基于NPSO的三维复杂井眼轨迹控制转矩的优选

The Complex Wellbore Trajectory Control Torque Optimization Based on NPSO Algorithm

针对三维复杂井眼轨迹优化问题中自变量多和约束条件复杂的特点,设计了一种新的粒子群算法(NPSO),以提高复杂井眼轨迹控制精度和优化速度。在各井段、套管长度及目标垂直井深等9个约束条件下,应用NPSO优化实际控制转矩(TCT),可以完成井身、井斜角、井斜方位角以及井段曲率等16个参数的优选,实现精确、高效的井眼轨迹控制。仿真结果表明:与MOGA和GA算法相比,NPSO优化TCT的结果更优,算法的运行速度更快。将NPSO应用于实际钻井过程中井眼轨迹控制,可以提高钻井效率,节约钻井成本,缩短钻井时间。

Considering the multi-variables and complex constrain conditions of the complex well trajectory op-timization,a new particle swarm optimization(NPSO)algorithm is designed to improve the accuracy and optimiza-tion speed of complex wellbore trajectory control.Under nine constraint conditions,such as the length of the well section and casing,and the vertical depth of the target,NPSO can be used to optimize the true control torque(TCT)to select the wellbore,inclination,azimuth and wellbore curvature,achieve accurate and efficient well traj-ectory optimization.The simulation results show that the TCT result by NPSO optimization is better and the algo-rithm runs faster.The method applied in optimizing the wellbore trajectory during actual drilling process would im-prove the drilling efficiency,save the drilling cost and shorten the drilling time.