Multi-criteria spatial screening and uncertainty analysis applied to direct-use geothermal projects

ABSTRACT

The focus of this work is general methods for prioritization or screening of project sites based on the favorability of multiple spatial criteria. We present a threshold-based transformation of each underlying spatial favorability factor into a continuous scale with a common favorability interpretation across all criteria. We compare several methods of computing site favorability and propagating uncertainty from the data to the favorability metrics. Including uncertainty allows decision makers to determine if seeming differences among sites are significant. We address uncertainty using Taylor series approximations and analytical distributions, which are compared to computationally intensive Monte Carlo simulations. Our methods are applied to siting direct-use geothermal energy projects in the Appalachian Basin, where our knowledge about any particular site is limited, yet sufficient data exist to estimate favorability. We consider four factors that contribute to site favorability: the thermal resource described by the depth to 80°C rock, natural reservoir productivity described by rock permeability and thickness, potential for induced seismicity, and the estimated cost of surface infrastructure for heat distribution. Those factors are combined in three ways. We develop favorability uncertainty propagation and sensitivity analysis methods. All methods are general and can be applied to other multi-criteria spatial screening problems.

KEYWORDS:

• Site suitability analysis
• multi-criteria decision analysis
• uncertainty analysis
• geothermal
• sensitivity analysis

Acknowledgments

We thank the members of the Geothermal Play Fairway-Appalachian Basin team for their help during this project, including Brian Anderson, Erin Camp, Cathy Chickering Pace, Zachary Frone, Xiaoning He, Matthew Hornbach, Jefferson Tester, Kelydra Welcker. We also thank Koenraad Beckers for his help and training on the use of GEOPHIRES and Timothy Reber for guidance on incorporating US Census data into the utilization analysis.

Disclosure statement

The authors do not have any financial interest or benefits or any conflicts of interest to disclose related to this article.

Data and Codes Availability Statement

The data and codes that support the findings of this study are available with a DOI at https://doi.10.6084/m9.figshare.10250303.v1.

Additional information

Funding

This work was supported by the U.S. Department of Energy under grant [DE-EE0006726] and the National Science Foundation Integrative Graduate Education and Research Traineeship under grant [0966045]. The information, data, or work presented herein was funded in part by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of the authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

Notes on contributors

Calvin A. Whealton

Calvin A. Whealton completed his graduate studies at Cornell University, where as a member of the Energy Institute he was involved in geothermal research, specifically statistical characterization of geothermal resources. Currently he is pursing probabilistic flood hazard assessment for the Aare River in Switzerland. Other interests include uncertainty analysis and flood frequency analysis using hydrological simulations.

Jery R. Stedinger

Jery R. Stedinger is the Dwight C. Baum Professor of Engineering at Cornell University. His research has addressed statistical issues in hydrology and operation of water resources of systems. Focus areas include flood frequency analysis, regionalization of geophysical information, optimization of the operation of reservoir and hydropower systems, and statistical characterization of geothermal resources. He is a member of the National Academy of Engineering, a Fellow of the American Geophysical Union, and a Distinguished Member of the American Society of Civil Engineers.

Jared D. Smith

Jared D. Smith completed his graduate studies at Cornell University, where his research focused on exploratory spatial data analysis and uncertainty propagation for geothermal resource assessment and reservoir models to inform decisions about community-scale deep direct use of geothermal energy. He is currently a Postdoctoral Research Associate at the University of Virginia pursuing the use of a Bayesian framework for multi-objective optimization of green infrastructure portfolios that are robust to parametric model uncertainties.

Teresa E. Jordan

Teresa E. Jordan is the J. Preston Levis Professor of Engineering within Cornell Unversity’s Department of Earth and Atmospheric Sciences. Her diverse geological research spans tectonic controls on sedimentary basins, to the climate and hydrological history of Chile’s Atacama Desert, to finding more environmentally benign ways to meet society’s demands for energy using subsurface resources. She is a Fellow of the American Geophysical Union and the Geological Society of North America as well as of Cornell’s Atkinson Center for a Sustainable Future.

Franklin G. Horowitz

Franklin G. Horowitz is a mathematical geophysicist who is interested in the study of subsurface structures through gravity and magnetic potential fields. Among his other diverse research interests are inverse problems, optimization, other applied mathematics topics in geophysics and geothermal energy.

Maria C. Richards

Maria C. Richards is Southern Methodist University’s (SMU) Geothermal Lab Coordinator. Her research includes many aspects of geothermal resources and development, e.g. modeling of heat flow for temperature-depth maps on national to regional scale, field exploration in the Northern Marianas Islands, and the synthesis of Dixie Valley, NV. Current focus includes the conversion of oil and gas wells to produce geothermal energy, using well temperature logs as a climate indicator, the SMU node of the National Geothermal Data System, and as a past president of the Geothermal Resources Council.