A three-dimensional geostatistically based iterative inverse method is presented for mapping spatial distributions of the hydraulic conductivity and sorption partitioning coefficient fields by sequential conditioning on both nonreactive and reactive tracer breakthrough data. A streamline-based semianalytical simulator is adopted to simulate chemical movement in a physically and chemically heterogeneous field and serves as the forward modeling. In this study, both the hydraulic conductivity and sorption coefficient are assumed to be random spatial variables. Within the framework of the streamline-based simulator an efficient semianalytical method is developed to calculate sensitivity coefficients of the reactive chemical concentration with respect to the changes of conductivity and sorption coefficient. The calculated sensitivities account for spatial correlations between the solute concentration and parameters. The performance of the inverse method is assessed by a synthetic tracer test conducted within an aquifer with distinct spatial features of physical and chemical heterogeneities. The study results indicate that our iterative stochastic inverse method is able to identify and reproduce the large-scale physical and chemical heterogeneity features. The conditional study on the geostatistical distributions of conductivity and sorption coefficient are expected to significantly reduce prediction uncertainties for solute transport in the medium.