgensen, F., Møller, R.R., Nebel, L. et al. A method for cognitive 3D geological voxel modelling of AEM data. Bull Eng Geol Environ 72, 421–432 (2013). https://doi.org/10.1007/s10064-013-0487-2

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  • DOI: https://doi.org/10.1007/s10064-013-0487-2

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