A common and challenging decision problem in the oil & gas industry is to decide how to explore an oil field. Typically there is a cluster of prospects, giving rise to a highly dependent set of uncertainties, according to their proximity and the geology of the area. For example, if you drill a well at one site and strike oil, it’s more likely that a nearby prospect will also have oil. If you drill a few “dry holes”, you’ll probably give up on the field rather than throw good money at potentially poor prospects. This makes intuitive sense, but until recently it was tough to model in a decision tree. With DPL’s handy Pruned Sequential Tree feature – these types of sequential decision problems are easier to tackle than ever before.