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Abstract

Summary

This study examines digital rock images obtained from various techniques, including full-diameter core CT, micro-CT, FIB-SEM, and SEM, from the Wufeng-Longmaxi Formation in the TY gas field, a shale demonstration area in Sichuan province, China. A workflow utilizing multi-scale 3D and 2D digital core was presented to identify and extract pore characteristic parameters. The workflow achieves recognition of pores and fractures from meso-fractures to nano-pores: Meso-fractures are extracted using the connected domain analysis method for full-diameter CT; Micro pores and fractures are identified by using threshold segmentation methods in Micro-CT and FIB-SEM, and the pore network models are established; Different types of pores in SEM images are automatic identified through deep learning methods. For quantitative parameter characterization, parameters such as apparent fracture attitude and fracture density are calculated using the least squares method and connected domain analysis respectively. For 3D micro-nano-scale pores extracted from Micro-CT and FIB-SEM, features such as pore radius, coordination number can be calculated based on the maximum ball algorithm. For nano-scale pores identified in SEM, parameters including facet porosity, pore diameter can be computed using connected domain analysis. The proposed workflow can accurately describe the pore and fracture features of reservoirs at the meso-to-micro scale.

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/content/papers/10.3997/2214-4609.202477218
2024-11-20
2026-02-08

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/content/papers/10.3997/2214-4609.202477218
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Identification and Parameter Characterization of Pores and Fractures in Shales Based on Multi-Scale Digital Core Data
Conference Proceedings 2024, 1 (2024); https://doi.org/10.3997/2214-4609.202477218
/content/papers/10.3997/2214-4609.202477218
/content/papers/10.3997/2214-4609.202477218
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