Drill string vibration is a major factor influencing drilling efficiency,drill string failure,borehole stability and drilling safety.Early recognition of complex vibration is crucial to mitigating downhole tool damage and improving production time.In this paper,domestic and foreign application achievements of machine learning in drill string vibration recognition are fully investigated,and drill string vibration recognition and prediction methods are analyzed comprehensively from the perspective of data acquisition.Then,different algorithm models are comparatively studied in the aspects of framework,characteristic parameters and test effects,and their advantages and disadvantages are evaluated systematically.Finally,some ideas on the future development direction of drill string vibration recognition and prediction are put forward.And the following research results are obtained.First,by learning from abundant vibration data and extracting the characteristics,machine learning algorithm can establish a model for vibration classification and prediction.The accuracy and reliability of drill string vibration recognition and prediction can be improved by optimizing the algorithm and the model continuously.Second,with the continuous development of data acquisition and processing technologies,the surface and downhole multi-source data fusion method can analyze and process multiple data simultaneously,so it can identify surface and downhole data characteristics as much as possible,and it is predicted to be an important solution to downhole problems.Third,the continuous integration and development of drilling engineering and Al technology promotes vibration alleviation and ROP improvement jointly and provides reliable guidance and decision for drilling engineering.In conclusion,the application and development of machine learning in drill string vibration recognition and prediction further alleviates downhole drill string vibration in ultra-deep wells,improves the efficiency and safety of drilling engineering,and promotes the efficient and intelligent development of drilling process.
关键词
钻柱振动/深层/油气钻井/机器学习/分类算法/识别/预测
Key words
Drill string vibration/Deep/Oil and gas drilling/Machine learning/Classification algorithm/Recognition/Prediction
维普
万方数据