Understanding hydraulic fracture mechanisms: From the laboratory to numerical modelling
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Abstract
The development of fracture networks associated with hydraulic fracturing operations are extremely complex multiphysics processes and there is still no accepted methodology for mapping or realistic recreating such fracture networks. This is an issue especially for modeling purposes, as, ideally, an accurate numerical representation, and subsequent numerical model, should be able to honor the trajectory, type, connectivity, and geometric properties of the complex fracture network generated. This research proposes a novel framework capable of conducting fluid flow numerical simulations based on mapped fracture networks induced during hydraulic fracturing laboratory experiments where a shale sample, under true triaxial reservoir stress conditions, is subjected to fluid injection to mimic a single stage open-hole in-situ hydraulic fracture operation. The resulting post-test fracture network of the shale sample is filled with fluorescent dyed epoxy and subsequently imaged. The images are segmented, and individual fractures are classified based on their geometrical characteristics, as parted bedding planes, opened natural fractures, and newly generated hydraulic fractures. The digital fracture network is numerically represented for fluid flow simulation using a dual-porosity model within the finite volume method. In the numerical reconstruction, fractures are implicitly represented in a set of cells with virtual fracture aperture. The properties of each grid cell are assigned based on fracture classification, and flow between grid cells is explicitly assigned based on the connectivity of the grid cells. Findings show faster fluid drainage parallel to bedding planes (horizontal) than in the vertical direction, indicating strong fluid flow anisotropy.
Document Type: Research highlight
Cited as: Abdelaziz, A., Ha, J., Li, M., Magsipoc, E., Sun, L., Grasselli, G. Understanding hydraulic fracture mechanisms: From the laboratory to numerical modelling. Advances in Geo-Energy Research, 2023, 7(1): 66-68. https://doi.org/10.46690/ager.2023.01.07
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DOI: https://doi.org/10.46690/ager.2023.01.07
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