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Erschienen in: Journal of Visualization 4/2017

05.05.2017 | Regular Paper

A corner-point-grid-based voxelization method for the complex geological structure model with folds

verfasst von: Qiyu Chen, Gang Liu, Xinchuan Li, Zhiting Zhang, Yang Li

Erschienen in: Journal of Visualization | Ausgabe 4/2017

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Abstract

The 3D voxel model is the foundation of geological property modeling, and it is also an effective approach to achieve the 3D visualization of heterogeneous attributes in geological structures. Corner-point grid is a representative structured grid model that is widely used nowadays. When implementing subdivision for the complex geological structure model with folds, its structural morphology and bedding features should be fully considered to ensure the generated voxels keep its original morphology. And on the basis of which, the detailed bedding features and the spatial heterogeneity of the internal attributes will be reproduced and expressed in the voxel model. For the purpose of overcoming the shortcomings of the existing technologies, a new corner-point-grid-based voxelization method is proposed which aims at the fast conversion from the 3D geological structure model with folds to its fine voxel model. As the rule of isocline in Ramsay’s fold classification is adopted in the gridding, the generated voxel model conforms to the spatial features of folds, and the voxels of the laminas inside a fold match the result of geological sedimentation and tectonic movement. This will provide a carrier and model foundation for the subsequent attribute assignment as well as the quantitative analysis and evaluation. Through the comparative analysis between the examples and Ramsay’s description of fold’s isoclines, the effectiveness and advantages of this method are discussed and tested.

Graphical abstract

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Metadaten
Titel
A corner-point-grid-based voxelization method for the complex geological structure model with folds
verfasst von
Qiyu Chen
Gang Liu
Xinchuan Li
Zhiting Zhang
Yang Li
Publikationsdatum
05.05.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Journal of Visualization / Ausgabe 4/2017
Print ISSN: 1343-8875
Elektronische ISSN: 1875-8975
DOI
https://doi.org/10.1007/s12650-017-0433-7

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