Abstract
Digital core models reconstructed using X-ray tomography (X-CT) enable the quantitative characterization of the pore structure in three dimensions (3D) and the numerical simulation of petrophysics. When the X-CT images accurately reflect the micro structures of core samples, the greyscale threshold in the image segmentation determines the accuracy of digital cores and the simulated petrophysical properties. Therefore, it is vital to investigate the comparison parameter for determining the key greyscale threshold and the criterion to describe the accuracy of the segmentation. Representative coquina digital core models from X-CT are used in this work to study the impact of grayscale threshold on the porosity, pore percolation, connectivity and electrical resistivity of the pore scale model and these simulations are calculated by Minkowski functions, component labeling and finite element method, respectively, to quantify the pore structure and simulate electrical resistivity. Results showed that the simulated physical properties of the digital cores, varied with the gradual increase of the greyscale threshold. Among the four parameters related to the threshold, the porosity was most sensitive and chose as the comparison parameter to judge the accuracy of the greyscale threshold. The variations of the threshold change the micro pore structures, and then the electrical resistivity. When the porosity of the digital core model is close to the experimental porosity, the simulated porosity exponent matches the experimental porosity exponents well. The good agreement proved that the porosity is the critical comparison parameter to describe the accuracy of image segmentation. The criterion is that the porosity of the digital core after segmentation should be close to the experimental porosity.
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Acknowledgment
We thank Patrick Corbett of Herriot-Watt University 510 for providing the CT scans of the samples. The investigation is financially supported by the National Science & Technology Major Special Project (No. 2016ZX05006-002), China Postdoctoral Science Foundation Funded Project (No.2018M632716), Shandong Province Post Doctor Innovative Project Special Fund, Open Project Fund of the National and Local Joint Engineering Research Center of Shale Gas Exploration and Development (No. YiqKTKFGJDFLHGCYJZX444-201901), and Chongqing Basic Research and Frontier Exploration Project (No. cstc2018jcyjax0503).
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Wang Hai-Tao, Lecturer, graduated from Heriot-Watt University with a PhD in petroleum engineering. He is currently a lecturer in the School of Petroleum Engineering in Chongqing University of Science and Technology. His main interests are well logging data processing and interpretation, digital petrophysical simulation, and digital rock and borehole model reconstruction.
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Hai-Tao, W., Li, W., Fu-Qiang, L. et al. Investigation of image segmentation effect on the accuracy of reconstructed digital core models of coquina carbonate. Appl. Geophys. 17, 501–512 (2020). https://doi.org/10.1007/s11770-020-0846-2
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DOI: https://doi.org/10.1007/s11770-020-0846-2