We investigated a new technique for aquifer characterization that uses cross-correlation of ambient seismic noise to determine seismic velocity structure of the Floridan aquifer system. Accurate characterization of aquifer systems is vital to hydrogeologic research and groundwater management but is difficult due to limited subsurface data and heterogeneity. Previous research on the carbonate Floridan aquifer system found that confining units and high permeability flow zones have distinct seismic velocities. We deployed an array of 9 short period seismometers from 11/2013 to 3/2014 in Indian Lake State Forest near Ocala, Florida, to image the hydrostratigraphy of the aquifer system using ambient seismic noise. We find that interstation distance strongly influences the upper and lower frequency limits of the dataset. Seismic waves propagating within 1.5 and 7 wavelengths between stations were optimal for reliable group velocity measurements and both an upper and lower wavelength threshold was used. A minimum of 100–250 hours of signal was needed to maximize signal to noise ratio and to allow cross-correlation convergence. We averaged measurements of group velocity between station pairs at each frequency band to create a network average dispersion curve. A family of 1-D shear-wave velocity profiles that best represents the network average dispersion was then generated using a Markov Chain Monte Carlo (MCMC) algorithm. The MCMC algorithm was implemented with either a fixed number of layers, or as transdimensional in which the number of layers was a free parameter. Results from both algorithms require a prominent velocity increase at ∼200 m depth. A shallower velocity increase at ∼60 m depth was also observed, but only in model ensembles created by collecting models with the lowest overall misfit to the observed data. A final round of modeling with additional prior constraints based on initial results and well logs produced a mean shear-wave velocity profile taken as the preferred solution for the study site. The velocity increases at ∼200 m and ∼60 m depth are consistent with the top surfaces of two semi-confining units of the study area and the depths of high-resistivity dolomite units seen in geophysical logs and cores from the study site. Our results suggest that correlation of ambient seismic noise holds promise for hydrogeologic investigations. However, complexities in the cross-correlations at high frequencies and short travel-times at low frequencies added uncertainty to the dataset.