GNGTS 2022 - Atti del 40° Convegno Nazionale

392 GNGTS 2022 Sessione 3.1 3D THERMAL MODELING CONSTRAINED BY CURIE ISOTHERM Y. Kelemework, M. Fedi University of Naples Federico II, Department of Earth, Environment and Resources Sciences, Naples The knowledge of subsurface temperature distribution is very important to identifying potential geothermal regions and understanding a variety of geologic processes, though it is one of the most poorly known geophysical parameters. To obtain information about temperature distribution in the crust and mantle, the surface observations (e.g., surface heat flux and near- surface temperature) could be extrapolated to the crust or lithosphere base using the heat conduction model (e.g., Cermak and Bodri, 1986; Lin et al. , 2014). Near-surface heat flow and temperature measurements, along with geochemical models, are often used to characterize the shallow thermal gradient of the crust (e.g., Artemieva, 2011). However, measurements of temperature and heat flow from boreholes are neither uniformly distributed nor consistently deep, and thus they are not enough in inferring deep thermal distributions. Thus, deriving an accurate thermal model of the deep crust is more challenging and requires the knowledge of crustal thickness and related thermal and physical parameters. Moreover, in young and active regions the temperature distribution could be significantly affected by near-surface processes and may completely hinder the deep geothermal gradient and heat flow. Thus, considering the surface heat flow in such regions to be representative of the deep thermal state may lead to wrong geotherm and thermal models (e.g., Della Vedova, 2001). We also need to know the boundary conditions at the top, bottom, and vertical boundaries. Although the surface and vertical boundaries can easily be assumed, the bottom boundary is usually unknown. To partially alleviate the above-mentioned problems, geophysical and petrological models that do not require data from boreholes can be used to infer deep thermal structures and may help to derive deep thermal constraints and may complement near-surface data. These techniques include the Curie depth point, xenolith, and seismic data among others. The Curie depth point estimated from magnetic data has been commonly used to infer the deep thermal structure (e.g., Tanaka et al. , 1999; Bouligand et al. , 2009; Kelemework et al. , 2021). Curie temperature isotherm (580 o C) is the temperature at which magnetic bodies lose their magnetization and become paramagnetic due to increasing temperature with depth. The Curie depth point varies as a function of both local geothermal gradient and lithological composition, and this introduces some uncertainties. Notwithstanding, Curie depth point derived from magnetic data using spectral analysis remains the most common technique to infer deep thermal structure. Furthermore, detailed results of the deep thermal distribution can be obtained by using Curie depth points as constraints by assigning them to the lower thermal boundary condition of a thermal model. Mather and Fullea (2019), for example, constrained the geotherm beneath the British Isles from Bayesian inversion of Curie depth. In this study, we aimed at building a 3D thermal model constrained by Curie depth points. In addition, crustal structures modeled from seismic and potential field data are used to assign physical parameters (thermal conductivity, heat production). We present a case study from Southern Italy. We also attempt to compare the Curie depth-derived model with geothermal models derived from borehole temperature data wherever possible. 3D thermal models may help to better model more complex geological structures, especially for studying temperature distributions in the contact zones of distinct geologic and tectonic provinces, where significant lateral and vertical variations in the subsurface temperature distributions are expected. Our preliminary 3D thermal model constrained by Curie depth points is shown in Figure 1. The computed temperature distributions of the crust seem to vary in relation to the volcano- tectonic history and the physical properties of the lithosphere. It is evident from the 3D thermal model that the southeastern Tyrrhenian Sea, including the Aeolian volcanic arcs, is characterized by high thermal gradients with a temperature of 580 o C at about 8 - 10 km. This