Geostatistical methods based on two-point spatial-bivariate statistics have been used to model heterogene­ity within computational studies of the dispersion of con­taminants in groundwater reservoirs and the trapping ofCO2 in geosequestration reservoirs. The ability of these methods to represent fluvial architecture, commonly oc­curring in such reservoirs, has been questioned. We challenged a widely used two-point spatial-bivariate sta­tistical method to represent fluvial heterogeneity in the context of representing how reservoir heterogeneity af­fects residual trapping of CO2 injected for geosequestra­tion. A more rigorous model for fluvial architecture was used as the benchmark in these studies. Both the geo-statistically generated model and the benchmark model were interrogated, and metrics for the connectivity of high-permeability preferential flow pathways were quan­tified. Computational simulations of CO2 injection were performed, and metrics for CO2 dynamics and trapping were quantified. All metrics were similar between the two models. The percentage of high-permeability cells in spanning connected clusters (percolating clusters) was similar because percolation is strongly dependent upon proportions, and the same proportion of higher per­meability cross-strata was specified in generating both models. The CO2 plume dynamics and residual trapping metrics were similar because they are largely controlled by the occurrence of percolating clusters. The bench­mark model represented more features of the fluvial ar­chitecture and, depending on context, representing those features may be quite important, but the simpler geosta­tistical model was able to adequately represent fluvialreservoir architecture within the context and within the scope of the parameters represented here.