基于锯齿型遗传算法的页岩气井钻井参数优化

Drilling parameter optimization of shale gas well based on saw-tooth genetic algorithm

针对重庆涪陵地区页岩气钻进过程中钻井参数优化困难,导致钻井成本难以下降的问题,以钻进过程中钻井参数组合优化为最佳经济目标,采用一种锯齿型遗传(saw-tooth genetic algorithm,saw-tooth GA)算法对目标函数进行求解。该算法提出了具有周期性重新初始化的可变群体大小,其遵循具有非等振幅和变化周期(saw-tooth GA)的锯齿方案,可以在约束条件下优化钻井参数。通过该遗传算法的快速计算,能够得到不同转速、钻压下的组合钻井参数,实现最佳经济效益,降低钻井成本,并且该算法与其他方法相比具有收敛速度快、容易理解且实现简单的特点。根据涪陵地区页岩气焦页某井现场实际情况,对其在直井段的钻井参数进行了优化计算。

In the process of drilling shale gas wells in the Fuling region of Chongqing,it is difficult to optimize drilling parameters,which makes it difficult to reduce drilling costs.The optimization combination of drilling parameters in drilling engineering was taken as the research object,and a saw-tooth genetic algorithm(saw-tooth GA)was used to perform the objective function.To solve the problem,the algorithm proposes a variable population size with periodic reinitialization,which follows a saw-tooth scheme with unequal amplitude and change period(saw-tooth GA),which can optimize drilling parameters under constraints.Example calculations show that the algorithm can achieve the best economic benefits at different rotational speeds and weights to reduce drilling costs.Compared with other methods,this algorithm has the characteristics of fast convergence,easy to understand and simple to implement.According to the actual situation of JY well in Fuling region,the drilling parameters in the vertical section are optimized and calculated in this paper.