Article: Lukawski, MZ; Silverman, RL; Tester, JW; “Uncertainty Analysis of Geothermal Well Drilling and Completion Costs”, Geothermics, 64: 382-391
Abstract: The goal of this study was to characterize the uncertainty associated with the cost of drilling and completion of geothermal wells. Previous research and publications have produced correlations for the average cost of geothermal wells as a function of well depth. This project develops this concept further by using a probabilistic approach to evaluate the distribution of geothermal well costs for a range of well depths. The well cost uncertainty was characterized by identifying the main cost components of geothermal wells and quantifying the probability distributions of the key variables controlling these costs. These probability distributions were determined based on the detailed cost records of U.S. geothermal wells drilled or designed from 2009 to 2013 as well as cost data from drilling equipment manufacturers and vendors.
Probability distributions of the key variables were examined to find statistically significant correlations between them. Lastly, the previously determined probability distributions of individual cost components and the correlations between them were input into WellCost Lite, a predictive geothermal drilling cost model, using the Monte Carlo method. This approach allowed us to generate the overall well cost probability distributions for 8000-15,000 ft. (2400-4600 m) geothermal wells. We have shown that the median geothermal well cost increases exponentially with depth. Deep wells typically have higher cost uncertainty and more positively-skewed cost probability distributions.
The correlations presented in this paper can be used to determine the economic feasibility of geothermal energy systems, assess the project risk, and facilitate investment decisions. (C) 2016 Elsevier Ltd. All rights reserved.
Funding Acknowledgement: Cornell Energy Institute, the Atkinson Center for a Sustainable Future; NSF Earth-Energy IGERT program; U.S. Department of Energy [DE-EE0002745, DE-EE0002852]
Funding Text: The authors are very grateful to the Cornell Energy Institute, the Atkinson Center for a Sustainable Future, as well as the NSF Earth-Energy IGERT program for partial financial support of this work. We also appreciate the support from the U.S. Department of Energy provided in the form of research grants #DE-EE0002745 and #DE-EE0002852. We would also like to express our gratitude to Louis Capuano Jr. and Louis Capuano III, the late Bill Livesay, Bill Eustes, Paul Graham, Karl Urbank, Joe Wangsness, Abraham Stroock, Lawrence Cathles, Chad Augustine, Brian Anderson, and Michal Moore, who provided advice on this work.