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  • This dataset is a catalogue of elastic stress models of hydraulic fracturing during the 2018 Preston New Road, PNR-1z operations (described in Clarke et al., 2019). This modelling was produced for the publication Kettlety et al. (2020), which studies the physical mechanisms controlling seismicity during hydraulic fracturing. For further details on the modelling approach and context for these data, see Kettlety et al. (2020) and the README file attached here.

  • The data are derived from interpretation of seismic reflection profiles within the offshore Corinth Rift, Greece (the Gulf of Corinth) integrated with IODP scientific ocean drilling borehole data from IODP Expedition 381 (McNeill et al., 2019a, 2019b). The data include rift fault coordinate (location, geometry) information and slip rate and extension rate information for the major faults. Seismic reflection data were published in Taylor et al. (2011) and in Nixon et al. (2016). Preliminary fault interpretations and rate data, prior to IODP drilling, were published in Nixon et al. (2016). Details of datasets: The data can be viewed in GIS software (ArcGIS, QGIS) or the Excel and .dbf files can be used for viewing of rate data and import of fault coordinates into other software. The 4 folders are for different time periods with shape files for the N-Dipping and S-Dipping Faults in the offshore Corinth Rift and respective slip and extension (horizontal) rates. The shapefiles are digitised fault traces for the basement offsetting faults, picked from the Multichannel Seismic Data collected by the R/V Maurice Ewing. Fault traces are segmented and each segment has an average throw (vertical) rate (Tavg) in mm/yr. The rates for the segments are averages based on measurements at the ends of each segment. The major fault trace segments also have slip-rates (slip_rate) and extension-rates (ext_rate or extension_) in mm/yr. All rates as well as the names for major faults can be located in the attribute table of the shape files along with X- and Y-coordinates. The coordinate system is WGS84 UTM Zone 34N. The shape files can be loaded into a GIS (ArcGIS, QGIS etc.) allowing mapping and visualization of the fault traces and their activity rates. In addition, the attribute tables are .dbf files found within each folder. These have also been provided as .xlsx (Excel) files which include the fault coordinate information, and slip rates and extension rates along the major faults. References McNeill, L.C., Shillington, D.J., Carter, G.D.O., and the Expedition 381 Participants, 2019a. Corinth Active Rift Development. Proceedings of the International Ocean Discovery Program, 381: College Station, TX (International Ocean Discovery Program). McNeill, L.C., Shillington, D.J., et al., 2019b, High-resolution record reveals climate-driven environmental and sedimentary changes in an active rift, Scientific Reports, 9, 3116. Nixon, C.W., McNeill, L.C., Bull, J.M., Bell, R.E., Gawthorpe, R.L., Henstock, T.J., Christodoulou, D., Ford, M., Taylor, B., Sakellariou, S. et al., 2016. Rapid spatiotemporal variations in rift structure during development of the Corinth Rift, central Greece. Tectonics, 35, 1225–1248. Taylor, B., J. R. Weiss, A. M. Goodliffe, M. Sachpazi, M. Laigle, and A. Hirn (2011), The structures, stratigraphy and evolution of the Gulf of Corinth Rift, Greece, Geophys. J. Int., 185(3), 1189–1219.

  • Locations of samples collected to constrain the recent activity on normal faults across Nevada. The geological samples will be used to measure the amount of exhumation that different normal faults of the Basin and Range experienced over the last 5 million years. The samples have been collected from granitic rocks that are expected to yield apatite crystals. (Uranium-Thorium)/Helium thermochronometry will be conducted on these samples to determine the cooling history of rocks from temperatures of approximately 70 degrees celsius. The samples are collected across Nevada at locations close to the fault to determine the most recent stages of exhumation. The ranges sampled are the Wassuk Range, White Range, Toiyabe Range, South Egan Range, Schell Range, Wheeler Range, House Range, Wasatch, Deep Greek, Ruby Range, Cortez Range, Humbolt Range, Dixie Valley, and Carson Range. Samples weigh approximately 2kg each. This sample coverage will constrain extension rates across the Basin and Range which is of interest to geologists, geodynamicists, and researchers interested in fault hazard.

  • This dataset shows both the micro-scale mechanisms and acoustic response involved in shear failure of a deforming porous rock. To our knowledge, this is the first such dataset to combine simultaneous acoustic measurements and x-ray tomography imaging. It comprises a time-series of 3D in-situ synchrotron x-ray microtomography (µCT) volumes showing a Clashach sandstone sample (CL10) undergoing triaxial deformation to failure under a constant acoustic emissions (AE) event rate. Use of a constant AE event rate slowed down the failure process after peak stress, enabling shear failure to be captured in unprecedented spatio-temporal detail by the µCT volumes. These volumes are accompanied by the local incremental 3D strain fields and simultaneously acquired waveforms from acoustic emissions and ultrasonic velocity surveys, as well as mechanical bulk stress and strain. These data are fully explained in Cartwright-Taylor et al. Seismic events miss important grain-scale mechanisms governed by kinematics during shear failure of porous rock, in review at Nature Communications. We also include an equivalent time-series of the same data types showing a second Clashach sandstone sample (CL04) undergoing triaxial deformation to failure, this time under a constant strain rate where failure happened abruptly, shortly after peak stress. Both collections were acquired in-situ on the beamline I12-JEEP at the Diamond Light Source, Didcot, UK, in September 2019. Each 3D µCT volume of the sample is contained in a .zip file labelled with the sequential scan number. Each volume comprises reconstructed 16-bit grey-scale data in a sequence of 2D image files (.tif), each numbered according to the depth at which it lies within the sample volume. The file dimensions are pixels, with an edge length of 7.91 µm. Two further .zip files contain the incremental 3D volumetric and deviatoric strain fields, obtained from digital volume correlation between neighbouring µCT volumes. Each strain field consists of a 32-bit 3D image file (.tif) in pixels with an edge length of 316.4 µm, labelled with its scan increment. Also included are (i) .csv files, containing the mechanical stress and strain time-series, the time and mechanical data at which each µCT volume was scanned, and the acoustic emissions event rate data, and (ii) .zip files containing times and waveforms for the acoustic emissions and ultrasonic velocity surveys as .ascii files. The .zip and .xlsx files are labelled with the sample name, the data type (grey-scale, strain-volumetric, strain-deviatoric, seismic, mechanical, mechCT, eventrateAE) and the sequential scan number (grey-scale only) according to the following convention: sample_datatype_scan#. We acknowledge Diamond Light Source for time on beamline I12-JEEP under proposal MG22517. This work is supported by the UK's Natural Environment Research Council (NERC) through the CATFAIL project NE/R001693/1 Catastrophic failure: what controls precursory localisation in rocks?

  • This collection comprises two time-series of 3D in-situ synchrotron x-ray microtomography (μCT) volumes showing two Ailsa Craig micro-granite samples (ACfresh02 and ACHT01) undergoing triaxial deformation. These data were collected in-situ at the PSICHE beamline at the SOLEIL synchrotron, Gif-sur-Yvette, France in December 2016 (standard proposal 20160434) and are fully explained in Cartwright-Taylor A., Main, I.G., Butler, I.B., Fusseis, F., Flynn M. and King, A. (in press), Catastrophic failure: how and when? Insights from 4D in-situ x-ray micro-tomography, J. Geophys. Res. Solid Earth. Together, these two time-series show the influence of heterogeneity on the micro-crack network evolution. Ailsa Craig micro-granite is known for being virtually crack-free. One sample (ACfresh02) remained as-received from the quarry until it was deformed, while the second (ACHT01) was slowly heated to 600 degC and then slowly cooled prior to deformation in order to introduce material disorder in the form of a network of nano-scale thermal cracks. Thus these two samples represent two extreme end-members: (i) ACfresh02 with the lowest possible (to our knowledge) natural pre-existing crack density, and so is a relatively homogeneous sample and (ii) ACHT01 with a thermally-induced nano-crack network imprinted over the nominally crack-free microstructure, and therefore has increased heterogeneity relative to ACfresh02. Each 3D μCT volume shows the sub-region of each sample in which the majority of damage was located and has three parts. Part one is reconstructed 16-bit greyscale data. Part two is 8-bit binary data showing individual voids (pores and micro-cracks) in the dataset after segmentation. Part three is 32-bit data showing the local thickness of each void, as in Cartwright-Taylor et al. (in press) Figures 4 and 5. Each part is a zip file containing a sequence of 2D image files (.tif), sequentially numbered according to the depth (in pixels, parallel to the loading axis) at which it lies within the sample volume. File dimensions are in pixels (2D), with an edge length of 2.7 microns. Each zip file is labelled with the sample name, the relevant letter for each 3D volume as given in Cartwright-Taylor et al. (in press) Tables 3 and 4, part 1, 2 or 3 (depending whether the data are greyscale, binary or local thickness respectively), the differential stress (MPa) on the sample, and the associated ram pressure (bar) to link with individual file names. The following convention is used: sample_letter_part_differentialstress_rampressure_datatype. Also included are (i) two spreadsheets (.xlsx), one for each sample, containing processing parameters and the mechanical stress and strain at which each volume was scanned, and (ii) zip files containing .csv files containing measurement data for the labelled voids in each volume. N.B. void label numbers are not consistent between volumes so they can only be used to obtain global statistics, not to track individual voids.