A scoping review of numerical modelling studies of geothermal reservoirs: Trends and opportunities post-COP25

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dc.contributor.affiliationLlanos E.M., ETICA Consulting & Research, Melbourne, Australia
dc.contributor.affiliationBlessent D., Faculty of Engineering, Universidad de Medellín, Medellín, Colombia
dc.contributor.authorLlanos E.M.
dc.contributor.authorBlessent D.
dc.date.accessioned2025-09-08T14:23:31Z
dc.date.available2025-09-08T14:23:31Z
dc.date.issued2025
dc.descriptionAt 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. © 2025, Diponegoro university Indonesia - Center of Biomass and Renewable Energy (CBIORE). All rights reserved.
dc.identifier.doi10.61435/ijred.2025.61071
dc.identifier.instnameinstname:Universidad de Medellínspa
dc.identifier.issn22524940
dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellínspa
dc.identifier.repourlrepourl:https://repository.udem.edu.co/
dc.identifier.urihttps://hdl.handle.net/11407/9065
dc.language.isoeng
dc.publisher.facultyFacultad de Ingenieríasspa
dc.publisher.programIngeniería Ambientalspa
dc.relation.citationendpage693
dc.relation.citationissue4
dc.relation.citationstartpage668
dc.relation.citationvolume14
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-105010387651&doi=10.61435%2fijred.2025.61071&partnerID=40&md5=8954d7076c55d401a0fe30e35f424dd0
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dc.rights.accesoRestricted access
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceInternational Journal of Renewable Energy Development
dc.sourceInternat. J. Rene. Ener. Devel.
dc.sourceScopus
dc.subjectCOMSOL
dc.subjectenergy
dc.subjectGeothermal
dc.subjectMachine Learning
dc.subjectmodelling
dc.subjectTOUGH2
dc.subjectEconomics
dc.subjectGeothermal fields
dc.subjectGeothermal wells
dc.subjectInvestments
dc.subjectMachine learning
dc.subjectCOMSOL
dc.subjectCross industry
dc.subjectEnergy
dc.subjectEnhanced geothermal systems
dc.subjectGeothermal
dc.subjectGeothermal industry
dc.subjectMachine-learning
dc.subjectModeling
dc.subjectScoping review
dc.subjectTOUGH2
dc.subjectLearning systems
dc.titleA scoping review of numerical modelling studies of geothermal reservoirs: Trends and opportunities post-COP25
dc.typeReview
dc.type.localRevisiónspa
dc.type.versioninfo:eu-repo/semantics/publishedVersion

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