Abstract: Faults are important channels for oil and gas migration and play a very important role in the migration and accumulation of oil and gas. Therefore, the identification and fine characterization of faults are very important for the understanding of oil and gas reservoirs and traps. The faults in P area of Xihu Depression are complex, with increasing formation depth, the difficulty of fault planar combination increases, which influences the description of trap characteristics and well location deployment. The maximum likelihood attribute recognition technology improves the imaging clarity of faults by calculating the maximum likelihood attribute on the basis of filtering the data volume. Compared with other fault recognition technologies such as coherence volume, it enhances the fault identification effect.This technology has been applied in P area of Xihu Depression and has enhanced the delineation accuracy of faults, which plays a crucial role in the identification of traps and the well location deployment.