抄録
With the growing demand for efficient and precise production in the oil industry, oilfield production optimization and intelligent management have become key research areas. This paper systematically reviews the applications of big data and artificial intelligence (AI) algorithms in oilfield production optimization and intelligent management. First, it explores real-time monitoring systems for oilfields based on big data, covering data collection and processing, real-time monitoring technologies, anomaly detection, and early warning mechanisms. Next, it provides an in-depth analysis of the application of AI algorithms in oil extraction parameter optimization, explaining how machine learning and deep learning models enable dynamic optimization of extraction parameters and real-time decision support. Through specific case studies, the paper demonstrates the practical applications of these technologies in oilfields and their impact on improving production efficiency. Finally, it discusses future trends in oilfield production optimization and intelligent management, addressing technical challenges such as big data processing, AI algorithm complexity, and system integration. This paper aims to provide a comprehensive knowledge framework for researchers and engineers in the oilfield industry, promoting the deeper application and development of intelligent management technologies in oilfield production.
