The complex faults, especially mid-deep faults, in the Laoyemiao area of the Nanpu Sag, the Bohai Bay Basin, are unclearly understood for their characteristics, constraining the structural and geological delineation of the area. The hydrocarbon enrichment in the Laoyemiao area is closely related to the faults, and thus the precise identification of mid-deep faults is of great significance for understanding the structural system and reservoir distribution in the area. In the past twenty years, artificial intelligence (AI) scholars developed new technologies and methods to solve engineering problems. Typically, the AI seismic data interpretation technology plays a critical role in improving the accuracy and efficiency of fault interpretation. In order to define the structural characteristics of the Laoyemiao area, the “2W1H” seismic data were processed by fault-constrained structure-oriented filtering, and then interpreted using the EasyTrack module of GeoEast independently developed by BGP. It is found that the imaging quality and accuracy of mid-deep faults are improved effectively. On this basis, the SN-trending strike-slip fault systems were discovered, and the structural pattern and evolution law of mid-deep faults in the Laoyemiao area were re-understood. The results are of great significance for the structural identification, reservoir evaluation and selection of exploration targets in this area.