Hydraulic fracturing in naturally fractured rocks can potentially generate a complex network of connected fractures. Efficient design of stimulation heavily depends on understanding of the mechanisms of hydraulic and natural fracture interactions and coalescence. Termination or partial propagation of hydraulic fractures might occur in the presence of natural fractures with detrimental effects on the stimulation. Improving fracture design in unconventional reservoirs must be based on a solid understanding of HF-NF interactions in 3D. In this study we cast light on the problem of 3D fracture propagation in naturally fractured rocks and show the potential impact on network design, DFIT interpretation, and proppant transport. Unlike attempts by previous Investigators, we investigate hydraulic fracture propagation in the presence of natural fractures by development and use of a fully 3D coupled model. Our 3D model is based on displacement discontinuity method for the stress analysis and a finite element model for fluid flow calculations. The contact status of natural fractures are determined using contact elements along with the Mohr-Coulomb criterion.
The model simulation results show that the normal and shear stress on the natural fracture are affected by the approaching hydraulic fracture. In the case of hydraulic fracture arrest, the hydraulic fracture can propagate in other directions and tends to engulf the natural fracture. It should be emphasized that capturing the engulfing pattern is only possible through using a robust 3D HF-NF model and other 2D and simpler 3D models fail to predict this geometry. Moreover, as a development, we show and discuss the pumping pressure profile for hydraulic fracturing in the presence of natural fractures obtained from a fully 3D model. The results show that stress shadowing causes non-uniform aperture profiles along the NF which impacts the proppant transport.
Economic production of hydrocarbons from unconventional reservoirs relies on the stimulation by hydraulic fracturing. Extensive research has been directed towards understanding of the reservoir response to stimulation, including experimental, theoretical, and numerical modeling (Blanton, 1982; Koshelev and Ghassemi, 2003a, b; Dobroskok and Ghassemi, 2004; Dobrosko et al., 2005; Zhang and Jeffrey, 2006; Dahi-Taleghani and Olson, 2011; Sesetty and Ghassemi, 2012; 2017; Hu et al., 2019; Ye and Ghassemi, 2018; Kumar and Ghassemi, 2018; Kamali and Ghassemi, 2018; Gao and Ghassemi, 2019; Sesetty and Ghassemi, 2018; Zhang et al., 2009).