Economics studies of areas with indications of hydrocarbons are submerged in uncertainties of assorted natures (geological, of engineering and economical). At the start of the study, aspects concerning the geology, the fluids, the rocks and the reservoir are only known through indirect methods that yield imprecise information. The reduction of these uncertainties is limited by high costs of drilling wells that allow direct tests. Consequently, decisions on exploration investments have to be made under risk. This motivates the development of methods for probabilistic economic evaluation of properties. This dissertation addresses the probabilistic economic evaluation of petroleum resources, prior wildcat well drilling. Assessing the economic value of a property depends on estimates of incomes and costs time profiles associated to its development and production (D and P). Obtaining such elements requires a D and P project for the property that, due to the limited data available, is less detailed than a multi- cellular simulation project. In this thesis, a probabilistic evaluation methodology based on Monte Carlo simulation is presented along with a prototype implementation. Performing the numerous replications necessary to obtain a probabilistic evaluation becomes feasible thanks to a procedure capable of automatically generating the D and P project. That procedure was developed by Petrobras based on heuristic rules supplied by an expert. In addition to a justification for the proposed approach, the description of the method and its implementation, comments are made on probability density functions used for encoding uncertainties, and on the results of the initial tests with the prototype system.