Research And Design Of A Pressure-controlled Drilling Overflow Monitoring And Diagnosis System Based On Cloud Computing

There are many types of drilling accidents.Overflow accidents are one of the most influential accidents on safe drilling.In the drilling process,the diagnosis of overflow accidents is not clear or improperly processed,and serious drilling accidents may occur.Therefore,if it is possible to timely and accurately find the overflow accident when the overflow occurs,well control measures in advance,control the development of overflow,prevent blowout and even blowout out of control,and ensure safe drilling is of great significance.At the same time,with the continuous development of modem information technology,the integration of nationalization(informatization and industrialization)has been deepened,and the development of new and old development kinetic energy and production system has been accelerated[1].The new generation of information technology represented by cloud computing,big data,Internet of Things,and mobile Internet is accelerating penetration and integration into all walks of life.Industrial cloud,industrial Internet,and smart devices have gradually become important national development strategies.However,as the national development engine of the oil and gas industry,in accordance with the guidance of the integration of the two,the oilfield exploration,development,production and automation,informationization,the application of the Internet of Things and cloud computing technology to all aspects of oil and gas,accelerate " The construction of Intelligent Oilfield(IOF)has accelerated the industrial upgrading of oil and gas industry and increased oil and gas production capacity has become an urgent problem to be solved.Based on this,this paper proposes the idea of applying cloud computing technology to the control and diagnosis system of pressure-controlled drilling overflow.Utilize the massive storage performance of cloud computing data and superior computing performance,combined with communication technology,computer technology and pattern recognition technology to quickly diagnose the drilling site spill accidents,guide the site to quickly take well control measures,and provide technology for safe drilling.stand by.Through the research of this paper,the following results were obtained:1.Research and analysis of relevant theories,and optimized the overflow monitoring and diagnosis method of pressure-controlled drilling based on vertical pressure sleeve pressure,and completed the design of digital mining system and the selection of related sensors.On this basis,the design of the system hardware and software is completed.2.Through the influence of non-overflow factors on the pressure of the vertical pressure sleeve,the research of data cleaning theory,the identification and repair model of the abnormal pressure data and missing data of the vertical pressure sleeve is established to ensure the accuracy of the vertical pressure sleeve monitoring and diagnosis of the overflow accident.Sex.At the same time,the research and analysis of the pattern recognition algorithm combined with the mutual independence of the vertical pressure and compression parameters,the naive Bayesian classification algorithm was established to diagnose the overflow accident of the drilling process.Through the in-depth study of Hadoop distributed system,a set of pressure monitoring drilling overflow monitoring and diagnosis system based on the Hadoop distributed system is designed and developed.The design of the overflow monitoring and diagnosis database was completed.The HDFS distributed file system,the MapReduce distributed computing module,and the data remote publishing module were developed by using the Java language.Finally,the virtual machine was developed to configure and deploy the entire cloud platform.4.The system is applied to the double-exploration XX well in Guangyuan District.The field application shows that the system can diagnose the overflow accident timely and accurately.At the same time,it has the ability of large-scale data storage and real-time parallel computing,and has a good application prospect.