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

doi:10.1007/s10064-013-0487-2

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 journal › Article › Research › peer-review

86 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 language	English
Pages (from-to)	421-432
Number of pages	12
Journal	Bulletin of Engineering Geology and the Environment
Volume	72
Issue number	3-4
DOIs	https://doi.org/10.1007/s10064-013-0487-2
Publication status	Published - Dec 2013

Keywords

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

Programme Area

Programme Area 2: Water Resources

Access to Document

10.1007/s10064-013-0487-2

Cite this

@article{119bbe7ec2ad4fc5aeee9921ebf1e390,

title = "A method for cognitive 3D geological voxel modelling of AEM data",

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.",

keywords = "Airborne electromagnetic data, Groundwater, Octree, Three-dimensional geological model, Voxel modelling",

author = "Flemming J{\o}rgensen and M{\o}ller, \{Rasmus R{\o}nde\} and Lars Nebel and Niels-Peter Jensen and Christiansen, \{Anders Vest\} and Sandersen, \{Peter B.E.\}",

note = "Funding Information: 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.",

year = "2013",

month = dec,

doi = "10.1007/s10064-013-0487-2",

language = "English",

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AU - Jørgensen, Flemming

AU - Møller, Rasmus Rønde

AU - Nebel, Lars

AU - Jensen, Niels-Peter

AU - Christiansen, Anders Vest

AU - Sandersen, Peter B.E.

N1 - Funding Information: 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.

PY - 2013/12

Y1 - 2013/12

N2 - 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.

AB - 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.

KW - Airborne electromagnetic data

KW - Groundwater

KW - Octree

KW - Three-dimensional geological model

KW - Voxel modelling

UR - https://www.scopus.com/pages/publications/84891151993

U2 - 10.1007/s10064-013-0487-2

DO - 10.1007/s10064-013-0487-2

M3 - Article

SN - 1435-9529

VL - 72

SP - 421

EP - 432

JO - Bulletin of Engineering Geology and the Environment

JF - Bulletin of Engineering Geology and the Environment

IS - 3-4

ER -

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

Abstract

Keywords

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