Aimed at the disadvantages of Fuzzy C Means Clustering (FCM) algorithm which is sensitive to initial values and easily falls into local convergence, a new FCM algorithm named as CQPSO-FCM is proposed in this paper, which makes a combination of FCM algorithm and Chaotic Quantum Particle Swarm Optimization (CQPSO) algorithm. In order to solve the problems mentioned above and improve the ability of fuzzy classification, CQPSO algorithm is used to initialize the membership matrix, which significantly improves the global optimum search ability of the proposed algorithm. What’s more, this method could be used to predict accurately the fluid of complex fracture-cavity carbonate reservoir. Because the common fluid director of AVO inversion would not be available enough in fluid identification of carbonate reservoir, this method is then employed to establish a relation of fluid and reservoir between well logs and elastic properties of AVO inversion. By this accurate relation, the fluid enrichment and fluid type are both identified. The case study results not only prove a practical applicability of the method in predicting the fluid distribution in carbonate reservoir, but also provide a new way for fluid prediction in carbonate reservoir by taking full advantage of pre-stack seismic data.