This paper tackles the volumetric representation of geophysical and geotechnical data, gathered during exploration surveys of the subsoil; in particular, we focus on the modeling and analysis of underwater deposits. The creation of a 3D model as support to geological interpretation has to take into account the heterogeneity of the input data, coming from offshore acquisition campaigns. Some data are massive, but cover the domain unevenly, e.g., along dense differently spaced lines, while others are very sparse, e.g., borehole locations with soil sampling and CPTU (Piezocone Penetration Test) locations. A automatic process is presented to generate the subsurfaces and volume defining a sub-seabed deposit, starting from the identification of relevant morphological features in seismic data. In particular, simplification and refinement based on geostatistics have been applied to generate regular 2D meshes from strongly anisotropic data, in order to improve the quality of the final 3D tetrahedral mesh. Furthermore, we also use geostatistics to predict geotechnical parameters from local surveys and estimate their distribution on the whole domain: in this way the 3D model will include relevant geological features of the deposit and allow extrapolating different geotechnical information with associated uncertainty. The volume characterization and its 3D inspection will support geological analysis and planning of future engineering activities. The developed methodology has been tested on two real case studies.
This paper tackles the volumetric representation of geophysical and geotechnical data, gathered during exploration surveys of the subsoil; in particular, we focus on the modeling and analysis of underwater deposits. The creation of a 3D model as support to geological interpretation has to take into account the heterogeneity of the input data, coming from offshore acquisition campaigns. Some data are massive, but cover the domain unevenly, e.g., along dense differently spaced lines, while others are very sparse, e.g., borehole locations with soil sampling and CPTU (Piezocone Penetration Test) locations. A automatic process is presented to generate the subsurfaces and volume defining a sub-seabed deposit, starting from the identification of relevant morphological features in seismic data. In particular, simplification and refinement based on geostatistics have been applied to generate regular 2D meshes from strongly anisotropic data, in order to improve the quality of the final 3D tetrahedral mesh. Furthermore, we also use geostatistics to predict geotechnical parameters from local surveys and estimate their distribution on the whole domain: in this way the 3D model will include relevant geological features of the deposit and allow extrapolating different geotechnical information with associated uncertainty. The volume characterization and its 3D inspection will support geological analysis and planning of future engineering activities. The developed methodology has been tested on two real case studies. (C) 2022 Elsevier Ltd. All rights reserved.
A computational approach for 3D modeling and integration of heterogeneous geo-data
Miola, Marianna;Vetuschi Zuccolini, Marino;Imitazione, Gianmario
2022-01-01
Abstract
This paper tackles the volumetric representation of geophysical and geotechnical data, gathered during exploration surveys of the subsoil; in particular, we focus on the modeling and analysis of underwater deposits. The creation of a 3D model as support to geological interpretation has to take into account the heterogeneity of the input data, coming from offshore acquisition campaigns. Some data are massive, but cover the domain unevenly, e.g., along dense differently spaced lines, while others are very sparse, e.g., borehole locations with soil sampling and CPTU (Piezocone Penetration Test) locations. A automatic process is presented to generate the subsurfaces and volume defining a sub-seabed deposit, starting from the identification of relevant morphological features in seismic data. In particular, simplification and refinement based on geostatistics have been applied to generate regular 2D meshes from strongly anisotropic data, in order to improve the quality of the final 3D tetrahedral mesh. Furthermore, we also use geostatistics to predict geotechnical parameters from local surveys and estimate their distribution on the whole domain: in this way the 3D model will include relevant geological features of the deposit and allow extrapolating different geotechnical information with associated uncertainty. The volume characterization and its 3D inspection will support geological analysis and planning of future engineering activities. The developed methodology has been tested on two real case studies. (C) 2022 Elsevier Ltd. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.