Optimization of Fracturing Parameters by Modified Variable-Length Particle-Swarm Optimization in Shale-Gas Reservoir

Abstract

Summary Horizontal drilling and hydraulic fracturing are recognized as the most efficient techniques to enhance recovery in shale-gas reservoirs. Because of the exploitation difficulties and complex flow mechanism in shale gas, it is imperative to focus on the optimization of fracturing parameters. However, most of the current heuristic algorithms follow the principle that the variable dimension is constant during iteration, which leads to poor performance when dealing with dimension-varying problems. The optimization of fracturing parameters can be regarded as a typical dimension-varying problem when considering the difference among fracture properties such as half-length and conductivity. Thus an improved algorithm named modified variable-length particle-swarm optimization (PSO) (VPSO) (MVPSO) was proposed to automatically select the optimal fracturing parameters: the number of fractures as well as the corresponding fracture properties. Then, MVPSO was verified and compared with VPSO by several benchmarks. In addition, a gas/water two-phase model considering gas-adsorption and Knudsen-diffusion effects was used to describe the shale-gas flow in matrix and fracture domains. An embedded discrete-fracture model (EDFM) was applied to model the hydraulic-fracture geometries and fractal methods were adopted to generate the fracture networks. The results indicated that MVPSO showed better performance in both convergence speed and accuracy than that of VPSO, which also provided a new perspective for the optimization of fracturing parameters. Besides, the multispindle-shaped fracture-distribution pattern reached a higher net-present-value (NPV) contrast to that of homogeneous fracture distribution. The decrease of gas price leads to smaller and more nonuniform half-length distribution.