Geothermal heat flow (GHF) is a critical parameter for understanding the thermal structure and dynamics of the lithosphere, offering key insights into geophysical processes and geothermal energy potential. We investigated the spatial variability of GHF across Germany by applying a Bayesian Markov Chain Monte Carlo method to estimate key thermal parameters, including crustal and mantle thermal conductivities, crustal heat production, and mantle heat flow. To address the limitations posed by the sparse and uneven distribution of direct borehole measurements, comprising only 595 GHF records, we incorporated a wide range of geophysical and geological datasets, such as gravity, magnetics, seismic velocity, topography, and proximity to faults and volcanic regions. The derived probabilistic multi-geoobservable model enhances our understanding of the geothermal regime in Germany, contributing to a more precise assessment of its geothermal resources and the thermal state of its lithosphere.
Teilnahme vor Ort im großen Sitzungssaal des Geozentrum Hannover oder online unter folgendem Webex-Link: https://liag.webex.com/liag/j.php?MTID=m6962bb91db07fcef8562a555139afff1
Der Vortrag wird auf Englisch gehalten.