Abstract
Because modeling the flow of gas and oil in fractured media is increasingly important, multipoint geostatistics approaches, such as single normal equation simulation and FILTERSIM, have become a focus of research in the simulation of sedimentary faces. However, there are problems when these methods are applied to the simulation of discrete fracture networks (DFNs). The biggest problem is that the generated fractures are discontinuous, behaving as separated and isolated points. This paper proposes an improved approach we call CCL-FILTERSIM, which combines FILTERSIM with a run-based, connected-component labeling algorithm to generate more continuous fractures. This paper focuses on the continuity of the simulated fracture network and adopts the scan of the training image, classification of the patterns, and the sequential simulation proposed by FILTERSIM. The principle innovation of the CCL-FILTERSIM approach is the choice of data pattern. Only patterns that form better continuous object patterns are chosen. This is realized by a connected-component labeling algorithm that calculates the connected runs of selected patterns and chooses the pattern with the least runs. Some cases are presented to compare realizations from CCL-FILTERSIM and FILTERSIM, which show that CCL-FILTERSIM yields more continuous objects than FILTERSIM. The DFNs generated by this method provide better conditions for subsequent fluid flow research.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China (Key Program) (Grant No. 51534006) and National Natural Science Foundation of China (Grant Nos. 51374181 and 51404206).
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This article is part of a Topical Collection in Environmental Earth Sciences on ‘‘Subsurface Energy Storage II’’, guest edited by Zhonghe Pang, Yanlong Kong, Haibing Shao, and Olaf Kolditz.
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For all the pixels, replace the provisional label with the representative label.
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Jia, M., Zhang, L. & Guo, J. Combining a connected-component labeling algorithm with FILTERSIM to simulate continuous discrete fracture networks. Environ Earth Sci 76, 327 (2017). https://doi.org/10.1007/s12665-017-6647-0
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DOI: https://doi.org/10.1007/s12665-017-6647-0