<p>Deep tight sandstone reservoirs, which are characterized by complex features including compaction, consolidation, superposition of multi-stage channel sand bodies, and differential sedimentary infill, usually present different pore-permeability characteristics and evident heterogeneity. Tight sandstone reservoirs exhibiting low to ultra-low permeability can be categorized into various types of effective reservoirs according to porosity and permeability parameters as key assessment indicators. Therefore, within the macro background of low permeability, the development areas presenting relatively high porosity and permeability (sweet spots) are the primary targets for investigation. However, distinguishing these types of effective reservoirs remains difficult due to the inadequate discriminative power of single elastic parameters, which introduces challenges for direct pre-stack seismic prediction. To address this concern, we propose a method for defining effective reservoir indicators by integrating reservoir physical parameters and establishing a statistical rock physical relationship between the indicators and elastic impedance. This technique constructs a seismic prediction framework for multiple types of effective reservoirs in deep tight sandstones on the basis of the Bayesian probabilistic inversion strategy. Results from model testing and field data applications validate the strong potential of the method for exploration practice.</p>