Abstract: In order to realize effective classification of low-permeability and tight sandstone reservoirs and clarify the classification boundary, and effectively guide the selection of reservoir development countermeasures, this paper used the methods of grey correlation, multivariate analysis, information superposition and cluster analysis to carry out comprehensive reservoir classification and determine the classification boundary. In this paper, firstly, based on grey correlation, the reservoir quality factor IRQ, main throat radius, movable fluid saturation, sorting coefficient and displacement pressure are selected as the main controlling factors for reservoir evaluation. Secondly，the comprehensive quantitative evaluation of the reservoir is completed by the information superposition of the multivariate analysis and the grey evaluation results, and K-means clustering method combined with probability distribution function is proposed and the boundary of each factor is clarified. Finally, a clustering method combined with probability distribution function is proposed. The results show that the average error between the calculated value of IRQ conversion model obtained from logging and experimental data and the measured value of core is 8.60%, which confirms the reliability of the model. The average errors of the optimized clustering algorithm and the single factor classification method are 13.57% and 19.63% respectively, and the former is more accurate. The rationality of the method is verified by the single well productivity: The daily oil production in stable production period of type Ⅰ well is above 7.48 t/d, that of type Ⅱ well is 4.37- 7.48 t/d, and that of type Ⅲ well is less than 4.37 t/d. 

Key words: tight sandstone；reservoir classification, grey correlation, multivariate analysis, information superposition, cluster analysis, Nanpu sag, faulted basin