Research on Optimization of Digital Oilfield Operations and Maintenance Based on Process Neural Networks
In order to better ensure the stable operation of digital oilfields and maximize the output and operating efficiency of oil wells,in-depth research on the operation and maintenance optimization of digital oilfields is carried out,and a digital oilfield operation and maintenance optimization method based on process neural networks is proposed.Firstly,the basic principle of process neural networks is described,and then process neural networks are used to collect and process the operation data of digital oilfields to obtain the fault characteristics of digital oilfield equipment.Based on the fault characteristics,a data matching model of digital oilfield operation equipment is established,and process neural networks are used to identify the faults of digital oilfield operation equipment to complete the operation and maintenance optimization of digital oilfields.An experimental comparison and analysis link is established,and the results show that this method can effectively improve the accuracy of fault identification of oilfield operation equipment,maintain the identified equipment faults,improve the output and operation efficiency of oil wells,ensure the stable operation of digital oilfields,and provide a basis for subsequent related research in the field of digital oilfield operation and maintenance optimization.
万方数据
维普
