In response to challenges in petroleum technology practice—including delays in data feedback, insufficient digital twin validation, and fragmented on-site collaborative decision-making—this study investigates an innovation model driven by the integration of artificial intelligence and digital twins. It outlines the foundational elements of full-chain oil and gas data, field and pipeline network mapping, and intelligent algorithm applications, and presents practical approaches for leveraging operational data from the field to drive decision-making, validating strategies through digital twin simulations, and enabling collaborative decision-making through intelligent reasoning.