基于钻井成本和机械比能的钻井参数优化方法的研究及应用  

Research and Application of Drilling Parameter Optimization Method Based on Drilling Cost and Mechanical Specific Energy

作　　者：王建龙 顾振涛 刘轩 郭菲 罗洁 郑锋 WANG Jianlong;GU Zhentao;LIU Xuan;GUO Fei;LUO Jie;ZHENG Feng(Engineering Technology Research Institute of BHDC,CNPC,Tianjin 300280,China)

机构地区：[1]中国石油集团渤海钻探工程有限公司工程技术研究院,天津300280

出　　处：《自动化应用》2024年第18期215-217,221,共4页Automation Application

基　　金：中石油渤海钻探工程有限公司科技重大研发项目“钻完井智能综合分析决策系统开发”(2022ZD01F-03)。

摘　　要：为解决钻进过程中破岩能效低、机械钻速慢的问题,以邻井地质数据、实时采集的录井数据和井下工程参数为输入,最大化钻头能效转化和最小化钻井成本为优化目标,机泵设备极限为约束条件,建立约束贝叶斯优化算法模型进行优化求解,实时导航最优钻井参数。通过与NSGA-Ⅱ、随机搜索等优化算法的对比及实例井应用分析表明,所建立的贝叶斯优化算法在保证计算结果精度的同时还能保持时效性,适用于钻井参数实时导航,可以帮助司钻识别钻速挖潜区,规避了低效破岩工作区,为提高破岩效率提供了决策依据。To solve the problems of low rock breaking energy efficiency and slow mechanical drilling speed during the drilling process,a constrained Bayesian optimization algorithm model is established with neighboring well geological data,real-time logging data,and downhole engineering parameters as inputs.The optimization objectives are to maximize the conversion of drill bit energy efficiency and minimize drilling costs,with the limit of pump equipment as the constraint condition.The optimal drilling parameters are navigated in real-time.Through comparison with optimization algorithms such as NSGA-Ⅱand random search,as well as analysis of practical well applications,it is shown that the Bayesian optimization algorithm established can ensure the accuracy of calculation results while maintaining timeliness.It is suitable for real-time navigation of drilling parameters and can help drillers identify drilling speed potential areas,avoid inefficient rock breaking work areas,and provide decision-making basis for improving rock breaking efficiency.

关 键 词：机械比能 钻井参数 多目标优化 约束贝叶斯算法 

分 类 号：TE928[石油与天然气工程—石油机械设备]