The thin interbedded sand bodies in the W oilfield of the South Turgay Basin,Kazakhstan,exhibit rapid lateral variation and poor connectivity.For many years,the application of conventional reservoir prediction methods has yielded unsatisfactory results,and unclear insights into the horizontal and vertical distribution characteristics of favorable reservoirs have severely constrained the oilfield's exploration and development.To address these challenges,this study adopted an integrated approach incorporating forward modeling,post-stack seismic processing,and multi-attribute fusion to develop a prediction methodology suitable for the geological conditions of the study area.Based on forward modeling that established the relationship between reservoir variation and seismic waveform changes,empirical mode decomposition and blue filtering were applied to enhance the dominant frequency and resolution of the seismic data.The multi-attribute fusion of waveform indication inversion results,root-mean-square amplitude,and instantaneous frequency ultimately delineated the distribution and thickness of the target sand bodies.The results demonstrate that this method effectively predicts the distribution and thickness of favorable sand bodies,with errors of less than 2 meters compared to drilled thicknesses across the field.The spatial distribution of reservoirs is consistent with geological understanding.This study provides valuable guidance for subsequent rolling evaluation and efficient development of the oilfield.