Research And Development Of Logging On-Board Equipment Operation And Maintenance Management System

The normal and stable operation of logging on-board equipment is of great significance to oil exploration and development.Due to the remote location and harsh environment of oil wells,the previous operation and maintenance mode of logging onboard equipment with Manually report faults and regular maintenance is not only inefficient and high labor cost,but also difficult to find problems and faults in operation quickly and accurately,and lack of information management of operation and maintenance data.Promoting the intelligent operation and maintenance and information transformation and upgrading of logging on-board equipment will help to improve the preventive maintenance level and efficiency of logging on-board equipment,reduce the operation and maintenance cost,and improve the safety,efficiency and stability of logging operation.Therefore,this paper studies the operation and maintenance management system of logging on-board equipment.Firstly,according to the characteristics and existing problems of logging on-board equipment and operation and maintenance service,this paper analyzes the requirements of logging on-board equipment operation and maintenance management system,puts forward the overall scheme of logging on-board equipment operation and maintenance management system,and designs the functional structure of the system.Secondly,the key technologies of logging on-board equipment operation and maintenance management system are studied.Combined with the complete set of logging on-board equipment and the requirements of operation and maintenance resource management,this paper studies the complete set of logging on-board equipment file BOM management method for MRO,establishes the complete set of logging on-board equipment BOM model for MRO,puts forward the composite BOM management method for MRO information resource management,and its effectiveness in reducing data redundancy is verified by taking VDMS equipment as an example.At the same time,taking the logging on-board monitoring equipment as an example,this paper studies thefault diagnosis method of logging on-board equipment based on Bayesian network.In the process of establishing the Bayesian network structure,combined with expert knowledge and K2 learning algorithm,this paper constructs the Bayesian network structure,establishes the EM parameter learning model integrating expert prior knowledge,learns the parameters of BN,and obtains a complete BN fault diagnosis model,Finally,an example analysis and model verification are carried out.The results show that this method can provide a basis for accurate diagnosis of logging vehicle monitoring system.Finally,based on the above research,combined with the actual operation and maintenance situation and needs of a logging equipment supplier,the operation and maintenance management system of logging on-board equipment is developed.The system can realize the functions of equipment operation monitoring,equipment archives management,operation and maintenance service management,remote fault diagnosis,operation and maintenance data analysis and so on.The system realizes the operation and maintenance service information management of logging on-board equipment,which is of great value to improve the maintenance response efficiency and quality of logging onboard equipment and ensure the stable operation of logging operation.At the same time,At the same time,it also provides support for suppliers in the enterprise decision-making of equipment optimization and product quality improvement.