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3D geological implicit modeling method of regular voxel splitting based on layered interpolation data

In view of the problems in traditional geological modeling methods, such as the insufficient utilization of geological survey data, the inaccurate expression of a stratigraphic model, and the large amount of model data, a 3D geological model cannot be smoothly loaded and rendered on the web end. In...

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Autores principales: Li, Jian, Liu, Peirong, Wang, Xinyu, Cui, Hao, Ma, Yurong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9381719/
https://www.ncbi.nlm.nih.gov/pubmed/35974051
http://dx.doi.org/10.1038/s41598-022-17231-x
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author Li, Jian
Liu, Peirong
Wang, Xinyu
Cui, Hao
Ma, Yurong
author_facet Li, Jian
Liu, Peirong
Wang, Xinyu
Cui, Hao
Ma, Yurong
author_sort Li, Jian
collection PubMed
description In view of the problems in traditional geological modeling methods, such as the insufficient utilization of geological survey data, the inaccurate expression of a stratigraphic model, and the large amount of model data, a 3D geological model cannot be smoothly loaded and rendered on the web end. In this paper, a 3D geological implicit modeling method of regular voxel splitting based on hierarchical interpolation data is proposed. This method first uses the boreholes and geological section data from a geological survey for data conversion and fusion, compares the applicability of different interpolation algorithms through cross-validation research, and uses the best fitting algorithm to interpolate and encrypt discrete points in the formation. Then, it constructs the regular voxels, designs five different regular voxel split types, and divides the voxels. In addition, the data structure design of the voxel split model is implemented, and the irregular voxel metadata structure is analyzed and displayed through Three.js. Using this method, based on the survey data of an area in Zhengzhou, the global workflow from data processing to model construction and visualization is demonstrated. The experimental results show that the model can integrate multisource hierarchical interpolation data; express different stratum structures accurately and smoothly, and can realize the rendering, spatial query and analysis of the internal information of a geological body in a browser.
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spelling pubmed-93817192022-08-18 3D geological implicit modeling method of regular voxel splitting based on layered interpolation data Li, Jian Liu, Peirong Wang, Xinyu Cui, Hao Ma, Yurong Sci Rep Article In view of the problems in traditional geological modeling methods, such as the insufficient utilization of geological survey data, the inaccurate expression of a stratigraphic model, and the large amount of model data, a 3D geological model cannot be smoothly loaded and rendered on the web end. In this paper, a 3D geological implicit modeling method of regular voxel splitting based on hierarchical interpolation data is proposed. This method first uses the boreholes and geological section data from a geological survey for data conversion and fusion, compares the applicability of different interpolation algorithms through cross-validation research, and uses the best fitting algorithm to interpolate and encrypt discrete points in the formation. Then, it constructs the regular voxels, designs five different regular voxel split types, and divides the voxels. In addition, the data structure design of the voxel split model is implemented, and the irregular voxel metadata structure is analyzed and displayed through Three.js. Using this method, based on the survey data of an area in Zhengzhou, the global workflow from data processing to model construction and visualization is demonstrated. The experimental results show that the model can integrate multisource hierarchical interpolation data; express different stratum structures accurately and smoothly, and can realize the rendering, spatial query and analysis of the internal information of a geological body in a browser. Nature Publishing Group UK 2022-08-16 /pmc/articles/PMC9381719/ /pubmed/35974051 http://dx.doi.org/10.1038/s41598-022-17231-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Li, Jian
Liu, Peirong
Wang, Xinyu
Cui, Hao
Ma, Yurong
3D geological implicit modeling method of regular voxel splitting based on layered interpolation data
title 3D geological implicit modeling method of regular voxel splitting based on layered interpolation data
title_full 3D geological implicit modeling method of regular voxel splitting based on layered interpolation data
title_fullStr 3D geological implicit modeling method of regular voxel splitting based on layered interpolation data
title_full_unstemmed 3D geological implicit modeling method of regular voxel splitting based on layered interpolation data
title_short 3D geological implicit modeling method of regular voxel splitting based on layered interpolation data
title_sort 3d geological implicit modeling method of regular voxel splitting based on layered interpolation data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9381719/
https://www.ncbi.nlm.nih.gov/pubmed/35974051
http://dx.doi.org/10.1038/s41598-022-17231-x
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