Hydraulic tomography (i.e., a sequential aquifer test) has recently been proposed as a method for characterizing aquifer heterogeneity. During a hydraulic tomography experiment, water is sequentially pumped from or injected into an aquifer at different vertical portions or intervals of the aquifer. During each pumping or injection, hydraulic head responses of the aquifer at other intervals are monitored, yielding a set of head/discharge (or recharge) data. By sequentially pumping (or injecting) water at one interval and monitoring the steady state head responses at others, many head/discharge (recharge) data sets are obtained. In this study a sequential inverse approach is developed to interpret results of hydraulic tomography. The approach uses an iterative geostatistical inverse method to yield the effective hydraulic conductivity of an aquifer, conditioned on each set of head/discharge data. To efficiently include all the head/discharge data sets, a sequential conditioning method is employed. It uses the estimated hydraulic conductivity field and covariances, conditioned on the previous head/discharge data set, as prior information for next estimations using a new set of pumping data. This inverse approach was first applied to hypothetical, two-dimensional, heterogeneous aquifers to investigate the optimal sampling scheme for the hydraulic tomography, i.e., the design of well spacing, pumping, and monitoring locations. The effects of measurement errors and uncertainties in statistical parameters required by the inverse model were also investigated. Finally, the robustness of this inverse approach was demonstrated through its application to a hypothetical, three-dimensional, heterogeneous aquifer.