Abstract: The Haita Oilfield has entered a stage of medium-high water cut development. It is necessary to conduct research on high-precision fault identification technology by combining well logging and seismic data, deepen the understanding of complex fracture systems, and guide the fine extraction of remaining oil in fault areas. In view of the difficulties of strong multi-solution and difficult interpretation of fault seismic data, relevant technical research was carried out from three aspects. Firstly, spectral inversion and structure-guided filtering post-stack interpretive processing technology were used to improve the quality of seismic fault imaging. Secondly, to address the significant quality differences between new and old seismic data, the data was categorized into three levels based on dominant frequency. For low-frequency data, the fusion of maximum and minimum curvature attributes was preferred; for medium-frequency data, the RGB mode fusion was applied using three sets of single-frequency data bodies at 30 Hz, 15 Hz, and 50 Hz; for high-frequency data, the Hue Intensity Saturation fusion was performed on the coherent, inclination, and azimuth attribute bodies made based on the dominant frequency body of 25 Hz. The new seismic attributes obtained by the above fusion methods all improved the identification ability of seismic faults with corresponding quality. Finally, guided by the concept of staged fault interpretation, manual interpretation was conducted to solve the “axis cutting” problem in interpreting faults of complex fracture systems involving multiple intersecting generations. By comprehensively applying the above methods, the accuracy in characterizing complex fracture zones and minor faults has been effectively improved, and the new achievements in fault understanding have proven effective in guiding the deployment of expansion wells in fault areas.