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Faults and fractures form the largest contrast of fluid flow in the subsurface, while their permeability is highly affected by effective pressure changes. In this experimental study, fractured low-permeability Flechtingen (Rotliegend) sandstones were cyclically loaded in a MTS tri-axial compression cell. Two different loading scenarios were considered: “continuous cyclic loading” (CCL) and “progressive cyclic loading” (PCL). During continuous cyclic loading, a displaced tensile fracture was loaded hydrostatically from 2 to 60 MPa in several repeated cycles. During progressive cyclic loading, the load was increased with a step-wise function (15, 30, 45 and 60 MPa) and unloaded after every loading step. For full elasticity of rock matrix deformation each rock sample has been preconditioned up to 65 MPa. After that, an artificial tensile fracture was introduced into the sample using the Brazilian Disk test. The fractured sample was installed into the MTS triaxial cell at a given offset of 0.5 mm and hydrostatic loading was applied accordingly. The fracture permeability was measured continuously using the cubic law calculated from the hydraulic aperture. Fracture closure was measured using LVDT extensometers during the entire experiment and the resulting fracture closure and stiffness was calculated accordingly. The total deformation of the sample was corrected by the amount of elastic deformation of the rock matrix to obtain the fracture closure only. Potential changes to the fracture surface topography before and after the experiments were analysed from high-resolution surface scans obtained by a 3D profilometer using the fringe pattern projection. The scale-independent roughness exponent was calculated using power spectral density method assuming self-affinity. The fracture aperture distribution and contact-area ratio was calculated by matching the best fitting principal planes of the bottom and top surface and applying a grid search algorithm. The results showed a “stress-memory” effect of fracture stiffness during progressive loading that can be used to identify previous stress states in fractures. This effect is characterized by a transition from a non-linear to a linear (reversible to non-reversible) behaviour of specific fracture stiffness when a previous stress-maximum is exceeded. Furthermore, the evolution of fracture permeability shows less reduction during progressive cyclic loading compared to continuous cyclic loading. The data measured during the flow-through experiment under varying effective pressure are provided in the file “MTS_data.zip”. The data are provided as separate text-files as well as in Excel format with different spreadsheets, such that each figure in the paper can be recalculated and that the underlying data is comprehensive. The name of all three rock samples is given in the file name including the type of the experiment (CCL or PCL). The fracture surfaces and the fracture aperture distributions are found within the file “Surface_data.zip”. This file contains the fracture data of each of the three rock samples as point cloud data (text-files), as well the data calculated from the surfaces.
The Central Andean orogeny is caused by the subduction of the Nazca oceanic plate beneath the South-American continental plate. In Particular, the Southern Central Andes (SCA, 27°-40°S) are characterized by a strong N-S and E-W variation in the crustal deformation style and intensity. Despite being the surface geology relatively well known, the information on the deep structure of the upper plate in terms of its thickness and density configurations is still scarcely constrained. Previous seismic studies have focused on the crustal structure of the northern part of the SCA (~27°-33°S) based upon 2D cross-sections, while 3D crustal models centred on the South-American or the Nazca Plate have been published with lower resolution. To gain insight into the present-day state of the lithosphere in the area, we derived a 3D model that is consistent with both the available geological and seismic data and with the observed gravity field. The model consists on a continental plate with sediments, a two-layer crust and the lithospheric mantle being subducted by an oceanic plate. The model extension covers an area of 700 km x 1100 km, including the orogen, the forearc and the forelands.
We studied the effect of pore fluid chemistry on compaction creep in quartz sand aggregates, as an analogue for clean, highly porous, quartz-rich reservoir sands and sandstone. Creep is specifically addressed, because it is not yet well understood and can potentially cause reservoir compaction even after production has ceased. Going beyond previous work, we focused on fluids typically considered for pressure maintenance or for permanent storage, e.g. water, wastewater, CO2 and N2, as well as agents, such as AlCl3, a quartz dissolution inhibitor, and scaling inhibitors used in water treatment facilities and geothermal energy production. Uniaxial (oedometer) compaction experiments were performed on cylindrical sand samples at constant effective stress (35 MPa) and constant temperature (80 °C), simulating typical reservoir depths of 2-4 km. Insight into the deformation mechanisms operating at the grain scale was obtained via acoustic emission (AE) counting, and by means of microstructural study and grain size analysis applied before and after individual compaction tests.
As a supplement to Huang et al. (2022) “The influence of sediments, lithosphere and upper mantle (anelastic) with lateral heterogeneity on ocean tide loading and ocean tide dynamics”, we provide for the advanced earth model LH-Lyon-3Dae [consisting of 3D elastic sediments, lithosphere and 3D anelastic upper mantle structures, see Huang et al.(2022) for details] the solutions of vertical ocean tide loading (OTL) displacement, self-attraction and loading (SAL) elevation, and ocean tides. Solutions for three tidal constituents, i.e., M2, K1 and Mf, are given. As a comparison, solutions based on the 1D elastic model PREM and the 1D anelastic LH-Lyon-1Dae are also presented. With these solutions, the primary results in Huang et al. (2022) such as the model amplitude differences, RMS differences and the predictions in GNSS stations can be reconstructed.
The data presented here were produced to study glacial and glacio-fluvial catchment erosion using 'tracer thermochronology' where detrital downstream samples can be used to infer the source elevation sectors of sediments when integrated with known surface bedrock ages from the catchment. For the first time, our study used the zircon (U-Th)/He (ZHe) method as tracer thermochronometer. The samples come from the Leones Valley at the northeastern flank of the Northern Patagonian Icefield, Chile (46.7° S) This data set comprises ZHe analytical results from (i) six detrital samples of different depositional age and grain size (622 single-grain analyses in total), and (ii) two previously analyzed (Andrić-Tomašević et al., 2021) bedrock samples (22 single-grain analyses in total), as well as grain size measurements and lithology identification of two of the detrital samples (two pebble samples with 262 and 211 pebbles, respectively). Data are provided in 10 tab-delimited text files. The full description of the data and methods is provided in the data description file.
We present a new Python-based Jupyter Notebook that helps interpreting detrital tracer thermochronometry datasets and quantifying the statistical confidence of such analysis. Users are referred to the linked GitHub repository for usage and methods. https://github.com/mdlndr/ESD_thermotrace
The Alps are one of the best studied mountain ranges in the world, yet significant unknowns remain regarding their crustal structure and density distribution at depth. Previous published interpretations of crustal features within the orogen have been primarily based upon 2D seismic sections, and those that do integrate multiple geo-scientific datasets in 3D, have either focused on smaller sub-sections of the Alps or included the Alps, in low resolution, as part of a much larger study area. Therefore the generation of a 3D, crustal scale, gravity constrained, structural model of the Alps and their forelands at an appropriate resolution has been created here to more accurately describe crustal heterogeneity in the region. The study area of this work focuses on a region of 660 km x 620 km covering the vast majority of the Alps and their forelands are included, with the Central and Eastern Alps and the northern foreland being the best covered regions.Surface GenerationAll referenced data was integrated to constrain sub-surface lithospheric features including: previous regional scale gravitationally and seismically constrained models of the TRANSALP study area, the Upper Rhine Graben, the Mollasse Basin and the Po Basin; continental scale integrative best fit models (EuCRUST-07 and EPcrust); and seismic reflection depths from numerous published deep seismic surveys (e.g. ALP’75, EGT’86, ALP 2002 and EASI). The software package Petrel was used for the creation and visualisation of the modelled surfaces in 3D, representing the key structural and density contrasts within the region. All surfaces were generated with a grid resolution of 20 km x 20 km using Petrel’s convergent interpolation algorithm. During interpolation, a hierarchy of data source types was used in the case of contradiction between the different data sources and was as follows: 1. regional scale, gravitationally and seismically constrained models; 2. regional scale, seismically constrained models; 3. individual seismic reflection surfaces and interpreted sections; 4. continental scale, seismically constrained, integrative best fit models. No subduction interfaces were modelled. Topography and bathymetry were taken from ETOPO1 and the LAB from Geissler (2010).Gravity ModellingThe generated surfaces and the calculated free-air anomaly from the global gravity model EIGEN-6C4, at a fixed height of 6 km above the datum were used in the 3D gravity modelling software IGMAS+ for the constrained of lithospheric density distribution. The layers of the generated model were split laterally into domains of different density, to reflect the heterogeneous nature of the crust within the region. Densities used in the initial structural model were derived from empirical P wave velocity to density conversions (Brocher, 2005) from the input seismic data sources. The densities were then modified, through multiple iterations, until the resulting model produced a gravity field within ± 25 mGal of the observed one. Surfaces generated as part of the integration work were not modified.FilesThe surface depths, thicknesses and densities of the model can be found as tab separated text files for each individual layer of the model (Unconsolidated Sediments, Consolidated Sediments, Upper Crust, Lower Crust and Lithospheric Mantle). The columns in each file are identical: the Easting is given in the “X COORD (UTM Zone 32N)”, Northing in the “Y COORD (UTM Zone 32N)”, the top surface depth of each layer is given as TOP (m.a.s.l), the thickness of each layer is given as THICKNESS (m), and the bulk density of that layer is given as DENSITY (Kg/m^3).
The data set contains stress-strain data of Carrara marble experimentally deformed in triaxial compression at temperatures of 20 – 800°C, confining pressures of 30 – 300 MPa, and strain rates between 10-3 and 10-6 s-1. This range covers conditions, at witch marble deforms in the semi-brittle regime, i.e., strength depends on all parameters, but with different sensitivity. Semi-brittle deformation behavior is expected to be important in the mid continental crust. The experiments were conducted in the Experimental Rock Deformation Laboratory of the GFZ German Research Centre for Geosciences in Potsdam, Germany. The data are separated into 91 individual ASCII files, one for each sample. The corresponding temperature, pressure and strain rate conditions are listed in Tab. 1. of the data description and in the associated work by Rybacki et al. (submitted).
The Central Andean orogen formed as a result of the subduction of the oceanic Nazca plate beneath the continental South-American plate. In the southern segment of the Central Andes (SCA, 29°S-39°S), the oceanic plate subducts beneath the continental plate with distinct dip angles from north to south. Subduction geometry, tectonic deformation, and seismicity at this plate boundary are closely related to lithospheric temperature distribution in the upper plate. Previous studies provided insights into the present-day thermal field with focus on the surface heat flow distribution in the orogen or through modelling of the seismic velocity distribution in restricted regions of the SCA as indirect proxy of the deep thermal field. Despite these recent advances, the information on the temperature distribution at depth of the SCA lithosphere remains scarcely constrained. To gain insight into the present-day thermal state of the lithosphere in the region, we derived the 3D lithospheric temperature distribution from inversion of S-wave velocity to temperature and calculations of the steady state thermal field. The configuration of the region – concerning both, the heterogeneity of the lithosphere and the slab dip – was accounted for by incorporating a 3D data-constrained structural and density model of the SCA into the workflow (Rodriguez Piceda et al. 2020a-b). The model consists on a continental plate with sediments, a two-layer crust and the lithospheric mantle being subducted by an oceanic plate. The model extension covers an area of 700 km x 1100 km, including the orogen (i.e. magmatic arc, main orogenic wedge), the forearc and the foreland, and it extents down to 200 km depth.
This dataset includes paleomagnetic and rock magnetic analyses from four sediment cores collected on continental slope of Storfjorden (EG-02, EG-03, SV-04) and Kveithola (GeoB17603-3) trough‐mouth fans and two cores collected at the crest of the Bellsund (GS191-01PC) and Isfjorden (GS191-02PC) sediment drifts (NW Barents Sea). The dataset gave the opportunity to reconstruct variation of past geomagnetic field at high latitude for the last 22 kya and define the path of the virtual geomagnetic pole (VGP). Data are presented as two metadata table: one with definitions of the column heads and one with the core details; six tables with the data on the measured rock magnetic and paleomagnetic parameters and 3 tables with the results of data analyses and elaboration. List of tables is as follows: 1) Metadata: definition of columns heads; 2) Metadata: core details; 3) GS191-01PC: down-core variation of rock magnetic and paleomagnetic parameters [k (10E-05 SI); ARM (A/m); MDF (mT); NRM (A/m); MAD (°); Incl PCA (°); Decl PCA (°)] for Core GS191-01PC; 4) GS191-02PC: down-core variation of rock magnetic and paleomagnetic parameters [k (10E-05 SI); ARM (A/m); MDF (mT); NRM (A/m); MAD (°); Incl PCA (°); Decl PCA (°)] for Core GS191-02PC; 5) EG03: down-core variation of rock magnetic and paleomagnetic parameters [k (10E-05 SI); ARM (A/m); MDF (mT); NRM (A/m); MAD (°); Incl PCA (°); Decl PCA (°)] for Core EG03; 6) EG02: down-core variation of rock magnetic and paleomagnetic parameters [k (10E-05 SI); ARM (A/m); MDF (mT); NRM (A/m); MAD (°); Incl PCA (°); Decl PCA (°)] for Core EG02; 7) SV04: down-core variation of rock magnetic and paleomagnetic parameters [k (10E-05 SI); ARM (A/m); MDF (mT); NRM (A/m); MAD (°); Incl PCA (°); Decl PCA (°)] for Core SV04; 8) GeoB17603-3: down-core variation of rock magnetic and paleomagnetic parameters [k (10E-05 SI); ARM (A/m); MDF (mT); NRM (A/m); MAD (°); Incl PCA (°); Decl PCA (°)] for Core GeoB17603-3; 9) Cores Correlation: GS191-01PC depth (cm) and ARM (A/m) down-core variations for core GS191-01PC (master core); GS191-02PC depth (cm), GS191-02PC depth transferred to GS191-01PC depth (cm), ARM (A/m) down-core for core GS191-02PC and correlation tie points; GeoB17603-3 depth (cm), GeoB17603-3 depth transferred to GS191-01PC depth (cm), ARM (A/m) down-core for core GeoB17603-3 and correlation tie points; EG02 depth (cm), EG02 depth transferred to GS191-01PC depth (cm), ARM (A/m) down-core for core EG02 and correlation tie points; EG03 depth (cm), EG03 depth transferred to GS191-01PC depth (cm), ARM (A/m) down-core and correlation tie points; SV04 depth (cm), SV04 transferred to GS191-01PC (cm), ARM (A/m) down-core for core SV04 and correlation tie points; 10) Age model: age model for Core GS191-01PC; GS191-02PC; EG02; EG03; SV04 and correlation tie points; 11) NBS stack: paleomagnetic inclination, declination and RPI variations for NBS22.2k stack. In order to define high-resolution correlation between the cores the along-core variation of rock magnetic and paleomagnetic parameters (Sagnotti et al., 2011; Caricchi et al., 2018; Caricchi et al., 2019) have been integrated with the distribution of characteristic lithofacies (Lucchi et al., 2013), and the available age constraints (Sagnotti et al., 2011; Caricchi et al., 2018, Caricchi et al., 2019; Caricchi et al., 2020). Core to core correlation has been reconstructed by means of the StratFit software (Sagnotti and Caricchi, 2018), which is based on the Excel forecast function and linear regression between subsequent couples of selected tie-points. The data are presented as one Excel sheet with eleven tables and in tab-delimited ASCII format in the zip folder: 2022-028_Caricchi-et-al_data-txt.zip.
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