In this work we use the simplified 3D displacement discontinuity method (DDM) for fracture deformation computations in the context of a dynamic fracture propagation model. Our method is expanded to account for the effects of fluid flowrate distributions inside multiple fractures and for fracture height growth in laminated reservoirs. The fracture simulator is coupled with a proppant transport model based on the Eulerian-Eulerian continuum framework and accounts for gravitational proppant settling, proppant bridging, and the transition from Poiseuille to Darcy flow.
The coupled simulator includes Proppant Transport Efficiency (PTE) versus Perforation Flow Ratio (PFR) correlations based on the computational fluid dynamics/discrete element method analysis to describe the proppant distribution within each cluster. To the authors’ knowledge, this is the first application of a coupled simulator that combines a simplified 3D displacement discontinuity model and a method of proppant transport based on the continuum Eulerian-Eulerian approach for the solution of the problem of dynamic propagation of single and/or multiple planar fractures. We believe that the proposed coupled simulator will be an effective tool for the optimization of the effort for uniform fracture propagation and proppant distribution and has the potential to significantly improve oil recovery from unconventional (shale) reservoirs.
Field observations from the emerging downhole diagnostic techniques such as distributed acoustic sensing (DAS), distributed strain sensing (DSS), distributed temperature sensing (DTS), and perforation imaging strongly suggest an uneven proppant distribution inside each fracture (Molenaar and Cox, 2013; Ugueto et al., 2016). This leads to underperforming hydrocarbon production from individual fracture clusters. This proppant-caused underperformance can further impact the unevenness in production is caused by the location of fractures: heel-side clusters of a fracturing stage usually contribute more to hydrocarbon production than toe-side clusters (Cramer et al., 2019; Mao et al., 2021). There may be multiple reasons for these observations: stress shadowing effects between and within fracture clusters, reservoir heterogeneity, near-wellbore effects, and others.