Numerical investigation of the fracture network morphology in multi-cluster hydraulic fracturing of horizontal wells: A DDM-FVM study

Abstract

Hydraulic fracturing is the most effective method to enhance the recovery of unconventional oil and gas via the formation of complex connected fracture networks. In this study, a pseudo three-dimensional fully fluid-solid coupled model is established to investigate the interaction between hydraulic fractures (HFs) and natural fractures (NFs), and the fracture network propagation process. The displacement discontinuity method (DDM) and finite volume method (FVM) are applied to simulate the rock deformation of the reservoir and fracturing fluid flow into the fracture networks, respectively. The influence of the stress shadow, flow rate distribution, comprehensive fluid loss, and complex extension behavior are considered in this model. A modified analytical crossing criterion is used to predict the interaction between the HF and NF. To improve the accuracy of the pressure calculation, the width of the fracture vertical cross-section is replaced by an equivalent width. The coupled equations are solved by Newton–Raphson iteration method. The numerical results of the proposed model agreed well with published analytical and experimental results. Based on the model, detailed sensitivity analyses are conducted to investigate the interaction between HFs and NFs, and the geometries of the fracture networks. The simulation results show that the fracture network morphology is significantly affected by NFs in naturally fractured reservoirs. The stress interference between HFs can weaken the effect of the horizontal stress difference; thus, NFs can be activated effectively. In addition, the complexity of the fracture network is proportional to the activation rate of the NFs. A more complex fracture network can be formed under the following conditions: a small horizontal stress difference, large NF length, low injection rate and low viscosity. It is noteworthy that a smaller value is not always better for cluster spacing. An optimal cluster spacing exist to obtain good results for reservoir stimulation.