Agradecimentos: The authors would like to thank the following entities for supporting this research: PETROBRAS, and the Research Network SIGER; STATOIL; the National Agency of Petroleum, Natural Gas and Biofuels (ANP); the Center for Petroleum Studies (CEPETRO), and UNISIM Research Group; the...

Agradecimentos: The authors would like to thank the following entities for supporting this research: PETROBRAS, and the Research Network SIGER; STATOIL; the National Agency of Petroleum, Natural Gas and Biofuels (ANP); the Center for Petroleum Studies (CEPETRO), and UNISIM Research Group; the Department of Energy of the School of Mechanical Engineering of the University of Campinas (UNICAMP); and the Coordination for the Improvement of Higher Education Personnel (CAPES). We also thank the Computer Modelling Group Ltd. (CMG) and Mathworks for software licenses and technical support

Many factors affect production strategy selection in petroleum field development. Decision makers many times rely on informal procedures and professional experience to base decisions because tools to quantify their expectations are sometimes unclear or incoherent in the petroleum literature. In this...

Many factors affect production strategy selection in petroleum field development. Decision makers many times rely on informal procedures and professional experience to base decisions because tools to quantify their expectations are sometimes unclear or incoherent in the petroleum literature. In this work, we improve the decision-making process in field development by providing a set of quantitative criteria that assess production strategies under uncertainty. These criteria incorporate the decision maker's attitude and objectives in the decision. We use lower and upper semi-deviations to effectively quantify downside risk (uncertainty in losses) and upside potential (uncertainty in gains) of production strategies. These metrics assess individual subsets of project variability against reference benchmarks, in line with the decision maker's definition of loss and gain. The general formulation we propose is applicable to production and economic indicators, in a single- or multi-objective framework, and explicitly accounts for the decision maker's attitude: neutrality to downsides and upsides, minimizing exposure to downsides, and exploiting potential upsides. We created this framework using the well-known expected value concept with lower and upper semi-deviation measures. Theoretical examples illustrate problems faced by decision makers when using traditional risk measures, which are overcome by lower and upper semi-deviations. A synthetic benchmark reservoir in the development phase demonstrates the application of the proposed frameworks for production strategy selection

COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPES

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