This paper describes a new technique for effective placement of delineation wells on the basis of the change of the uncertainty in the key global-reserves variable. Uncertainty is summarized through the geostatistical framework. The authors develop a numerical and analytical methodology that is tested on synthetic and real petroleum case studies. The implementation is straightforward, and the results are promising. A methodology is developed to assist in delineation-well placement. Decisions for new-well locations are assisted with a quantitative measure of the expected reduction in global uncertainty in the volume of original oil in place (OOIP). The available realizations are analyzed and processed to quantify the impact of well placement. Variograms and other required statistics are inferred from the realizations. As a result, a gridded map of impact values is produced, from which locations with the highest impact are suggested for new-well locations. Numerical and analytical approaches for the impact-map calculation are proposed and compared. Pros and cons of each approach are summarized The numerical approach requires a large number of realizations for effective implementation of the impact map, which might not be practically achievable. On the other hand, the analytical approach does not require many realizations and produces stable results. In most cases, only variogram models and current well locations are needed for the analytical impact-map computation. Although computational time of this approach largely depends on the model size, some options are suggested to reduce the cost. The analytical impact calculation is developed for the OOLP model response, in which the petroleum reservoir is defined as a complex geological architecture with multiple structural surface constraints. Several case studies, including a real-petroleum-reservoir example, demonstrate the use of the impact map for the assessment of new delineation-well locations. The developed tool is of significant help for well placement.