ABSTRACT: Risk assessment and management have always been at the core of hydrocarbon producing endeavors. Yet to date nearly all risk assessment has been qualitative and so-called quantitative risk assessment remains a new and potential fertile area of application. Much current practice in estimating hydrocarbon recovery is based on numerical simulation of flow through reservoirs. It has become axiomatic that incorporating more data into such models leads to greater confidence in its predictions. This statement has not been proven to be true, and, indeed, cannot be true in all cases. Furthermore, incorporating more data into a simulation model is not easy because 'data' comes in all forms, covers a disparity of volumes of investigations, and many times becomes available only while the resource is being produced. This presentation deals with that portion of risk assessment known as uncertainty estimation. It reviews common observations in the practice of history matching, reviews the statistical concepts of bias and precision, and finally illustrates the insights that three-dimensional seismic information can bring to a waterflood prediction.