Oilfield Water Drive Inefficient Injection And Production Identification And Auxiliary Governancel System

After long-term development of water flooding and polymer flooding,the oilfield has entered a period of high water cut.In order to improve the oil production of an oilfield,it is often necessary to apply common technologies such as water shutoff,injection control,and injection stop.These technologies have become important methods to improve the oil production.At present,with the increasing number of low-efficiency wells,the manual analysis of low-efficiency wells has higher complexity and slower speed,and the influencing factors of water plugging,injection control and injection stop are more complex.Therefore,combined with the comprehensive study of historical data and dynamic and static data of the oil field,computer technology is introduced into the actual business of the treatment wells,artificial intelligence technology is adopted to assist in judging the low-efficiency wells to be treated,and relevant treatment measures are recommended for the low-efficiency wells to be treated,so as to construct the identification and auxiliary treatment system for low-efficiency injection and production of water flooding in the oil field,and provide help for the increase of oil production in the oil field.In order to solve the practical problems such as the number of low-efficiency wells that need to be treated in the secondary mining process and the difficulty of controlling low-efficiency wells,this paper aims to solve the problem.First,the low-efficiency wells are screened out through the single well benefit evaluation chart.According to the calculation results,the inefficient layer in the inefficient well is determined,and the treatment measures for the treatment of the inefficient well layer are given,so as to design the inefficient well layer identification and auxiliary treatment system,and secondly,the intelligent optimization and treatment of the inefficient well layer.Measures and methods for effect prediction were studied.BP neural network algorithm was used to establish a predictive model of low-efficiency well production to ensure the increase of oil after treatment,and the knowledge of expert system was applied to low-efficiency well treatment measures to design inefficiency.The reasoning method of well selection wells not only makes the analysis of the optimal inefficient wells much less difficult,but also improves the accuracy and effectiveness of the preferred results.Finally,combined with the actual existence of well selection in oilfield treatment inefficient wells Problems and needs,developed an inefficient injection-production identification and auxiliary treatment system for oilfield oilfield flooding,and realized a reasonable method for analyzing low-efficiency well treatment measures.Anddecision-making,provide a scientific basis for improving oil field oil production.The system development is based on C# platform,and SOA-oriented architecture is adopted to realize application services.It summarizes many years of experience and methods of manual well selection.It has comprehensive functional design,simple and easy operation,time-saving and labor-saving operation.Through the application of the system,the auxiliary analysis and decision-making of low-efficiency well management measures are realized,which greatly improves the work efficiency and provides effective auxiliary analysis tools for standardized management of oil fields and helps oil fields.