Abstract

Abstract Caprock integrity is a critical concern in the successful implementation of geologic carbon capture and storage (CCS) projects. Caprock can break mechanically by radial cracking, plastic deformation, inner and outer debonding, and channelling. Understanding these failure mechanisms is crucial for designing robust management strategies in CCS applications. The classical approach is limited, so this study uses three-dimensional digital image correlation (3D-DIC) to study caprock sample deformation and failure for carbon capture and storage (CCS) reservoir to ensure caprock integrity. Caprock samples from CCS reservoirs were put through diametrical compression using a precise 100 kN electro-mechanical load frame that moved at a rate of 0.05mm/min. The samples had a wide range of minerals. During the diametrical compression tests, a 3D-DIC image capture system was set up to watch the samples without touching them at a rate of 5 frames per second. A black-and-white speckle pattern is affixed to the specimen to monitor its deformation underload. The 3D-DIC system is used for image processing, visualization, and analysis of the caprock sample damage process under various load circumstances. The study uses DIC-generated strain maps to analyze the process of caprock samples breaking, revealing a tension-compression ratio between 2% and 5%. The damage evolution process is divided into four stages: initial, linear elastic, elastic-plastic, and plastic damage. The results show that shale damage changes over time when samples have anisotropy and distinct heterogeneity, potentially causing caprock integrity issues. This study focuses on predicting damage processes in caprock integrity in CCS using various methods. 3D-DIC outperforms these methods in terms of test range, affordability, accuracy, and field monitoring. This image-based algorithm is better at understanding anisotropic and heterogeneous conditions. The results will enhance the effectiveness of examining caprock integrity in CCS outperforms other methods in terms of test range, affordability, accuracy, and field monitoring.

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