Smart well technology has progressed significantly over the last few years. Earlier research1,2  has concentrated on the application of the technology to secondary recovery. More recent studies3,4,16  have aimed to advance the technical application to tertiary recovery concentrating on WAG processes. A utility theory approach to valuing information and risk attitude is used in this study.

Incorporating the economics into the decision making process and taking into account risk attitude complicates the decision making process. Earlier the goal was optimization of the global sweep efficiency under economic constraints through the control of the injection size of each slug, the controlled injection rate of each well, the injection location along the wellbore, and the production rates and locations. The control parameters stay the same but the goal is a risk based optimization of the project economics. Traditional real options based approach requires a normal distribution of outcomes which was not found to be true in this study. Therefore a utility theory approach is used to incorporate risk attitude.

The WAG process is sensitive to reservoir, fluid, and economic parameters which justify the need to quantify the uncertainty in production economics and associated risk. Gradients are determined from the proxy model. The gradients provide optimal control settings for the injection and production settings. This study demonstrates the feasibility of creating a response surface proxy model, using experimental design and analysis, to facilitate Monte Carlo simulation, uncertainty analysis and optimization of the expected value utility. The proxy model is orders of magnitude faster allowing a statistical analysis of the uncertainty, value of information, value of flexibility and associated risk. Results on this model show significant improvements over an uncontrolled WAG production and the ability to incorporate risk attitude into the optimization process.

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