抄録
With the rapid development of artificial intelligence (AI) and big data technologies, the application of these advanced technologies in petroleum engineering has progressively deepened, showing significant potential, particularly in oilfield completion design and optimization. This paper systematically reviews the key applications of AI and big data in oilfield completion processes, covering areas such as data-driven completion parameter optimization, formation pressure and temperature prediction, real-time monitoring, and intelligent decision support. It provides a detailed analysis of how these technologies enhance the precision and safety of completion operations. Furthermore, the paper explores innovative applications of AI in completion safety management, focusing on optimizing the balance between operational safety and efficiency. The article concludes by summarizing current technical challenges, including data quality control, limited algorithm adaptability, and the need for interdisciplinary collaboration, while also highlighting future research directions. This study aims to serve as a valuable reference for the further application of AI and big data technologies in oilfield completion.
