The unconventional reservoir identification is presented based on rough set attribute reduction and particle swarm optimization(PSO), which means utilizing the rough set attribute reduction approach to reduce data space and using PSO clustering algorithm to deal with processing normalized data. Experiment shows that identification rate of the unconventional reservoir with reduced attributes is much higher than all feature attributes in PSO clustering algorithm.