Research on Digitalization Technology of Oil and Gas Fields Based on Digital Twin

With the advancement of digital transformation, digital twin technology, as a core component of Industry 4.0, is bringing revolutionary changes to the oil and gas field development sector. Based on a systematic review of relevant domestic and international literature, and incorporating the latest research advancements, this paper explores the evolutionary logic and development trends of digital twin technology in the oil and gas sector from three dimensions: technical architecture, application paradigms, and innovation pathways. The study reveals that by constructing a dynamic mapping mechanism between the physical and virtual spaces, digital twin technology effectively enables situational awareness and decision optimization across the entire development process. However, there are still intrinsic challenges in multi-source heterogeneous data integration and model self-evolution capabilities, which hinder its application effectiveness and scalability. This paper proposes a triple-innovation framework focused on intelligent sensing, autonomous decision-making, and ecological collaboration. It emphasizes the deep integration of intelligent algorithm clusters and novel computing architectures to drive the transformation of oil and gas development systems into adaptive and evolvable intelligent entities, providing a methodological reference for the industry’s digital transformation.