石油钻采工艺2025，Vol.47Issue(6)：695-703,9.DOI:10.13639/j.odpt.202508033
瞬态波动压力计算模型与起下钻临界速度智能决策方法
Transient surge/swab pressure calculation model and intelligent decision-making method for critical tripping speed in drilling and completion
摘要
Abstract
Transient surge/swab pressure during tripping in drilling and completion is a core factor triggering safety risks in deep wells with narrow safe mud weight windows.Based on unsteady flow theory,a transient surge/swab pressure calculation model during tripping was established and solved using the method of characteristics.The model was validated against field-measured data.Furthermore,constrained by the formation pressure profile,a tripping speed decision-making model was constructed based on the penalty function method,integrating such three swarm intelligence optimization algorithms as Genetic Algorithm(GA),Particle Swarm Optimization(PSO),and Grey Wolf Optimizer(GWO)to formulate an intelligent decision-making method for critical tripping speed.The results demonstrate that the simulated transient surge pressure aligns well with measured data in overall trends,indicating the model's effectiveness in capturing downhole pressure dynamics and its strong predictive capability.All three algorithms(GA,PSO,and GWO)maintained Equivalent Circulating Density(ECD)within the safe mud weight window,satisfying the constraints of the safe mud weight window.Statistical metrics from 50 repeated experiments,including mean,range,standard deviation,and confidence intervals,consistently identified GWO as the top-performing algorithm in terms of solution quality and safety,followed by PSO,while GA exhibited the poorest performance and lowest stability.The developed intelligent decision-making method for critical tripping speed provides scientific guidance for tripping operations,ensuring safety and enhancing operational efficiency.关键词
瞬态波动压力/起下钻/临界速度/智能决策/群智能优化/遗传算法/粒子群优化算法/灰狼优化算法Key words
transient surge/swab pressure/tripping/critical speed/intelligent decision-making/swarm intelligence optimization/Genetic Algorithm(GA)/Particle Swarm Optimization(PSO)/Grey Wolf Optimizer(GWO)分类
能源科技引用本文复制引用
WANG Feng,DUAN Yongqiang,TANG Hongbin,QIU Aimin,LIU Penglin,GUO Xiao,XI Yan..瞬态波动压力计算模型与起下钻临界速度智能决策方法[J].石油钻采工艺,2025,47(6):695-703,9.基金项目
国家自然科学基金面上项目"CCUS工程多场耦合及跨时空尺度条件下井筒密封完整性失效机理及控制方法研究"(52374001). （52374001）
