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Dataset to Geothermal Resources and ATES Potential of Mesozoic Reservoirs in the North German Basin

This dataset provides point-shapefiles and geotiffs, related to the figures presented in (Frick et al., 2022a, 2022b). It covers most of northern Germany, with the boundaries defined by the extent of the North German Basin, which is part of the Central European Basin System. The files contain information on the depth (m.b.s. = meter below surface), thickness, temperature, heat in place and heat storage potential of selected geological units and the formations therein. These data are an addendum to the data presented in (Frick et al., 2022a, 2022b), resolving 5 geological units and 9 formations. The data are presented as regularly spaced point-shapefiles, with a spacing of 1000 m. The data were produced as part of the Helmholtz Climate Initiative (HICAM), which focuses on Net Zero 2050 (mitigation) and Adapting to Extreme Events (adaptation). As part of this initiative, estimates of the heat in place and heat storage potential of the subsurface play an important part for mitigation of fossil fuel bound emissions as they pose a promising alternative (geothermal energy). The data presented here, therefore give an overview of areas which might be suited for geothermal applications in the different geothermal target units and formations. We integrated the recently published TUNB Model (BGR et al., 2021) as well as available borehole data, data from the Sandsteinfazies and GeoPoNDD projects (Franz et al., 2018, 2015) and temperature data from two models (Agemar et al., 2014; Frick et al., 2021) the process of which will be described in the following.

3D-CEBS: Three-dimensional lithospheric-scale structural model of the Central European Basin System and adjacent areas

We provide a set of grid files that collectively allow recreating a 3D geological model which covers the Central European Basin System and adjacent areas. The data publication is a complement to the publication of Maystrenko and Scheck-Wenderoth (2013) with a higher spatial and stratigraphic resolution. The structural model consists of (i) 11 sedimentary units including sea water; (ii) five crystalline crust units composed of four upper crustal units and one lower crustal unit; (iii) one lithospheric mantle unit. The available files include information on the regional variation of these geological units in terms of their depth and thickness, both attributes being allocated to regularly spaced grid nodes with horizontal spacing of 4 km. In comparison, the horizontal spacing of data provided by Maystrenko and Scheck-Wenderoth (2013) was 16 km. Besides, the model provided here resolves Permian, Mesozoic and Cenozoic sediments and Permo-Carboniferous volcanics. The model has originally been developed to analyse the first-order structural features characterizing the crust and the lithospheric mantle below the Central European Basin System and adjacent areas and obtain a basis for numerical simulations of heat transport and to calculate the lithospheric-scale conductive thermal field. Such simulations require the subsurface variation of physical rock properties to be defined, the 3D model differentiates units of contrasting materials, i.e. rock types. On that account, a large number of geological and geophysical data have been analysed (see Related Works) and we shortly describe here how they have been integrated into a consistent 3D model (Methods). For further information on the data usage and the characteristics of the units (e.g., lithology, density, thermal properties), the reader is referred to Maystrenko and Scheck-Wenderoth (2013). The contents and structure of the grid files provided herewith are described in the Technical Information section and the associated data description file (pdf).

3D geological model of Berlin - Germany

This dataset provides the grid files which were used to generate the 3d structural model for Berlin, capital city of Germany. It covers a rectangular area around the political boundaries of Berlin. Geologically the region is located in the Northeast German Basin which is in turn part of the Central European Basin System. The data publication is a compliment to the publications Frick et al., (2019) and Haacke et al., (2019) and resolves 23 geological units. These can be separated into eight Cenozoic, eight Mesozoic and three Paleozoic units, the upper and lower crust as well as the lithospheric mantle. We present files which show the regional variation in depth and thickness of all units in the form of regularly spaced grids where the grid spacing is 100 m. This model was created as part of the ongoing project Geothermal potential Berlin which was also partly situated in Energy Systems 2050, both of whom look at the evaluation of the local thermal field and the closely related geothermal potential. These are obtained by simulating fluid- and heatflow in 3d with numerical models built based on the data presented here. These numerical models and simulations rely heavily on a precise representation of the subsurface distribution of rock properties which are in turn linked to the different geological units. Hence, we integrated all available geological and geophysical data (see related work) into a consistent 3D structural model and will describe shortly how this was carried out (Methods). For further information the reader is referred to Frick et al., (2016) and Frick et al., (2019).

3D-URG: 3D gravity constrained structural model of the Upper Rhine Graben

We provide a set of grid files that collectively allow recreating a 3D geological model which covers the Upper Rhine Graben and its adjacent tectonic domains, such as portions of the Swiss Alps, the Molasse Basin, the Black Forest and Vosges Mountains, the Rhenish Massif and the Lower Rhine Graben. The data publication is a complement to the publication of Freymark et al. (2017). Accordingly, the provided structural model consists of (i) 14 sedimentary and volcanic units; (ii) a crystalline crust composed of seven upper crustal units and a lower crustal unit; and (iii) two lithospheric mantle units. The files provided here include information on the regional variation of these geological units in terms of their depth and thickness, both attributes being allocated to regularly spaced grid nodes with horizontal spacing of 1 km. The model has originally been developed to obtain a basis for numerical simulations of heat transport, to calculate the lithospheric-scale conductive thermal field and assess the related geothermal potentials, in particular for the Upper Rhine Graben (a region especially well-suited for geothermal energy exploitation). Since such simulations require the subsurface variation of physical rock properties to be defined, the 3D model differentiates units of contrasting materials, i.e. rock types. On that account, a large number of geological and geophysical data have been analysed (see Related Work) and we shortly describe here how they have been integrated into a consistent 3D model (Methods). For further information on the data usage and the characteristics of the units (e.g., lithology, density, thermal properties), the reader is referred to the original article (Freymark et al., 2017). The contents and structure of the grid files provided herewith are described in the Technical Info section.

3D-NEA: Three-dimensional lithospheric-scale structural model of the North East Atlantic

The Northeast Atlantic (NEA) region has long been a subject of interest due to its complex geological history, particularly regarding the interaction between the Iceland plume and the lithospheric plates. In this data publication, we present a comprehensive three-dimensional structural and density model of the NEA crust and uppermost mantle, consolidating and integrating a wide range of previously fragmented data sets. Our model highlights the influence of the Iceland plume on the region's geological evolution, shedding light on the mechanisms that facilitated the continental breakup between Europe and Laurentia during the earliest Eocene period. The whole workflow and methods are described in Gomez Dacal et al. (2023) and its Supplementary Information.

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