Geothermal resource and reserve assessment methodology: Overview, analysis and future directions

Anthony E. Ciriaco, Sadiq J. Zarrouk and Golbon Zakeri

Renewable and Sustainable Energy Reviews, 2020, vol. 119, issue C

Abstract: Resource assessment and reserve estimation play a crucial role in the decision-making, financing, development, and operation of geothermal projects. The present study critically examines all existing resource assessment methodology and practices when quantifying power potential of geothermal fields. The potential generating capacity of geothermal projects at the early stage of development, where there is limited information about the resource, is typically estimated using the volumetric method. Sustainable operation and management of existing geothermal fields, on the other hand, rely on developing and updating a calibrated numerical reservoir model. To-date, the volumetric method and reservoir simulation remain the most appropriate tools to use for geothermal resource assessment. The former method is the recommended approach for projects that are still at the early stage of development, while the latter technique is for predicting sustainable production capacity after exploration drilling. However, building a numerical model for a project at the early due diligence stage is also useful and can complement the volumetric method. Most studies of resource assessment methodologies highlight the difficulty of obtaining accurate, predictable generating output potential. Quantification of uncertainty in predictable output is carried out using the Monte Carlo method. This review demonstrates that the probabilistic assessment using Experimental Design (ED) and Response Surface Methodology (RSM) is a more promising technique that can be easier and quicker to implement.

Keywords: Resource assessment; Resource assessment methodology; Power potential; Volumetric method; Numerical reservoir simulation; Probabilistic resource assessment (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (12)

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DOI: 10.1016/j.rser.2019.109515

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