A Fast Workflow for Automatically Extracting the Apparent Attitude of Fractures in 3-D Digital Core Images

Fractures play a crucial role as fluid conduits and reservoir spaces in reservoirs. The distribution and characteristics of fractures determine the presence of high-quality reservoirs. To accurately analyze and observe fracture parameters, three-dimensional (3-D) digital cores generated from compute...

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Veröffentlicht in:Processes 2023-09, Vol.11 (9), p.2517
Hauptverfasser: Zhou, Ying, Chang, Deshuang, Zheng, Jianxiong, Zhu, Douxing, Nie, Xin
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Sprache:eng
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Zusammenfassung:Fractures play a crucial role as fluid conduits and reservoir spaces in reservoirs. The distribution and characteristics of fractures determine the presence of high-quality reservoirs. To accurately analyze and observe fracture parameters, three-dimensional (3-D) digital cores generated from computed tomography (CT) are utilized. However, the current process of extracting fracture properties from these digital cores is time-consuming and labor-intensive. This paper introduces a new, fast, and automatic workflow for extracting the apparent dip angle and direction of fractures from 3-D digital core images. The proposed workflow involves several steps. Firstly, two perpendicular cross-sections are obtained from the digital core and converted into binary images. Next, the coordinates of four fracture feature points within the core image are automatically extracted. The fracture plane is then fitted using the least squares method based on the extracted coordinates. Finally, the apparent dip angle and direction of the fracture are calculated using the plane’s normal vector. By comparing and analyzing the proposed workflow with the original method, it becomes evident that the method proposed in this paper allows for quick, automated, and accurate extraction of the apparent dip angle and direction of fractures. The application of this workflow to extract fracture attitudes in 3-D micro-CT and full-hole digital core images significantly enhances efficiency.
ISSN:2227-9717
2227-9717
DOI:10.3390/pr11092517