Abstract

Abstract Geothermal resources have attracted global attention because of their renewability, cleanliness, and universality. The U.S. Department of Energy estimates that harnessing just 0.1% of the Earth's geothermal energy can power humanity for 2 million years. An improved geothermal system (EGS) efficiently extracts heat from deep hot dry rock (HDR). However, EGS is battling to assure safe drilling and appropriate fracturing to extract heat potential. Conventional laboratory techniques cannot detect fine-scale variability in HDR structures during loading. Due to its inherent heterogeneities, it is especially crucial to characterize deformation and frac-face damage during induced fracturingto unlock heat energy from HDR. This study uses three-dimensional digital image correlation (3D-DIC) to examine damage and deformation in HDR samples. HDR samples from the DOE Utah FORGE project's Well 16B(78)-32 were studied under uniaxial and diametrical compression using a precise 100kN electro-mechanical load frame with a continuous displacement of 0.05mm/min. The samples had a wide range of minerals. During the uniaxial and diametrical compression tests, a3D-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 under load. The 3D-DIC system is used for image processing, visualization, and analysis of the HDR damage process under various load circumstances. Our preliminary results of DIC-generated quantitative full-field strain maps (tension, compression, and shear) exhibiting all sequences involved in the damage process of HDR samples. To evaluate the sample damage, damage factors are measured using DIC maps; the tension-compression ratio is obtained at 5%-10%. The damage evolution process of HDR specimens is separated into four stages, which are evaluated by damage variables: initial damage stage, linear elastic, elastic-plastic, and plastic damage stage. The findings have a major impact on our ability to predict the damage process in EGS. DIC outperforms micro-Computed Tomography(µ-CT), Scanning Electron Microscope (SEM), andAcoustic Emission(AE) in terms of test range, affordability, accuracy, and monitoring of the entire field. This method overcomes the laboratory limitations for evaluating HDR damage heterogeneity. This image-based algorithm is better at understanding anisotropic and heterogeneous HDR fragmentation and predicting stimulated reservoir volume (SRV). Thus, the results of this study will enhance the effectiveness of hydraulic fracturing in HDR and heat recovery from EGS.

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