Reservoir simulation

Bayesian Framework Helps History Matching of Permian EOR Field With Data Uncertainty

The authors of this paper present an application of a Bayesian framework for uncertainty assessment and efficient history matching of a Permian CO2 enhanced oil recovery field for reliable production forecast.

A cut-away 3D view of the simulation model showing different relative permeability regions.
A cut-away 3D view of the simulation model showing different relative permeability regions.

Reservoir production forecasts are inherently uncertain because of the lack of quality data available to build predictive reservoir models. Traditionally, a best estimate for relative permeability data is assumed during the history-matching process despite significant uncertainty. Performing sensitivities around the best-estimate relative permeability case will cover only part of the uncertainty space. In the complete paper, the authors present an application of a Bayesian framework for uncertainty assessment and efficient history matching of a Permian carbon-dioxide (CO2) enhanced oil recovery field for reliable production forecasting.

Field Details

Regional and Structural Geology.

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