3D geological model of Berlin - Germany

DOI

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).

For creating this 3D structural model numerous datasets have been integrated. For this we first visualized all data, that is geological cross-sections, drilled well tops, water depths, seismic lines and larger scale models using the commercial software Petrel (©Schlumberger). We then split those datasets into the desired output horizons, removing inconsistencies between them, and using the scattered information of each of the units top elevations to interpolate to regular grids. This was done by the convergent interpolation algorithm of Petrel and a regular grid resolution of 100 m. Especially for the deeper units where only sparse information can be obtained from drilled well tops, we relied on existing models of the Central European Basin System and of the Northeast German Basin which integrated all available GDR seismic lines and are gravity constrained. These have been used along with the 3D Brandenburg model to provide the carcass for the model where no local information was available. Therefore, the crust, mantle and Pre-Permian sediment configuration was derived from larger scale models. For the overlying model units available deep seismic lines along with all deep wells were integrated. For the shallower model units (i.e. Cenozoic) highly resolved geological cross-sections and a dense population of wells were integrated along with the seismic lines. In a final step, high resolution data of the topography (i.e. lake surface and earth surface) were combined with lake bathymetry data to derive the geological surface of the model.

The grids provided are space separated ascii files for a) the elevation of the top and b) the thickness of each unit, with their structure being identical. The columns for a) are 1: x-coordinate, 2: y-coordinate, and 3: elevation (meter above sea level). For b) the columns are 1: x-coordinate, 2: y-coordinate, and 3: thickness (meter). The horizontal dimensions are 43.5 x 53 km. The resolution of the files is identical, each having a spacing of 100 m. The associated coordinate system is Gauß-Krüger DHDN Zone 4. The naming of the files includes the layer name (geological unit) as well as a number representing the structural position in the model in ascending order. Hence, recomposing the model one would have to order the grids by ascending number to build the model from top to bottom. The vertical resolution of the model is heterogeneous since model units have heterogeneous distributions. A thickness of "0" is denoted where the unit is absent.

Identifier
DOI https://doi.org/10.5880/GFZ.4.5.2020.005
Related Identifier https://doi.org/10.1155/2019/4129016
Related Identifier https://doi.org/10.5194/adgeo-49-9-2019
Related Identifier https://doi.org/10.1016/j.egypro.2016.10.011
Related Identifier https://doi.org/10.5194/adgeo-45-177-2018
Related Identifier https://gdz.bkg.bund.de/index.php/default/digitales-gelandemodell-gitterweite-10-m-dgm10.html
Related Identifier https://doi.org/10.1002/ggge.20192
Related Identifier https://doi.org/10.1016/j.tecto.2013.04.023
Related Identifier https://gfzpublic.gfz-potsdam.de/pubman/item/item_1182898_2/component/file_1182897/11071_Moeck%20et%20al._Geothermal%20Exploration.pdf
Related Identifier https://doi.org/10.1007/s12665-013-2438-4
Related Identifier http://books.google.de/books?id=Ng88OAAACAAJ
Related Identifier https://doi.org/10.1007/s12665-013-2679-2
Related Identifier https://daten.berlin.de/datensaetze/geologische-schnitte-umweltatlas-wms-0
Related Identifier https://doi.org/10.2312/gfz.syserde.09.01.1
Metadata Access http://doidb.wdc-terra.org/oaip/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:doidb.wdc-terra.org:6957
Provenance
Creator Frick, Maximilian ORCID logo; Bott, Judith ORCID logo; Scheck-Wenderoth, Magdalena ORCID logo; Cacace, Mauro ORCID logo; Haacke, Nasrin (ORCID: 0000-0001-9065-729X); Schneider, Michael
Publisher GFZ Data Services
Contributor Frick, Maximilian; Scheck-Wenderoth, Magdalena; Schneider, Michael; Limberg, Alexander; Hörmann, Ulrike; Zapf, Sarah; Dronski, Christiane; Wagner, Michael
Publication Year 2020
Funding Reference FP7 Energy
Rights CC BY 4.0; http://creativecommons.org/licenses/by/4.0/
OpenAccess true
Contact Frick, Maximilian (GFZ German Research Centre for Geosciences, Potsdam, Germany)
Representation
Resource Type Dataset
Discipline Geology; Geosciences; Geospheric Sciences; Natural Sciences
Spatial Coverage (13.046W, 52.322S, 13.839E, 52.722N); Berlin Model