Abstract
Abstract Oil and gas development is fraught with technical uncertainty. As hard as we try, subsurface anomalies continue to surprise the most gifted petroleum engineers, and as a result, we seek technology that can help manage reservoir uncertainty. A classic success story is 3D seismic technology, which has proven to enhance our reservoir knowledge and reduce capital investment uncertainty. Intelligent Well Technology is much the same, in that it reduces the negative effects of reservoir uncertainty on expected future production and cash flow. Intelligent Well technology can provide an operator continuous/permanent down-hole monitoring coupled with the ability to reconfigure the well completion upon demand (through remotely operated flow control) without additional investment in response to reservoir knowledge gained over time. This ability creates value through reduced well intervention costs, reduced operating costs (i.e. through reduced surface facility requirements), reduced capital expenditures through innovative Intelligent Well Field Development Programs, increased production through commingling and increased recovery through enhanced reservoir surveillance and management. Moreover, the combined capabilities of real-time monitoring and flow control allow an operator the flexibility to actively respond to unforeseen reservoir driven events (i.e. early gas/water breakthrough or coning), effectively reducing future cash flow uncertainty. Traditional discounted cash flow (DCF) models do not adequately value the benefits of operational flexibility, and thus often underestimate the value of intelligent well technology (i.e. the benefits of real-time monitoring and control).1 Real Option analysis has been shown to effectively quantify this value in cases regarding portfolio analysis and corporate capital management.2 In this paper, we describe a method to apply Real Options theory to quantify the value of Intelligent Well applications, including the value of reducing project volatility and risk. We derive the mathematics to quantify Intelligent Well value for four specific case scenarios and outline the methodology to manage more complex cases. Finally, we describe how the mathematical model can be incorporated into a larger workflow process to assess entire asset portfolios for potential Intelligent Well applications.
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