10.18419/darus-1435Balcewicz, MartinMartinBalcewicz0000-0001-9953-1431Bochum University of Applied Sciences, Bau- und UmweltingenieurwesenRuf, MatthiasMatthiasRuf0000-0003-0299-5921University of Stuttgart, Institute of Applied Mechanics (CE)Steeb, HolgerHolgerSteeb0000-0001-7602-4920University of Stuttgart, Institute of Applied Mechanics (CE) & SimTechSaenger, Erik H.Erik H.Saenger0000-0002-2057-4728Bochum University of Applied Sciences, Bau- und Umweltingenieurwesen; Fraunhofer IEG, Institution for Energy Infrastructures and Geothermal Systems; Ruhr-University Bochum, Institute of Geology, Mineralogy and GeophysicsDigital rock physics: A geological driven workflow for the segmentation of anisotropic Ruhr sandstone: segmented subvolumesDaRUS2021Computer and Information ScienceEarth and Environmental SciencesEngineeringRuhr sandstonemicro X-Ray Computed Tomography (micro-XRCTDigital Rock Mechanics (DRP)Image segmentaionSteeb, HolgerHolgerSteebUniversity of Stuttgart, Institute of Applied Mechanics (CE) & SC SimTech2021-05-04591140884148380493014391114417306819801application/pdfapplication/x-rar-compressedapplication/x-rar-compressedapplication/x-rar-compressedapplication/x-rar-compressed1.0CC BY 4.0The Ruhr sandstone is assigned to the Upper Carboniferous and is part of the Ruhr cyclothem located in North Rhine-Westphalia, which consists of clays, siltstones, mudstones, sandstones, and interbedded coal seams. The sediment was chemically and mechanically compacted, folded, and faulted during the Hercynian orogeny. The studied microstructure of the Ruhr sandstone indicates depths of up to 6000 m and reconstructed, possible temperatures of over 120 ºC. This results in a complex mineralogical structure compared to other sandstones such as the Berea sandstone or the Fontainbleau sandstone. As part of the Balcewicz et al. (2021) publication, we made a first attempt to study the Ruhr Sandstone using Digital Rock Physics (DRP).<br> <br> This dataset contains two different binned subvolumes of the micro-XRCT data set presented in Ruf et al. (2021). Based on a 1600³ voxel subvolume from the original data set, an 800³ voxel cube subvolume ("subvolume_2x2x2_binned.rar"), and a 400³ voxel cube subvolume ("subvolume_4x4x4_binned.rar") were generated by a 2x2x2 and 4x4x4 binning procedure, subsequently. This means that both data sets show the same physical region but distinguishing in the resolution. Both data sets were then segmented into a total of eight phases: (1) clean pore, (2) soiled pore, (3) quartz, (4) sericite, (5) albite, (6) orthoclase, (7) pyrite, and (8) high angle quartz grain boundaries. The idea of dividing the pore space into two distinct phases was inspired by thin-section studies of the microstructure. Here we found that there is a difference between (1) open pores and (2) pores filled with rock fragments of the host rock. A detailed description of the segmentation workflow can be looked up in Balcewicz et al. (2021) publication.<br>