Research On Optimization Of Fracturing Parameters For Horizontal Wells In Shale Gas Reservoirs

Shale gas reservoirs were tight gas reservoirs with poor porosity and permeability.And then conventional methods were no longer suitable,thus it was imperative to adopt fracturing methods to enhance gas recovery.The two key techniques were horizontal well technology and hydraulic fracturing technology.Fracturing techniques were successfully applied in field oil and gas reservoirs,but little work has been done on the design of parameters.According to statistics,about one-third of fracturing methods failed to achieve the expected productivity,mainly due to the complexity of fractures and reservoir characteristics as well as a large number of design variables.For the black-box problem of fracturing parameter optimization,it was urgent to establish a complete optimization design system to guide on-site construction operations.First of all,in term of the existing optimization studies on shale gas reservoir fracturing parameter,single-factor analysis and non-holistic optimization methods were difficult to accurately consider the interference between wells and fractures,the correlation between fracture parameters and the optimization time cost.A method based on surrogate model assisting particle swarm optimization was proposed to optimize the overall parameters from well to fractures in multi-well pads in shale gas reservoirs.In the model,multi-porosity,horizontal well friction,adsorption and desorption,non-Darcy flow were considered.At the same time,parameters such as well position,well spacing,number of fractures and half-length of fractures were taken into account for overall gas production as well as the economic benefits.The initial population was generated based on Latin hypercube sampling,and the surrogateassisted hierarchical particle swarm algorithm was used to optimize the parameters with the net present value as the objective function.In addition,in view of the fact that the current optimization of fracturing parameter cannot consider the difference of the property between fractures and the optimal number of wells,the dimension-varying algorithm was introduced and improved in the field of fracturing parameter optimization research,named modified variable-length particle swarm optimization(MVPSO).This method brook the limitation of constant dimension in conventional intelligent algorithms and surrogate models.This method was not only an inheritance of the above method,but also an innovation of the above method.An embedded discrete fracture model was applied to model the hydraulic geometries and fractal methods were adopted to generate the fracture networks.In addition,the method was extended to the multi-well pads,which solved the problem of the inability to optimize the number of wells in conventional methods.The results indicated that compared with traditional single-factor analysis,optimizing fracturing parameters in an overall perspective was more reasonable and effective,and the assistance of surrogate models can dramatically improve the iteration efficiency.When considering the difference between fractures,the half-length distribution of fractures is multidumbbell shaped,and the conductivity and half-length are in near-linear dependency.The optimal bifurcate angle is approximately 90°,with which the maximum depleted area can be obtained.When considering the multi-well problem,the optimal parameters of a single well were not same as that of multi-wells.The improved algorithm can effectively locate horizontal wells in high abundance areas.