Research on AI-Based Oil and Gas Pipeline Leak Detection and Localization Technology

Oil and gas pipelines, as a crucial part of the global energy transmission, play an essential role in ensuring energy security and efficient transportation. However, pipeline leakage is a significant problem that has long plagued the industry, causing not only severe environmental damage but also potentially leading to major safety incidents and resulting in enormous economic losses. Traditional leakage detection methods, such as those based on pressure and flow monitoring, although effective in some cases, are often limited by high false alarm rates and low sensitivity, especially in detecting small-scale or concealed leaks.In recent years, with the rapid development of artificial intelligence technology, its application in oil and gas pipeline leak detection and localization has increasingly gained attention. Artificial intelligence technologies, particularly machine learning and deep learning algorithms, can identify subtle signs of leaks by analyzing large amounts of data, thereby enabling earlier warnings of leaks. These technologies can improve the accuracy and efficiency of detection while reducing false alarm rates, offering a new perspective and method for the safe operation of pipelines.This paper aims to explore and analyze the application of artificial intelligence technology in the field of oil and gas pipeline leak detection and localization. We will first analyze the impact of oil and gas pipeline leaks, then review the limitations of traditional detection technologies, and discuss in detail how artificial intelligence can improve existing leak detection methods. Through specific case studies and analysis of experimental data, this paper will demonstrate the significant advantages of artificial intelligence technology in enhancing the accuracy and efficiency of leak detection. Finally, we will discuss the current challenges and potential directions for future development, emphasizing the importance of further research.