At the 28th Conference of Parties (COP28) a commitment to triple renewable energy capacity by 2030 was made. Currently at 16 GW, geothermal accounts for 0.5% of world-wide installed renewable electricity capacity. In this scoping review, Elsevier’s database was used to determine the role reservoir simulation has played and could continue to play in assisting the geothermal industry in achieving COP28's goal. The review includes journal papers published in English from 2020 to 2023. Particular attention was paid to the applications of TOUGH2 and COMSOL, the benefits of Machine Learning (ML) and recent projects that could assist in promoting the geothermal industry. The topics' categories comprised: Enhanced Geothermal Systems (EGS), hydrothermal, laboratory, and technology synergies. Outcomes of a bibliometric analysis elucidate these trends: ML is vital to ensuring the optimisation of geothermal resources; EGS and cross-industry projects are showing growing global interest. The likelihood of meeting the COP28 target for geothermal would be enhanced with increased participation from the South American and African countries. However, the industry’s growth in these continents is restricted by high initial investment costs, technical complexities, unclear regulatory frameworks, social acceptance, and difficulties with electrical grid integration. Suggestions for overcoming these barriers to development are proposed. A brief country case study is also presented. It focuses on the economic, environmental and technical context to understand the unique challenges and opportunities for geothermal. Finally, five areas for research and development opportunities were identified: Thermo-Hydro-Mechanical-Chemical processes, reinjection and induced seismicity, reservoir characterization, cross-industry collaborations, and laboratory studies.
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