SummaryImprovements in seismic data quality can significantly enhance hydrocarbon production, motivating the investigation of methods to acquire more accurate and reliable data. In many cases there will be considerable uncertainty in reservoir properties and in the level of error in the data. We present an approach for determining the potential value of competing seismic survey methods to improve knowledge of reservoir properties to inform decisions related to reservoir management. Monte Carlo simulations using an earth model based on a Gulf of Mexico site, and seismic error models, provide statistical estimates of the ability of seismic amplitudes to infer porosity and reservoir thickness. Bayesian decision analysis methods then facilitate the optimization of an infill drilling program and allow the quantification of the economic value of the different seismic data sets.