This paper describes a new technique for effective placement of delineationwells on the basis of the change of the uncertainty in the key global-reservesvariable. Uncertainty is summarized through the geostatistical framework. Theauthors develop a numerical and analytical methodology that is tested onsynthetic and real petroleum case studies. The implementation isstraightforward, and the results are promising. A methodology is developed toassist in delineation-well placement. Decisions for new-well locations areassisted with a quantitative measure of the expected reduction in globaluncertainty in the volume of original oil in place (OOIP). The availablerealizations are analyzed and processed to quantify the impact of wellplacement. Variograms and other required statistics are inferred from therealizations. As a result, a gridded map of impact values is produced, fromwhich locations with the highest impact are suggested for new-well locations.Numerical and analytical approaches for the impact-map calculation are proposedand compared. Pros and cons of each approach are summarized. The numericalapproach requires a large number of realizations for effective implementationof the impact map, which might not be practically achievable. On the otherhand, the analytical approach does not require many realizations and producesstable results. In most cases, only variogram models and current well locationsare needed for the analytical impact-map computation. Although computationaltime of this approach largely depends on the model size, some options aresuggested to reduce the cost. The analytical impact calculation is developedfor the OOIP model response, in which the petroleum reservoir is defined as acomplex geological architecture with multiple structural surface constraints.Several case studies, including a real-petroleum-reservoir example, demonstratethe use of the impact map for the assessment of new delineation-well locations.The developed tool is of significant help for well placement.