Search

The assessment of the probability of geological success (i.e. the chance that a well encounters mobile hydrocarbons) is an important task in the prospect evaluation workflow. After the initial assessment of a geological probability of success, POSg, we use the geophysical direct hydrocarbon indicators (DHI) as extra information in a second Bayesian risk modification step. The Bayesian risk modification (BRM) is a very flexible approach, allowing many data types to be considered. The BRM is extended in this paper to include multiple DHI attributes. If we want to use two seismic attributes (e.g. top reservoir reflection and flat spot amplitudes), then possible interdependences between the attributes must be carefully investigated before application. We suggest a simple approach to determine the degree of attribute dependence and we demonstrate how to compute the scenario conditional probabilities (likelihoods) of these attributes for all possible exploration outcomes. A case study from the Barents Sea shows the feasibility of the multi-attribute BRM to solve a complex risking situation for a prospect with a flat spot. The later drilling and well results confirmed the plausibility of the risking modification outcome.