抄録
Carbonate reservoirs, characterized by their complex pore structures and significant heterogeneity, have long faced numerous challenges in oilfield development. Traditional water injection techniques have limited effectiveness in carbonate reservoirs, making it difficult to achieve efficient and uniform displacement of residual oil. In recent years, with the rapid advancement of artificial intelligence and big data technologies, intelligent water injection technology has provided a revolutionary solution for carbonate reservoir development. By integrating real-time monitoring, machine learning models, and optimization algorithms, this technology dynamically regulates injection rates and volumes to achieve precise control over water injection, thereby maximizing extraction efficiency and enhancing reservoir management effectiveness. This paper systematically explores the core mechanisms and key technologies of intelligent water injection in carbonate reservoirs, including data acquisition and processing, intelligent model construction, parameter optimization, and real-time decision support. Through case studies of practical engineering applications, the advantages of this technology in enhancing water injection efficiency and resource recovery are analyzed. Finally, the development prospects of intelligent water injection technology for carbonate reservoirs are discussed, and potential future research directions are proposed. This paper aims to provide theoretical support for the following argument. It also offers practical guidance for intelligent development under complex reservoir conditions.
