The Silurian reservoir in the Kataklonk Uplift area of the Tarim Basin is characterized by alternating sandstone and mudstone depositions, exhibiting strong heterogeneity with generally thin individual sand bodies. Traditional seismic waveform indication inversion techniques, while capable of identifying reservoir characteristics through impedance parameter calculations, lack sufficient sensitivity to minor lithological differences in complex formations with frequent sandstone-mudstone alternations, thus limiting reservoir prediction accuracy. To address this issue, this paper innovatively introduces a method combining Principal Component Analysis with Seismic Waveform Indication Inversion (PCA-SMI). First, through sensitivity analysis, Gamma Ray (GR) logging curves were determined as the input feature parameters for seismic waveform indication simulation inversion. Then, the first three principal components reflecting the main reservoir characteristics were extracted using principal component analysis to reconstruct the gamma ray curve, enhancing the feature curve's ability to identify different lithologies. Finally, the reconstructed gamma ray curve was used as input for lithological inversion via waveform indication simulation. Results demonstrate that this method significantly improves the identification accuracy of sandstone-mudstone interbedded reservoirs, optimizing the sandstone-mudstone discrimination threshold from 74.56 API to 57.6 API, effectively resolving issues of low vertical resolution and lateral discontinuity in inversion results. In practical applications, this method shows significant advantages in identifying individual sand bodies and precisely characterizing reservoir distribution, with prediction results achieving a 91.76% match with actual logging sandstone thickness. This achieves dual improvements in reservoir prediction accuracy and resolution, providing powerful technical support for oil and gas exploration under complex geological conditions.