0. Introduction
Unconventional oil and gas resources have become key to the world’s energy supply[
1]. Unconventional reservoirs are characterized by low permeability and low porosity. There is no production naturally due to the low flow rate[
2]. Hydraulic fracturing can efficiently promote the oil/gas flow into the wellbore by creating fractures within the reservoirs[
3]. However, hydraulic fractures tend to propagate along the path with low resistance, and it is difficult to create complex fracture networks. Temporary plugging and diverting fracturing (TPDF) can plug the previous fracture (PF) paths by injecting self-degradable diverters. In this way, the injection pressure can be enhanced, and diversion fractures (DFs) can be created along other paths. After generating a complex fracture network, the diverters can degrade and flow out to the ground[
4].
During TPDF, the PFs can induce additional stresses, and the apertures of the DFs are highly influenced by the existence of PFs[
5]. Fracture aperture determines the effect of the proppant transportation and the conductivity of the propped fractures. Quantitative investigation of fracture aperture is of great value to optimize the design of TPDF. Various models have been established to calculate fracture apertures. Sneddon and Elliott established the model for calculating the aperture of a Griffith fracture under internal pressure. This model considers the distribution of stress in the interior of an infinite 2D elastic medium[
6]. Penkins et al. reported that the fracture aperture is essentially controlled by fluid pressure drop within the fracture. Fractures of wide aperture can be generated by the high injection rate and viscous fluids. They derived the equations which permit the estimation of fracture apertures for a variety of flow conditions and both for vertical and horizontal fractures[
7]. Palmer and Carroll proposed models of three-dimensional (3D) fracture propagation to investigate the effects of tresses on the fracture aperture. The model can give an upper or safe limit on the pumping parameters to ensure proppant transportation[
8]. Morales described a pseudo-3D fracture model that can solve the coupled fluid flow and elastic rock deformation during fracture propagation. The fracture width was obtained from a plane-strain elasticity solution. The state of proppant transportation was tracked during the treatment[
9]. Todd et al. estimated the fracture aperture for arbitrary pressure distribution in porous media. They pointed out that the fluid leak-off, the fluid flow in porous media, and the pressure response should be incorporated in predicting fracture aperture[
10]. Guo et al. investigated the aperture of two fractures symmetrically located at the edge of a wellbore subjected to a uniform wellbore pressure. Detailed fracture aperture profiles for various in-situ stresses and fracture lengths are obtained. The closed-form solution for the fracture mouth aperture was derived based on dimensional analysis and the superposition principle[
11]. Shahri et al. provided a fast-running, semi-analytical workflow to accurately predict fracture aperture distribution and fracture re-initiation pressure accurately. The algorithm and workflow can account for near-wellbore stress perturbations, far-field stress anisotropy, and wellbore inclination[
12]. Zhang et al. developed a new semi-analytical line fracture solution that accounts for stress anisotropy. The new solution is simple to implement and has been verified against the finite element calculation[
13]. Liu et al. proposed an inversion algorithm in which the strains are related to the fracture widths through a Green function. A 3D displacement-discontinuity method is used to construct the Green function[
14]. Xu et al. developed the prediction model for dynamic fracture aperture based on the non-Newtonian fluid loss dynamic theory. The model is validated by field data. Parametrical analysis was conducted to investigate the effects of flow pattern index, pressure difference, and consistency coefficient on the dynamic fracture aperture[
15].
The distribution of fracture aperture has also been investigated through experimental and numerical methods. True tri-axil hydraulic fracturing experiments have been applied to investigate the fracture geometry, the fluid injection pressure, and the fracture aperture distribution. Zheng et al. investigated the effect of pore pressure on the fracture geometry and the fracture aperture. They pointed out that when the pore pressure increases by 4 MPa, the breakdown pressure can increase by 22.8%[
16]. Zhang et al. proposed a novel experimental process to model the propagation of multiple fractures. Rock splitting and 3D reconstruction technology were applied to characterize the fracture geometry. The fracture aperture was compressed by the existence of previous fractures[
17]. Wu et al. performed numerous triaxial hydraulic fracturing experiments to investigate HF propagation behavior. Seven types of HF geometries were observed[
18]. Shi et al. conducted a series of large-size hydraulic fracturing physical simulation experiments to investigate hydraulic fracture propagation in massive-distributed hydrate-bearing reservoirs. The effects of massive hydrate size, approaching angle, and fracturing fluid displacement were analyzed[
19]. Chang et al. conducted laboratory fracturing tests to investigate the influence of injection scenarios on the initiation, propagation, and aperture of hydraulic fractures. They concluded that the cyclic injection method can reduce the breakdown pressure by 24%. Pulse fracturing creates the most complex fracture geometry[
20]. Shi et al. performed true triaxial hydraulic fracturing experiments on gravel rocks with acoustic emission monitoring. Results show that the fracture aperture for a penetration fracture is the largest due to high fracturing energy. The diversion fracture exhibits the smallest fracture width[
21]. Wang et al. conducted hydraulic fracturing experiments to investigate the injection pressure and the overall fracture geometry during TPDF. The fracture aperture was also investigated by numerical methods[
22]. Wang et al. applied the 3D finite element method to investigate the fracture mouth aperture influenced by the previous fracture along a vertical well. The effects of the previous fracture can be neglected due to the small induced stress vertically[
23]. Wu and Olson applied the 3D boundary element method to analyze the methods for promoting uniform development of simultaneous multiple-fracture propagation in horizontal wells. Fractures can divert and compress with each other. Screenout is more likely to occur at the mouth of the inner fractures[
24].
In conclusion, the pattern of fracture aperture during hydraulic fracturing can be effectively investigated by the theoretical model, the experimental method, and the numerical method. The theoretical model can calculate the aperture of a single fracture, not multiple fractures. The size of the experimental samples is limited and the effects of the boundary condition cannot be neglected. The reported numerical simulations have not considered the effects of the previous fractures perpendicular to the diversion fracture during TPDF. In this work, a 2D fluid-solid coupling model is established to investigate the effects of 7 factors on the apertures of the initial and diversion fractures. The plug model is proposed to simulate the effect of the tight plug, and the propping model is proposed the simulate the effect of the proppant. This work finds out the dominant factors that determine the fracture aperture. Moreover, measurements are proposed to lower the risk of screenout.
1. Mathematical Equation
The simulation of hydraulic fracturing is a complex problem because multiple physical processes should be considered, including rock deformation, fracture initiation, fracture propagation, fluid flow within porous media, and fracture flow within the fracture. The controlling equations can be referred to Wang et al.[
25] Moreover, the reliability of the finite element method in simulating hydraulic fracturing has been verified by several researchers[26-30].
1.1. Rock Deformation
The rock equilibrium equation can be described by[
25]
Where
t is the surface traction vector per unit area, N/m
2;
f is the body force vector per unit volume, N/m
3;
I is the identity matrix, dimensionless;
δε is the matrix of virtual strain rate, s
-1;
δv is the matrix of virtual velocity, m/s.
is the matrix of effective stress, Pa.
1.2. Fluid Flow in Porous Media
The fluid continuity equation within the porous rock is [
25]
Where
J is the volume change ratio of porous media, dimensionless;
ρw is the fluid density, kg/m3;
nw is the porosity ratio, dimensionless;
vw is the seepage velocity of the fluid, m/s;
x is space vector, m.
1.3. Fluid Flow within Fractures
The tangential flow rate
qf within hydro-fractures is [
25]
Where
qf is the average fluid velocity, m
3/s;
w is the fracture width, m;
μ is the fluid viscosity, cp;
pf is the fluid pressure within the fracture, Pa.
The fluid continuity equation within fracture is [
25]
Where
qb and
qt are the normal flow velocity at the bottom fracture surface and the top fracture surface, respectively, m/s.
1.4. Fracture Initiation Law
The quadratic fracture initiation law is applied to determine the time when the fracture element begins to degrade: [
25]
Where are the real stresses in the three directions, are the corresponding tensile and shear strength.
1.1. Fracture Propagation Law
The Benzeggagh-Kenane fracture criterion is applied to simulate the fracture propagation state:
Where GequivC is the computed equivalent fracture energy release rate; GIC, GIIC, and GIIIC, are Model I (tension failure), Model II (shear failure under sliding), and Model III (shear failure under tearing) fracture energy release rates, respectively; in BK roles, GIIC equals to GIIIC.