Developing an exploration decision support system (EDSS): A strategy for combining information and analytics

Petroleum exploration companies enter the twenty first century facing an increasingly competitive and risky environment. Under those circumstances, there is a growing need for better systematic decision-making that explicitly embodies the firm's desired goals and resource constraints. Computer-aided decision making, or decision support systems (DSS), provide an aid for those exploration management problems that are large, complex, unstructured, and involve management mudgment. Almost every present day DSS falls into one of two general classes. Vehicle DSSs such as linear/nonlinear programming models and other optimization routines, propose and impose specific methodologies to the decision-maker. On the other hand, toolbox DSSs, such as simulation programs, statistical functions, and graphical packages, are generally flexible in enabling their users to employ a variety of approaches and tools for their decision tasks but provide little guidance on both problem representation and investigation. This paper describes the development of a hybrid DSS model that combines the advantages of both the vehicle and toolbox systems components to provide a comprehensive approach to exploration planning from geological development through the capital allocation process. The Exploration Decision Support System (EDSS) preserves the flexibility of the toolbox system while enriching the problem-solving strategies available to the firm. The central objectives for developing an EDSS framework are: (1) better decisions about resource allocations; (2) more systematic understanding of the factors affecting exploration decisions; (3) improved communication about E&P performance objectives and constraints at all levels of decision-making; and (4) an explicit vehicle for continuous improvement of the petroleum exploration firm's decision-making process. The EDSS model can guide geological and exploration managers toward a more formal evaluation of projects, provide insight into the impact of competing choice alternatives, and significantly improve the quality of exploration decisions.