Calibration of the Interaction Parameters between the Proppant and Fracture Wall and the Effects of These Parameters on Proppant Distribution

Abstract

Saltation and reputation (creep) dominate proppant transport rather than suspension during slickwater fracturing, due to the low sand-carrying capacity of the slickwater. Thus, the interaction parameters between proppants and fracture walls, which affect saltation and reputation, play a more critical role in proppant transport. In this paper, a calibration method for the interaction parameters between proppants and walls is built. A three-dimensional coupled computational fluid dynamics-discrete element method (CFD-DEM) model is established to study the effects of the interaction parameters on proppant migration, considering the wall roughness and unevenly distributed diameters of proppants. The simulation results show that a lower static friction coefficient and rolling friction coefficient can result in a smaller equilibrium height of the sand bank and a smaller build angle and drawdown angle, which is beneficial for carrying the proppant to the distal end of the fracture. The wall roughness and the unevenly distributed diameter of the proppants increase the collision between proppant and proppant or the wall, whereas the interactions have little impact on the sandbank morphology, slightly increasing the equilibrium height of the sandbank. low-viscosity fluid. Moreover, experiments on proppant transport in fracture networks [10,12,13] were mostly carried out to answer the debatable question of whether slickwater can transport proppants into secondary fractures or not. In addition to experimental research, computational fluid dynamics (CFD) methods were widely used to study proppant transport in fractures. The most common approach for modeling proppant transport is the Eulerian-Eulerian method in which the interaction between the particles and fluid is fully coupled [14][15][16][17][18][19]. In a recent study, Han et al. [20] used the Eulerian granular model to track proppant movement in various fractures for a better understanding of how proppant transport is influenced by fracture viscosity, proppant density, and pump rate. The second method is the Eulerian-Lagrangian model, which tracks individual particle movement with time and location with the Lagrangian framework and describes fluid flow with the Eulerian framework [21][22][23]. The discrete element method (DEM) [24] is a useful tool to simulate the behavior of particles, and it can be coupled with CFD to model the interaction between particles and the surrounding fluid. In recent years, the coupled CFD-DEM model was used to study fracturing fluid flow in fractures for its advantages of considering proppant-proppant, proppant-boundary, and proppant-fracturing fluid interactions [25][26][27][28][29][30][31][32]. Blyton et al. [26] first used the coupled CFD-DEM model to simulate the motion of particles flowing with a fluid between fracture walls, and the simulations individually determined that particle trajectories such as particle-to-particle and particle-to-wall collisions occur. Zhang et al. [28] used a two-dimensional coupled CFD-DEM model to study ...

Quantitative Study on Bed Load Proppant Transport during Slickwater Hydraulic Fracturing

“…Baldini et al [7] presented similar to those of Zhang et al [6]. Li et al [8] studied the influence of interaction parameters between proppants and walls on proppant transport with a CFD-DEM model. They found that the friction coefficient of the proppant affects the bed load proppant transport.…”

“…Particle Control Equations. By Newton's second law, the particle movement is predominantly translational and rotational, and the expressions are as follows [8,21]:…”

“…Fluid Control Equations. In the CFD part, the fluid phase is solved directly by the Eulerian-Eulerian model [8,11,14].…”

“…The size of the fracture used in their experiments was 2:44 m ðLÞ × 0:305 m ðHÞ × 0:00794 m ðWÞ, and the other parameters in their experiments were ρ f = 1000 kg/m 3 , ρ s = 2650 kg/m 3 , and d p = 0:0006 m. The static friction coefficient and rolling friction coefficient between the proppants (sand) in their experiments are not given. We took larger values than ceramic proppant [8], where μ m = 0:7 and μ d = 0:2. The results with various injection rates of fluid and proppant by the built model are shown in Table 4.…”

Revealing the Effect of Bifurcated Fractures and Fluid Parameters during Multiphase Slurry Transport

“…On the other hand, the CFD-DEM studies, such as works by Blyton, Zeng et al, and Yi et al, focus on non-diluted or dense particle–fluid mixture transport, elaborating the particle–particle interactions. This approach has been intensively adopted by modeling the proppant transport due to its excellence in capturing the fundamental physical processes of the particle movement in the dense slurry. − However, due to the extremely high computational costs of the method, these studies generally incorporated simplified fracture geometries to investigate the fundamental physics of the proppant transport in the fracture. As a result, recent advances in hydraulic fracture modeling studies seek to improve computational efficiencies.…”