There is great potential for development in the middle and shallow layers of the central depression area in the southern part of the Songliao Basin. The reservoirs in this area are mainly thin layers and thin interbeds, which require higher structural accuracy and reservoir identification from seismic data. In this study, spatial relative resolution processing technology was adopted to maintain the relative changes of reservoir spatial information, with the aim of eliminating the influence of near-surface and acquisition factors above the reservoir on wavelet consistency. This mainly utilizes comprehensive static correction and wavelet consistency processing to improve resolution and signal-to-noise ratio under the premise of amplitude preservation. The spatial relative resolution processing technique primarily leverages comprehensive static corrections and wavelet coherence processing to enhance resolution and signal-to-noise ratio (SNR) while preserving amplitude information. The application of this spatial relative resolution processing technique has demonstrated a significant ability to preserve underground reservoir information, highlight the seismic response characteristics of the reservoir, and enhance the micro-structural accuracy of the target interval. The imaging quality of thin-bed fluvial sand bodies has been notably improved, effectively increasing the prediction accuracy of thin and inter-bedded reservoirs, thus meeting the demands of detailed interpretation and supporting the development of oil and gas reservoirs in such environments. This technology addresses the issue where the absolute seismic resolution limit alone fails to satisfy geological requirements by solely improving vertical resolution. It enhances the spatial description capability of the reservoir and produces genuine geological interpretation results.