Geophysical characterization of geothermal fields: Inversion of temperature data and ground motions

Abstract

Geothermal energy, the heat that can be extracted from the Earth’s subsurface, could play an important role in the energy transition towards renewable energy sources. However, the global increase in geothermal applications is relatively slow compared to other renewables, related to the economic uncertainty of geothermal operations. Therefore, a detailed understanding of geothermal reservoirs is necessary, not only to map their potential but also to reduce the risks of geothermal projects by quantifying subsurface uncertainties. In this thesis I aim to provide novel approaches for improving geothermal reservoir characterization with the use of temperature measurements and ground deformation observations. To achieve this, country-scale thermal models (Chapter 2 and Chapter 3) and site-specific source models for surface movements (Chapters 4 – 6) were constructed. Models were constrained by independent geological and geophysical data, assessing the thermal field, deformation processes, and associated properties of the geothermal reservoirs. Access to datasets for the case studies from Hungary (Chapter 2 and Chapter 4) and the Netherlands (Chapter 3) were provided through collaborations with Hungarian partners and TNO. Various geological and geophysical datasets together with conceptual models were available within the framework of the EU-funded GEMex project, which facilitated the interpretation of ground deformation at the Mexican Los Humeros geothermal field (Chapter 5 and Chapter 6). This thesis demonstrates that the identification of temperature and ground motion anomalies and the understanding of physical processes and properties behind them can significantly contribute to map potential areas and to plan exploitation strategies for geothermal utilization. Additionally, continuous monitoring of operating geothermal fields using InSAR measurements and inverse modeling has been proven to be a valuable addition to conventional geophysical methods for geothermal field management, and is expected to become a widely used technology in the future. Effective exploration and safe and sustainable production of subsurface resources require knowledge of the subsurface processes, the driving parameters and their uncertainties. For the understanding of the complex processes occurring at geothermal sites, the integration of multi-disciplinary models and datasets is paramount. By facilitating this integration and quantification, inversion methods demonstrate their effectiveness in the case studies of this thesis.