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

Flemming Jørgensen, Rasmus Rønde Møller, Lars Nebel, Niels-Peter Jensen, Anders Vest Christiansen, Peter B.E. Sandersen

    Research output: Contribution to journalArticleResearchpeer-review

    72 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)421-432
    Number of pages12
    JournalBulletin of Engineering Geology and the Environment
    Volume72
    Issue number3-4
    DOIs
    Publication statusPublished - Dec 2013

    Keywords

    • Airborne electromagnetic data
    • Groundwater
    • Octree
    • Three-dimensional geological model
    • Voxel modelling

    Programme Area

    • Programme Area 2: Water Resources

    Fingerprint

    Dive into the research topics of 'A method for cognitive 3D geological voxel modelling of AEM data'. Together they form a unique fingerprint.

    Cite this