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Geological surface reconstruction from 3D point clouds

The numerical simulation of phenomena such as subsurface fluid flow or rock deformations are based on geological models, where volumes are typically defined through stratigraphic surfaces and faults, which constitute the geometric constraints, and then discretized into blocks to which relevant petro...

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Autores principales: Serazio, Cristina, Tamburini, Marco, Verga, Francesca, Berrone, Stefano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374526/
https://www.ncbi.nlm.nih.gov/pubmed/34430294
http://dx.doi.org/10.1016/j.mex.2021.101398
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author Serazio, Cristina
Tamburini, Marco
Verga, Francesca
Berrone, Stefano
author_facet Serazio, Cristina
Tamburini, Marco
Verga, Francesca
Berrone, Stefano
author_sort Serazio, Cristina
collection PubMed
description The numerical simulation of phenomena such as subsurface fluid flow or rock deformations are based on geological models, where volumes are typically defined through stratigraphic surfaces and faults, which constitute the geometric constraints, and then discretized into blocks to which relevant petrophysical or stress-strain properties are assigned. This paper illustrates the process by which it is possible to reconstruct the triangulation of 3D geological surfaces assigned as point clouds. These geological surfaces can then be used in codes dedicated to volume discretization to generate models of underground rocks. The method comprises the following: - Characterization of the best fitting plane and identification of the concave hull of the point cloud which is projected on it - Triangulation of the point cloud on the plane, constrained to the Planar Straight Line Graph constituted by the concave hull The algorithm, implemented in C++, depends exclusively on two parameters (nDig, maxCut) which allow one to easily evaluate the optimal refinement level of the hull on a case by case basis.
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spelling pubmed-83745262021-08-23 Geological surface reconstruction from 3D point clouds Serazio, Cristina Tamburini, Marco Verga, Francesca Berrone, Stefano MethodsX Method Article The numerical simulation of phenomena such as subsurface fluid flow or rock deformations are based on geological models, where volumes are typically defined through stratigraphic surfaces and faults, which constitute the geometric constraints, and then discretized into blocks to which relevant petrophysical or stress-strain properties are assigned. This paper illustrates the process by which it is possible to reconstruct the triangulation of 3D geological surfaces assigned as point clouds. These geological surfaces can then be used in codes dedicated to volume discretization to generate models of underground rocks. The method comprises the following: - Characterization of the best fitting plane and identification of the concave hull of the point cloud which is projected on it - Triangulation of the point cloud on the plane, constrained to the Planar Straight Line Graph constituted by the concave hull The algorithm, implemented in C++, depends exclusively on two parameters (nDig, maxCut) which allow one to easily evaluate the optimal refinement level of the hull on a case by case basis. Elsevier 2021-05-26 /pmc/articles/PMC8374526/ /pubmed/34430294 http://dx.doi.org/10.1016/j.mex.2021.101398 Text en © 2021 The Authors. Published by Elsevier B.V. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Method Article
Serazio, Cristina
Tamburini, Marco
Verga, Francesca
Berrone, Stefano
Geological surface reconstruction from 3D point clouds
title Geological surface reconstruction from 3D point clouds
title_full Geological surface reconstruction from 3D point clouds
title_fullStr Geological surface reconstruction from 3D point clouds
title_full_unstemmed Geological surface reconstruction from 3D point clouds
title_short Geological surface reconstruction from 3D point clouds
title_sort geological surface reconstruction from 3d point clouds
topic Method Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374526/
https://www.ncbi.nlm.nih.gov/pubmed/34430294
http://dx.doi.org/10.1016/j.mex.2021.101398
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