Intelligent Video Surveillance Technology for Safety Risks in Oil and Gas Production Operations

The petroleum and petrochemical industry involves a massive volume of high-risk operations. The traditional risk management model relies on on-site inspections by monitoring personnel, which suffers from numerous regulatory blind spots and incomplete coverage.As the temporal and spatial coverage of video surveillance continues to expand, massive amounts of image data are generated.In this study, 1.4 million images of high-risk operation sites were collected and compiled. Utilizing computer vision technology, a multi-mechanism dynamic identification method for safety hazards was constructed, integrating object detection, pose estimation, and object tracking. Specifically, the object detection model first outputs information such as target types (e.g., human bodies, cranes), keypoints (e.g., crane boom keypoints), and IDs. Spatiotemporal attention mechanisms were incorporated into the object detection model to enhance the recognition accuracy of multi-scale and small-scale targets within the images. Finally, based on the violation behaviors that need to be determined, algorithm reasoning logic was designed to enable the computer to distinguish and identify the behaviors of key targets from complex video images, automatically analyzing and extracting critical information from video sources.This study developed 40 types of video recognition algorithms for operational hazards, such as "personnel standing under a crane boom" and "working at heights without wearing a safety harness" (achieving an accuracy rate of \geqslant 90 %). This enables the real-time, intelligent identification and analysis of violation behaviors, facilitating the transformation of operational risk management from a "human-based defense" to an integrated "human + technical + intelligent defense" model. It allows for early intervention in operational violations, thereby further elevating the standard of safety risk management.

Keywords: High-risk operations, Risk management, Computer vision, Video analysis, Hazard identification.