Abstract
Abstract Probabilistic and deterministic methods for reserves and resources evaluation are commonly used in isolation and often considered mutually exclusive. Subsurface uncertainties are critical factors impacting projects and reserves/resources especially in projects/areas where large sums of capital investment are required. Probabilistic methods allow a rigorous use of information on the ranges of uncertainty on key reservoir parameters like porosity, water saturation, permeability aquifer size for reserves estimation. A key output of probabilistic methods is the confidence levels associated with the reserves. Deterministic methods cannot provide confidence levels associated with reserves and resources assessments reason why its successful application is often relaying on the expert knowledge of the evaluator and the strict use of reserves or resources definitions. Technological advances in computing in the last decades have played a key role in advancing computationally intensive probabilistic methodologies including artificial intelligence. These advances have allowed integrated teams to perform studies using sophisticated workflows in feasible timeframes. In this paper a detailed analysis of the different probabilistic methods is presented with a review of the level of regulatory compliance with the SEC1 and other industry guidelines like SPE PRMS2 that each of the different methods have. A group of workflows using a combination of these methods is also analysed.