Abstract: The Pinghu Slope in the Xihu Depression has developed delta reservoirs influenced by tides in the Pinghu Formation. Sedimentary sand bodies such as delta distributary channels, tidal sand bars, and tidal channels have fast changes in sedimentary facies and are difficult to identify; At the same time, due to the large burial depth of the target layer, the seismic response of the reservoir is mostly a "dark spot" seismic reflection with small impedance differences, further increasing the difficulty of identifying high-quality reservoirs. This article utilizes technologies such as ancient landform restoration, AI artificial intelligence fault identification, high impedance sandstone wedge AVO forward simulation, and extended elastic impedance to complete the study of the gully slope system, identification of high-quality reservoirs, and hydrocarbon detection in this area. The results indicate that U-shaped, V-shaped, and W-shaped valleys are developed in this area. The W valley is the main channel for sediment diversion; Four identical fault step type slope breaks were identified, and the segmented points controlled the input of sand bodies in the area; The gradient negative 90° phase rotation seismic body can effectively identify the "dark spot" reservoirs in this area; In summary, the optimal coordinate rotation angle for expanding elastic impedance in this area is 20°, completing the detection of major sand body hydrocarbons and indicating favorable areas for oil and gas exploration.