Enhancing assessment accuracy of the Halten Terrace Jurassic play using constrained Bayesian discovery process modeling

A Bayesian version of the discovery process model was applied to the pre-rift Lower and Middle Jurassic play of the Halten Terrace, Mid-Norway. The Bayesian approach estimates the lognormal parameters, the discoverability parameter, and the distribution of sizes of the undiscovered fields as well as the play potential, conditioned on a discovery sequence. A Bayesian discovery process modeling averaging over all possible prior choices weighted by their likelihood has been implemented by Markov chain Monte Carlo sampling. This process may be constrained by judgemental evidence expressed as permissible regions for the parent population parameters and the sizes of the expected largest and smallest remaining discoveries. Geological conditioning through the study of the petroleum system and the particularities of individual exploration plays integrated with the discovery sequence within a Bayesian framework may be orders of magnitude more accurate than methods using non-constrained extrapolation of creaming curves.