Decision making about field development plans has to consider the inherent uncertainties of sub-surface hydrocarbon reservoirs; therefore, the decisions would be stable under different geological scenarios. As described in Sect. 1.5.1, the aim of this kind of uncertainty management is to propagate the uncertainty from inputs to the outputs. Therefore, instead of a single deterministic output, the output will be probabilistic from which some statistical measures, such as the expected value, standard deviation, etc. can be calculated to account for the uncertainty. Therefore, the final decision regarding the field development plan can be taken according to the statistical measures. This kind of uncertainty management is also known as the robust field development optimization as explained in the following. In addition, different risk measures, different approaches to selecting an ensemble of representative geological realizations to be used in robust optimization, decreasing the computational cost of the optimization under geological uncertainty by constrained optimization, and challenges related to these activities are described in this chapter.