AI-Driven Dynamic-Static Integration for Complex Fault-Block Reservoir Rolling Development: A Case Study of Nanpu Sag

Aiming at the development problems of complex fault block reservoirs with dense fault systems and strong reservoir heterogeneity in Nanpu Sag, Bohai Bay Basin, this paper proposed a rolling development method fusing artificial intelligence (AI) and dynamic data in tectonic reservoir control mode. This study takes single well oil testing as the starting point, constructs a “single well analysis-structural re-understanding-target demonstration” grading framework, integrated seismic-logging-dynamic data, innovatively integrate key technologies under the collaborative constraints of AI and dynamic data to achieve subtle traps detection and quantitative reserves evaluation. Practice shows that this method supported rolling production in five potential areas of Nanpu Oilfield, deployed 10 new wells, added 1.96 million tons of geological reserves, and increased the success rate of oil testing from 65% to over 83% (p < 0.05). The research reveals that: ① the reuse of oil test data in old areas can reduce the risk of new well deployment; ② AI technology breaks through the bottleneck of micro-fault (< 10 m) identification; ③ the dynamic-static synergistic model can quantitatively evaluate reserves scalel. This method constructs a reproducible technical framework and empirical cases, providing reference for the efficient development of similar complex fault-block reservoirs.