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This article presents a methodology for risk assessment and management in the development of hard-to-recover hydrocarbon reserves. The proposed methodology integrates Monte Carlo simulation and fuzzy logic methods, which allows for the consideration of both quantitative stochastic risks (e.g., fluctuations in oil prices, variability in costs, and production volumes) and qualitative uncertainties (e.g., environmental, social, and technological risks) that are traditionally difficult to formalize. The approach facilitates the incorporation of uncertainties associated with complex field developments and aims to improve managerial decisions through comprehensive risk assessment. The article elaborates on the theoretical aspects of the proposed methodology, including risk identification stages, the formalization of qualitative data using fuzzy logic, and the application of the Monte Carlo method for integrating various risk categories. The results confirm the potential of this methodology as a tool to enhance the resilience and economic efficiency of projects involving the development of hard-to-recover hydrocarbon reserves.
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