Investigating geothermal potential with limited direct measurements

Understanding the whole system from the mantle to the surface is required to produce accurate subsurface models for geothermal resource assessment, resource exploration, hazard assessment and the understanding of tectonic processes. Variations in lithology and the associated thermal parameters will influence the subsurface thermal structure, which is one of the key parameters for geothermal exploration. This information can be difficult to obtain in areas with limited deep boreholes that directly sample subsurface lithology and physical properties (e.g.  temperature). Furthermore, subsurface temperature signals are intertwined with other variables, requiring approaches to separate the individual contributions within overlapping datasets. One way to achieve this is by utilising complementary datasets such as laterally continuous geophysical datasets (primarily passive seismic), thermal conductivity and heat production, and inverting directly for subsurface temperature with a joint geophysical-petrological inversion.

We use Ireland to test the methodology within the crust and lithospheric mantle, both for the full island and local scale. Ireland has 32 deep (>1 km) boreholes, which are unevenly distributed across the island and have variable quality temperature measurements. In contrast, Ireland has abundant indirect geophysical measurements from seismic, magnetotelluric and gravity data. The output from the inversion includes the lithospheric geotherm, lithospheric thickness and Moho depth, as well as crustal structure parameters such as seismic velocity, density and radiogenic heat production. The resulting temperature models agree well with the existing borehole temperature data and provide information for areas with fewer direct measurements. In addition, the inversion outputs offer insights into the lithological and compositional variations within the crust. We further develop the workflow by incrporating lithological boundaries from detailed 3D subsurface models.