3D Quantitative Characterization of Fractures and Cavities in Digital Outcrop Texture Model Based on Lidar

Bo Liang, Yuangang Liu, Yanlin Shao, Qing Wang, Naidan Zhang and Shaohua Li
Additional contact information
Bo Liang: School of Geosciences, Yangtze University, Wuhan 430100, China
Yuangang Liu: School of Geosciences, Yangtze University, Wuhan 430100, China
Yanlin Shao: School of Geosciences, Yangtze University, Wuhan 430100, China
Qing Wang: School of Geosciences, Yangtze University, Wuhan 430100, China
Naidan Zhang: School of Geosciences, Yangtze University, Wuhan 430100, China
Shaohua Li: School of Geosciences, Yangtze University, Wuhan 430100, China

Energies, 2022, vol. 15, issue 5, 1-17

Abstract: The combination of lidar and digital photography provides a new technology for creating a high-resolution 3D digital outcrop model. The digital outcrop model can accurately and conveniently depict the surface 3D properties of an outcrop profile, making up for the shortcomings of traditional outcrop research techniques. However, the advent of digital outcrop poses additional challenges to the 3D spatial analysis of virtual outcrop models, particularly in the interpretation of geological characteristics. In this study, the detailed workflow of automated interpretation of geological characteristics of fractures and cavities on a 3D digital outcrop texture model is described. Firstly, advanced automatic image analysis technology is used to detect the 2D contour of the fractures and cavities in the picture. Then, to obtain an accurate representation of the 3D structure of the fractures and cavities on the digital outcrop model, a projection method for converting 2D coordinates to 3D space based on geometric transformations such as affine transformation and linear interpolation is proposed. Quantitative data on the size, shape, and distribution of geological features are calculated using this information. Finally, a novel and comprehensive automated 3D quantitative characterization technique for fractures and cavities on the 3D digital outcrop texture model is developed. The proposed technology has been applied to the 3D mapping and quantitative characterization of fractures and cavities on the outcrop profile for the Dengying Formation (second member), providing a foundation for profile reservoir appraisal in the research region. Furthermore, this approach may be extended to the 3D characterization and analysis of any point, line, and surface objects derived from outcrop photos, hence increasing the application value of the 3D digital outcrop model.

Keywords: digital outcrop model; feature detection; lidar; carbonate reservoir; characterization of fractures and cavities (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/5/1627/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/5/1627/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:5:p:1627-:d:755812

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().