Analysis of synthetic data was performed to determine the most cost-effective tomographic monitoring system for a geologic carbon sequestration injection site. Artificial velocity models were created that accounted for the expected velocity decrease due to the existence of a CO₂ plume after underground injection into a depleted petroleum reservoir. Seismic events were created to represent induced seismicity from injection, and five different geophone arrays were created to monitor this artificial seismicity. Double-difference tomographic inversion was performed on 125 synthetic data sets: five stages of CO₂ plume growth, five seismic event regions, and five geophone arrays. Each resulting velocity model from tomoDD—the double-difference tomography program used for inversion—was compared quantitatively to its respective synthetic velocity model to determine an accuracy value. The quantitative results were examined in an attempt to determine a relationship between cost and accuracy in monitoring, verification, and accounting applications using double-difference tomography. While all scenarios resulted in little error, no such relationship could be found. The lack of a relationship between cost and error is most likely due to error inherent to the travel time calculation algorithm used.