Many Middle Eastern fractured carbonate reservoirs due to their strong sub-surface heterogeneity are characterized by significant and wide range of uncertainties. During brown-field redevelopment of such reservoirs, producing reliable production forecasts, which incorporate the full range of sub-surface uncertainty in a systematic and geologically-realistic manner, is a major challenge and a cumbersome task.

This paper presents a case study of one of the largest and oldest oil fields in Oman. Despite over 35 years of production through various drive mechanisms, there remains an opportunity to realize significant additional value in the field. The scale and complexity of the uncertainties associated with such an opportunity necessitates the use of structured approach to uncertainty handling. Experimental design and response surface modelling methods provide a framework for evaluating sensitivities and estimating impact of uncertainties on field performance. These methods require the a priori definition of the uncertainty range of key (or root) parameters and the construction of static reservoir models representing the full range of possible realizations. A selection of 3D simulation models, as defined by the experimental design approach, were then run to construct response surface models, which are then used to assess the impact of these uncertainties on field behaviour. The historical performance of the field is critical data used to constrain the range of some uncertainties. The results of this study are used to guide future development of the field.

The methodology described in this paper highlights the value of a structured multiple realizations approach, using experimental design and response surface modelling, for uncertainty estimation and management.


Uncertainties quantification in reservoir performance is an important part of proper economic evaluation. Over the past few years, the focus has been on new approaches and methodologies to make sound technical decisions on field development that account for uncertainties systematically. Many frameworks to integrate uncertainties into decision analysis use various tools such as Monte Carlo simulation, full physics simulation, scenario analysis, experimental design and response surface modeling. This paper describes the application of experimental design and response surface method in a systematic assessment of subsurface uncertainties for a mature field.

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