Abstract
With the rapid development of big data technology, the oil industry is embracing new opportunities for oil well optimization. This paper aims to explore the big data-driven oil well optimization technologies and their applications. First, the importance of big data technology in oil well optimization is outlined, with an introduction to methods of data collection and management, including the acquisition and processing of sensor data, production data, and geological data. Next, an in-depth analysis of data analysis techniques and optimization model construction is provided, focusing on the application of data mining, machine learning, and deep learning in production optimization, reservoir management, and predictive maintenance. Then, specific examples demonstrate the practical effectiveness of big data technology in real-time monitoring, production parameter optimization, reservoir development, cost control, and environmental monitoring. Finally, the paper discusses the challenges and future development directions in the process of big data-driven oil well optimization. Through a systematic exploration of these topics, this paper aims to provide valuable insights and practical references for the application of big data in the oil industry.
