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The purpose of this chapter is to provide a workflow for modeling uncertainty. It focuses upon a mature (brown) field redevelopment in a giant fractured carbonate field in Oman. We used experimental design to constrain the range and impact of individual parameters on production forecasts using historical field performance data. The approach allowed for an assessment of the interaction and impact of the uncertainty for a large number of subsurface parameters with a manageable number of model runs. A priori assumptions of the uncertainty range of each parameter were first modeled and then challenged during initial screening runs. Subsequently, historical data were used to constrain the uncertainty range of those parameters that were sensitive to past production performance. The uncertainty range of all other parameters was carried forward into the production forecast, and their impact on various development options was tested. The results of this work were input into a data gathering and pilot production plan to further delimit uncertainty ranges and to help select and optimize development options.

The predictive capacity of a reservoir model is strongly influenced by the uncertainty range associated with the individual subsurface parameters that are captured in it. A large uncertainty range results in a low predictive power, but if uncertainty ranges are too narrow, then realistic forecasts of future production may not be achieved. Integrated subsurface teams are routinely tasked with identifying and quantifying uncertainty and capturing the probabilistic ranges in production forecasts. Of the many methods of handling this challenge, experimental design provides a robust mechanism for assessing the impact of a combined range of subsurface parameters on future production. This chapter outlines a case study of how experimental design can be used to handle such uncertainty in production forecasts.

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