Implementation Of Hazardous Operation Identification System For Oilfield Production Monitoring

The petroleum industry is an important basic energy source in China.In order to achieve the safe production of the petroleum industry,but also to reduce the number of on-site operators and obtain greater economic benefits,China has gradually introduced digital communication technology,automatic monitoring technology,mobile network,etc.into the safety management of the work site.In addition to the monitoring of the equipment status of the operation site,China’s oilfield enterprises gradually promote the video surveillance system to monitor the oilfield operation site,so as to timely discover the dangerous operation behavior of personnel and ensure safe production.At present,oilfield enterprises are mainly remote duty personnel use video surveillance systems to view video pictures in real time,and on-duty personnel monitor video pictures for a long time to reduce their vigilance,resulting in the inability to timely detect dangerous operation behaviors at the work site,and the real-time performance is poor.The main role of video surveillance is to hold accountable after the fact,so it is necessary to introduce artificial intelligence technology,based on the existing video surveillance system,establish an automatic identification system for dangerous operations of oilfield production monitoring,and realize intelligent video surveillance,so as to automatically process the on-site video taken by the video surveillance system and identify non-compliant actions in the operation.This paper uses artificial intelligence to establish a hazardous operation identification system for oilfield production monitoring.Through the method of object detection,the useless interference information of the video screen is filtered,dangerous actions are automatically identified,the key useful features in the video source are analyzed and extracted,and the abnormal situation in the monitoring screen is judged and alarmed in real time.This paper uses the YOLOv3(You Only Look Once version 3)algorithm for object detection,which improves the detection accuracy while maintaining the detection speed,especially small target detection.Dangerous operation behavior detection is also to detect small targets,and the algorithm can complete the experimental target detection task.In this paper,several improvements have been made to the YOLOv3 algorithm to improve the detection effect,including modifying the loss function,adding the spatial pyramid pooling(SPP)module,adding the attention mechanism,and introducing the Mobile Net v3 lightweight classification network.The main research contents of this paper include data processing,improving the YOLOv3 algorithm,designing the detection interface combined with Tkinter and Tkinterdnd2,and designing the hazardous operation identification system.Compared with the YOLOv3 algorithm,the average accuracy(m AP)value of the improved YOLOv3 algorithm is increased by 3.48%,which improves the detection accuracy of small targets.The realization of the hazardous operation identification system for oilfield production monitoring expands the function of the video surveillance system and provides favorable support for oilfield safety production.