There’s a lot to like about the Uinta Basin’s waxy crude, but ramping up its production and use in refinery feedstock slates will require multimillion-dollar investments in rail terminals, special rail cars, heated storage, refinery equipment and other midstream and downstream infrastructure. A natural concern for E&Ps, midstreamers, and refiners is whether the basin has sufficient long-term staying power to justify the upfront costs and commitments. As we discuss in today’s RBN blog, a machine-learning-based analysis can provide many of the answers by assessing the basin’s long-term outlook under various scenarios.