Abstract
With the rapid development of big data technology, its application in reservoir numerical simulation and drilling optimization is gradually becoming a key method to improve oilfield development's efficiency and scientific nature. This paper systematically reviews the latest advancements in big data technology in reservoir modeling and optimization, focusing on using massive geological, seismic, and production data to construct high-precision 3D reservoir models and improve drilling plan design and implementation through numerical simulation and optimization techniques. First, the core role of big data in reservoir modeling is analyzed and compared with traditional methods, highlighting its unique advantages in data integration, analysis, and prediction. Next, the process of big data-based reservoir modeling is elaborated, including data collection and preprocessing, model construction and calibration, and the application of optimization methods. Subsequently, the specific applications of numerical simulation in drilling optimization are discussed, especially the technological pathways that use real-time monitoring data and intelligent decision support systems to improve drilling success rates and reduce development costs. Typical case studies demonstrate the effectiveness of big data-driven reservoir numerical simulation and drilling optimization technologies in actual oilfield development, and future research directions and potential challenges are also proposed. This paper aims to provide scientific technical guidance and theoretical references for oilfield development through systematic review and analysis, promoting the intelligent upgrading of reservoir management and development technologies.
