Reservoir Uncertainty Quantification Methods Supporting Reliable Forecasting Across Varying Geological and Operational Scenarios

Reservoir uncertainty quantification (UQ) methods are essential for enhancing the reliability of forecasting in oil and gas reservoirs, particularly across varying geological and operational scenarios. As reservoir management and production strategies become increasingly complex, accurate forecasting is crucial for maximizing recovery, minimizing risks, and optimizing resource allocation. Traditional reservoir models often incorporate significant uncertainties due to the inherent heterogeneity of subsurface environments, limited data, and dynamic operational factors. To address these challenges, advanced UQ methods have been developed to quantify and reduce uncertainties in reservoir behavior, providing more reliable forecasts. The application of UQ techniques, including Monte Carlo simulations, Bayesian inference, and machine learning algorithms, enables the integration of multiple sources of uncertainty, from geological heterogeneity and reservoir parameters to operational constraints. By incorporating these uncertainties into reservoir models, UQ methods offer a probabilistic framework that helps decision-makers evaluate a range of potential outcomes, rather than relying on a single deterministic prediction. This probabilistic approach supports more robust risk assessments, facilitating the identification of high-impact scenarios and enabling operators to develop contingency plans. Furthermore, UQ methods enable better integration of real-time data and adaptive reservoir management. As production data and monitoring results become available, UQ models can be updated, refining forecasts and enhancing operational efficiency. This dynamic approach allows for continuous model calibration and real-time decision-making, improving the overall management of reservoirs throughout their lifecycle. In conclusion, the adoption of reservoir uncertainty quantification methods significantly improves the accuracy and reliability of reservoir forecasting. By providing a comprehensive understanding of potential risks and production variability across geological and operational conditions, UQ techniques support informed decision-making, optimized recovery, and more sustainable reservoir management practices.