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

journal contribution
posted on 2020-05-01, 17:45 authored by Calvin WhealtonCalvin Whealton, Jery Stedinger, Jared Smith, Teresa Jordan, Franklin Horowitz, Maria Richards


Contents of this repository are code, data, and figures used in the analysis for the paper titled “Multi-criteria spatial screening and uncertainty analysis applied to direct-use geothermal projects”, International Journal of Geographical Information Science. More details are in the "readme" file.

Calvin A. Whealton, Jery R. Stedinger, Jared D. Smith, Teresa E. Jordan, Franklin G. Horowitz & Maria C. Richards (2020) Multi-criteria spatial screening and uncertainty analysis applied to direct-use geothermal projects, International Journal of Geographical Information Science, 34:10, 2053-2076, DOI: 10.1080/13658816.2020.1765247

Article 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 exists to estimate favorability. We consider four factors that contribute to site favorability: the thermal resource described by the depth to 80 oC 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.


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