Geothermal energy stands as a promising renewable resource with vast untapped potential. This paper presents a comprehensive review of geothermal resource assessment by integrating petrophysical insights and machine learning (ML) for enhanced reservoir characterization for predictive modelling for economic feasibility assessments. The examination of global geothermal hotspots, considering thermal attributes alongside porosity and permeability characteristics, contributes to understanding the efficiency and feasibility of geothermal reservoirs for future sustainable energy initiatives. The exploration of geothermal reservoirs plays a pivotal role in harnessing energy. Through analysis of various geological surveys, reservoir modelling, and advanced exploration technologies aimed to provide insights into the estimation and characterization of geothermal reservoirs. this paper explains the prospects and challenges associated with harnessing this clean, reliable, and renewable energy source for future energy sustainability in Africa. This Paper shows illustration of reservoir characterization and modelling of two wells in west Africa to investigates Potential for the sustainable exploitation of geothermal energy, encompassing enhanced geothermal systems (EGS), coupled with economic feasibility assessments.
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Akagbosu et al. (2024) studied this question.
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