Research And Implementation Of Drilling Accident Recognition System Based On Machine Learning

There are a large number of uncertainties,ambiguities and random factors in the oil drilling process.Drilling accidents may occur at any time,which seriously threatens the safety of drilling.The timely identification and effective control of drilling accidents is a technical problem that drilling engineers and technicians have been committed to solving.At present,the commonly used drilling accident identification methods include: manual judgment,expert system,etc.,but these methods have the problem of insufficient knowledge acquisition in drilling accident identification.Therefore,this paper proposes a drilling accident identification system based on machine learning.This research is of great significance for drilling accident identification.This article first discusses the related theories of drilling accident identification,the realization principle of neural network,decision tree and the principle of fault tree analysis;Secondly,researched and constructed a drilling accident recognition model based on Cart decision tree,which can be used to identify common drilling accidents.On this basis,in view of the complexity and type diversity of lost circulation accidents,the fault tree analysis method is used to analyze the causes of lost circulation accidents,and a lost circulation accident identification model is constructed based on RBF neural network,which can further identify Different degrees of lost circulation,namely micro leaks,small leaks,medium leaks,large leaks,and serious leaks.Finally,the Python language is used to design and implement a drilling accident recognition system based on machine learning.The system mainly includes common drilling accident identification,lost circulation accident identification,case management and other functional modules.In order to verify the effectiveness of the accident identification model studied in this paper,the drilling data of an oil field is selected and the system is used to identify and test common drilling accidents.The results show that the drilling accident recognition system based on machine learning has a high accuracy in identifying drilling accidents.The system developed in this paper can improve the scientific of drilling accident recognition and provide an important basis for drilling technicians to prevent and control drilling accidents.