西南石油大学学报（自然科学版）2025，Vol.47Issue(5)：121-133,13.DOI:10.11885/j.issn.1674-5086.2024.01.08.01
基于多维时序LSTM的超深井机械钻速预测方法
Prediction of Penetration Rate Method for Ultra-deep Well Based on Multi-dimensional Time Series LSTM
摘要
Abstract
In order to solve the problems of multiple factors,complex mechanism,nonlinear,strong coupling and other cha-racteristics of rate of penetration in the process of complex deep drilling,this paper proposes a method of ROP prediction based on multi-dimensional time series long short-term memory neural network.Based on the actual logging data of Well X-1 in Xinjiang,this paper selects engineering parameters,hydraulics parameters,lithology parameters and other parameters as model inputs through the feature correlation analysis and the physical meaning of traditional ROP equation,and analyzes the ROP prediction effect of multi-dimensional features under different parameter combination modes.The results show that ROP is positively correlated with rotational speed,torque and riser pressure,but negatively correlated with vertical depth,hook load,specific weight on bit,drilling fluid conductivity,outlet drilling fluid temperature,outlet displacement and PDC drill ability,while weakly correlated with pump stroke and drilling fluid density;different characteristic parameter combinations have different prediction accuracy on ROP,among which the optimal parameter combinations are specific weight on bit,rotational speed,torque,hook load,riser pressure,drilling fluid conductivity,outlet drilling fluid temperature,outlet displacement,vertical depth and PDC drillability extreme value.MAE of ROP prediction is 0.30 m/h,MAPE is 11.35％and R2 is 0.93;The optimal hyperparameter combination scheme of the model was determined by orthogonal experiment.The R2 was increased by 0.06.关键词
超深井/机械钻速/LSTM/超参数组合/正交实验Key words
ultra-deep well/rate of penetration/LSTM/hyperparameter combination/orthogonal experiment分类
石油、天然气工程引用本文复制引用
刘阳,陈思彤,向幸运,沈明华,马天寿..基于多维时序LSTM的超深井机械钻速预测方法[J].西南石油大学学报（自然科学版）,2025,47(5):121-133,13.基金项目
国家自然科学基金青年基金(52204016) （52204016）
中国博士后科学基金面上项目(2020M673576XB) （2020M673576XB）
西南石油大学启航计划(2021QHZ027) （2021QHZ027）
