Petroleum exploration portfolios generated with different optimization approaches: Lessons for decision-makers

Abstract

Petroleum explorers recognize the value of portfolio management, but many have not seen it effectively applied in the industry or do not understand how subsurface assessments by geoscientists link to portfolio analysis and decision-making by managers. Here, we constructed a fictitious but realistic inventory of 50 prospects distributed across plays of various maturity and then generated portfolios with rank and cut, efficient frontier and portfolio filtering approaches. Different analysis and optimization techniques have varying degrees of use and success in aligning portfolio selections with specific strategic goals and available drilling budget. Portfolios ranked and cut by mean risked volumes, economic probability of success (PoS) and expected monetary value can deliver good exploration results. However, they are sub-optimal when compared with similar efficient frontier portfolios optimized for expected total recoverable resource volume and its standard deviation. Portfolios ranked and cut by geological PoS values can deliver the greatest geological success rate among all portfolios, but not much resources and monetary value when the low-risk prospects have relatively small success-case volumes. Portfolio filtering helps find suitable alternative portfolios. Better portfolios include prospects from the emerging play setting characterized by greatest geological and economic PoS values and success-case volumes, but exclude high-risk prospects from frontier play settings. The formal portfolio optimization approaches are blind to the fact that companies have to drill high-risk frontier prospects to de-risk plays and provide access to prospects in emerging plays. Portfolio analysis and optimization techniques must be coupled with good understanding of exploration business and long-term strategy to deliver excellent sustainable exploration results.