Energies (Nov 2023)

Development of an Improved Decision Support Tool for Geothermal Site Selection in Nigeria Based on Comprehensive Criteria

  • Uchechukwu Nwaiwu,
  • Matthew Leach,
  • Lirong Liu

DOI
https://doi.org/10.3390/en16227602
Journal volume & issue
Vol. 16, no. 22
p. 7602

Abstract

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Geothermal resource assessment is crucial for the rural electrification of Nigeria. A comprehensive set of criteria was used to appraise promising geothermal sites in Nigeria. The evaluation of the sites was performed using the multi-criteria decision analysis (MCDA) method and taking into account evidence of a wide range of criteria from a set of geological, geophysical, well log, environmental, remote sensing, and geochemical datasets to appraise promising geothermal sites and to add to the current debate on the needed criteria for geothermal development. To gather relevant data, various sources such as bottom-hole temperature (BHT) data from different boreholes and oil and gas wells, aeromagnetic maps, reduced-to-the-pole, magnetic, heat flow, seismic, and geothermal gradient data from aerogravity maps, Bouguer anomaly maps, earthquake epicenter maps, satellite images, and geological maps were obtained from the literature. A case study of the thirty-six states of Nigeria, including the federal capital territory, Abuja (FCT), was conducted to illustrate how these criteria would reveal the technical aspect of the geothermal energy situation. A model was developed to show that the application of a wide range of criteria to the six datasets identified and analyzed in this study reveals that the datasets complement each other and should not be used independently. It can be found from the overall suitability map that more than 20% of the study area is suitable for geothermal energy development. It can also be observed from the map that some of the promising sites in Nigeria may include but are not limited to Bauchi, FCT, Taraba, Ebonyi, Adamawa, Oyo, and Nasarawa states in Nigeria. The opportunities for the further application of the approach are discussed, including the use of the model to help policymakers decide where to invest in the future.

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