Schlumberger

Technical Paper: SAGD Optimization Under Uncertainty

Society: Other
Paper Number: WHOC11-355
Presentation Date: 2011
Download: SAGD Optimization under Uncertainty (0.66 MB PDF)

 

Abstract

A proven thermal method for producing heavy oil is steam-assisted gravity drainage (SAGD), which employs two horizontal wells; an injector and a producer. This method requires a lot of energy to generate the necessary steam; and therefore, can be a costly choice in an environment where the allocation of resources, efficient or otherwise, can make the difference between an economically viable venture and a loss-making one. Sensitivity analysis on reservoir simulations is usually undertaken one parameter at a time to establish the most efficient allocation of these resources. Not only do such practices require costly computational time, they are also prone to overlooking both more effective and optimum strategies. While automated optimization processes have been shown to provide practical solutions to such complex interdependent multidimensional problems, those so far published are discrete in nature, i.e., they have not considered uncertainties that may be pervasive and potent in actual SAGD operations. A shale distribution, for example, can significantly alter steam chamber growth and shape, and thereby impact the efficiency of the SAGD process. This paper defines a practical means to establish the aforementioned optimum SAGD operation (either economically or against some other metric) when confronted with real and impactful uncertainty. The method is demonstrated for a configuration applied to typical heavy crude found in the Faja region of Venezuela. The nature of uncertainty takes the form of three different, but equiprobable, geological realizations corresponding to varying shale heterogeneities along the wells. Optimization under uncertainty provides different strategies, while taking into consideration the risk tolerance (aversion) of the decision maker in a manner that incorporates all relevant and significant uncertainties.

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