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  • Data  (52)
  • EARTH SCIENCE 〉 SOLID EARTH
  • Seismology
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  • 1
    Publication Date: 2021-09-30
    Description: Abstract
    Description: This data set includes the results of digital image correlation of ten brittle-viscous experiments on crustal extension and four benchmark experiments performed at the Tectonic Modelling Lab of the University of Bern (UB). The experiments demonstrate the differences in rift development in orthogonal versus rotation extension. Detailed descriptions of the experiments and monitoring techniques can be found in Zwaan et al. (2019) to which this data set is supplementary. Additional background information concerning the general modelling approach are available in Zwaan et al. (2016).. The data presented here consist of movies displaying digital image correlation (DIC) derived surface and internal displacement fields as well as profiles of the lateral cumulative surface displacements.Digital photographs of the experimental surface and digital image cross section of the computed CT-scans were analyzed with DIC (Adam et al., 2005, 2013) techniques to quantify displacements in the image plane at high precision (〈0.1 mm). DIC was undertaken with the software DaVis 8.0 (LaVision) applying 2D-DIC (FFT-legacy) multipass processing with a final interrogation window size of 32x32 (CT: 12x12) pixels and 50% (CT: 25%) overlap.
    Keywords: analogue models of geologic processes ; EPOS ; Multi-scale laboratories ; analogue modelling results ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION ; EARTH SCIENCE 〉 SOLID EARTH ; tectonic setting 〉 extended terrane setting 〉 continental rift setting ; tectonic process 〉 continental_breakup 〉 rifting ; rift valley ; depression ; Silicon/Silly putty/PDMS ; Sand 〉 Quartz Sand ; Sand 〉 Corundum Sand ; Extension box ; Digital Image Correlation (DIC) / Particle Image Velocimetry (PIV) 〉 StrainMaster (La Vision GmbH) ; X-ray computed tomographic scanner (CT-scan) ; SLR camera ; Surface image
    Language: English
    Type: Dataset , Dataset
    Format: 3 Files
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  • 2
    Publication Date: 2021-10-27
    Description: Abstract
    Description: A new seismic model for crust and upper mantle of the south Central Andes is derived from full waveform inversion, covering the Pampean flat subduction and adjacent Payenia steep subduction segments. Focused crustal low‐velocity anomalies indicate partial melts in the Payenia segment along the volcanic arc, whereas weaker low‐velocity anomalies covering a wide zone in the Pampean segment are interpreted as remnant partial melts. Thinning and tearing of the flat Nazca slab is inferred from gaps in the slab along the inland projection of the Juan Fernandez Ridge. A high‐velocity anomaly in the mantle below the flat slab is interpreted as relic Nazca slab segment, which indicates an earlier slab break‐off triggered by the buoyancy of the Juan Fernandez Ridge during the flattening process. In Payenia, large‐scale low‐velocity anomalies atop and below the re‐steepened Nazca slab are associated with the re‐opening of the mantle wedge and sub‐slab asthenospheric flow, respectively.
    Keywords: Seismic model ; crust ; upper mantle ; central Chile ; Western Argentina ; Pampean flat ; Juan Fernandez Ridge ; relic slab ; EARTH SCIENCE 〉 SOLID EARTH ; EARTH SCIENCE SERVICES 〉 MODELS 〉 GEOLOGIC/TECTONIC/PALEOCLIMATE MODELS
    Type: Dataset , Dataset
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  • 3
    Publication Date: 2022-01-05
    Description: Abstract
    Description: 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.
    Description: Methods
    Description: Different data sets were integrated to derive the lithospheric features: - We used the global relief model of ETOPO1 (Amante and Eakins 2009) for the topography and bathymetry. - The sub-surface structures were defined by integrating seismically constrained models, including the South-American crustal thickness of Assumpção et al. (2013; model A; 0.5 degree resolution), the sediment thickness of CRUST1 (Laske et al. 2013) and the slab geometry of SLAB2 (Hayes et al. 2018). - Additionally, we included seismic reflection and refraction profiles performed on the Chile margin (Araneda et al. 2003; Contreras-Reyes et al. 2008, 2014, 2015; Flueh et al. 1998; Krawzyk et al. 2006; Moscoso et al. 2011; Sick et al. 2006; Von Huene et al. 1997). - Besides, we used sediment thickness maps from the intracontinental basin database ICONS (6 arc minute resolution, Heine 2007) and two oceanic sediment compilations: one along the southern trench axis (Völker et al. 2013) and another of global-scale (GlobSed; Straume et al. 2019). To build the interfaces between the main lithospheric features, we compiled and interpolated these datasets on a regular grid with a surface resolution of 25 km. For that purpose, the convergent algorithm of the software Petrel was used. We assigned constant densities within each layer, except for the lithospheric mantle. In this case, we implemented a heterogeneous distribution by converting s-wave velocities from the SL2013sv seismic tomography (Schaeffer and Lebedev 2013) to densities. The python tool VelocityConversion was used for the conversion (Meeßen 2017). To further constrain the crustal structure of the upper plate, a gravity forward modelling was carried out using IGMAS+ (Schmidt et al. 2010). The gravity anomaly from the model (calculated gravity) was compared to the free-air anomaly from the global gravity model EIGEN-6C4 (observed gravity; Förste et al 2014; Ince et al. 2019). Subsequently, the crystalline crust of the upper plate was split vertically into two layers of different densities. We inverted the residual between calculated and observed gravity to compute the depth to the interface between the two crustal layers. For the inverse modelling of the gravity residual, the Python package Fatiando a Terra was used (Uieda et al. 2013) For each layer, the depth to the top surface, thickness and density can be found as separate files. All files contain identical columns: - Northing as "X Coord (UTM zone 19S)"; - Easting as "Y Coord (UTM zone 19S)"; - depth to the top surface as "Top (m.a.s.l)" and - thickness of each layer as "Thickness (m)". The header ‘Density’ indicates the bulk density of each unit in kg/m3. For the oceanic and continental mantle units, a separate file is provided with a regular grid of the density distribution with a lateral resolution of 8 km x 9 km and a vertical resolution of 5 km. The containing columns are: Northing as "X Coord (UTM zone 19S)"; Easting as "Y Coord (UTM zone 19S)"; depth as "Depth (m.a.s.l)" and density as "Density (kg/m3)"
    Keywords: Lithosphere ; Gravity Modelling ; Andes ; EARTH SCIENCE ; EARTH SCIENCE 〉 LAND SURFACE 〉 TOPOGRAPHY 〉 TOPOGRAPHICAL RELIEF ; EARTH SCIENCE 〉 OCEANS 〉 BATHYMETRY/SEAFLOOR TOPOGRAPHY 〉 BATHYMETRY ; EARTH SCIENCE 〉 SOLID EARTH ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOMORPHIC LANDFORMS/PROCESSES 〉 TECTONIC LANDFORMS 〉 MOUNTAINS ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOMORPHIC LANDFORMS/PROCESSES 〉 TECTONIC PROCESSES 〉 SUBDUCTION ; EARTH SCIENCE 〉 SOLID EARTH 〉 GRAVITY/GRAVITATIONAL FIELD ; EARTH SCIENCE 〉 SOLID EARTH 〉 GRAVITY/GRAVITATIONAL FIELD 〉 GRAVITY ; EARTH SCIENCE 〉 SOLID EARTH 〉 ROCKS/MINERALS/CRYSTALS 〉 SEDIMENTS ; EARTH SCIENCE SERVICES 〉 MODELS 〉 GEOLOGIC/TECTONIC/PALEOCLIMATE MODELS
    Type: Dataset , Dataset
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  • 4
    Publication Date: 2022-01-05
    Description: Abstract
    Description: The southern Central Andes (SCA, 29°S-39°S) are characterized by the subduction of the oceanic Nazca Plate beneath the continental South American Plate. One striking feature of this area is the change of the subduction angle of the Nazca Plate between 33°S and 35°S from the Chilean-Pampean flat-slab zone (〈 5° dip) in the north to a steeper sector in the south (~30° dip). Subduction geometry, tectonic deformation, and seismicity at this plate boundary are closely related to the lithospheric strength in the upper plate. Despite recent research focused on the compositional and thermal characteristics of the SCA lithosphere, the lithospheric strength distribution remains largely unknown. Here we calculated the long-term lithospheric strength on the basis of an existing 3D model describing the variation of thickness, density and temperature of geological units forming the lithosphere of the SCA. The model consists of 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.
    Description: Methods
    Description: To compute the lithospheric strength distribution in the SCA, we used the geometries and densities of the units forming the 3D lithospheric scale model of Rodriguez Piceda et al. (2020a,b). The units considered for the rheological calculations are (1) oceanic and continental sediments; (3) upper continental crystalline crust; (4) lower continental crystalline crust; (5) continental lithospheric mantle (6) shallow oceanic crust; (7) deep oceanic crust; (8) oceanic lithospheric mantle; and (9) oceanic sub-lithospheric mantle. The thermal field was derived from a temperature model of the SCA (Rodriguez Piceda et al. under review) covering the same region as the structural model of Rodriguez Piceda et al. (2020a). To calculate the temperature distribution in the SCA, the model volume was split into two domains: (1) a shallow domain, including the crust and uppermost mantle to a depth of ~50 km below mean sea level (bmsl), where the steady-state conductive thermal field was calculated using as input the 3D structural and density model of the area of Rodriguez Piceda et al. (2020b, a) and the finite element method implemented in GOLEM (Cacace and Jacquey 2017); (2) a deep domain between a depth of ~50 and 200 km bmsl, where temperatures were converted from S wave seismic velocities using the approach by Goes et al. (2000) as implemented in the python tool VelocityConversion (Meeßen 2017). Velocities from two alternative seismic tomography models were converted to temperatures (Assumpção et al. 2013; Gao et al. 2021). A detailed description of the method can be found in Rodriguez Piceda et al. (under review). The yield strength of the lithosphere (i.e. maximum differential stress prior to permanent deformation) was calculated using the approach by Cacace and Scheck-Wenderoth (2016). We assumed brittle-like deformation as decribed by Byerlee’s law (Byerlee 1968) and steady state creep as the dominant form of viscous deformation. Low-temperature plasticity (Peierls creep) at differential stresses greater than 200 MPa was also included (Goetze et al. 1978; Katayama and Karato 2008). In addition, effective viscosities were computed from a thermally activated power-law (Burov 2011) We assigned rheological properties to each unit of the model on the basis of laboratory measurements (Goetze and Evans 1979; Ranalli and Murphy 1987; Wilks and Carter 1990; Gleason and Tullis 1995; Hirth and Kohlstedt 1996; Afonso and Ranalli 2004). These properties were chosen, in turn, based on the dominant lithology of each layer derived from seismic velocities and gravity-constrained densities. More methodological details and a table with the rheological properties are depicted in Rodriguez Piceda et al. (under review). The rheological results using the thermal model derived from the seismic tomography of Assumpção et al. (2013) and Gao et al. (2021) can be found in Rodriguez Piceda et al. (under review, under review), respectively
    Description: Other
    Description: Two comma-separated files can be found with the calculated lithospheric temperature, strength and effective viscosity for all the points in the model (2,274,757). These points are located at the top surface of each model unit. Therefore, the vertical resolution of the model is variable and depends on the thickness and refinement of the structural modelled units. SCA_RheologicalModel_V01.csv corresponds to the results using the mantle thermal field from the tomography by Assumpção et al. (2013) and presented in Rodriguez Piceda et al. (under review). SCA_RheologicalModel_V02.csv includes the results using the mantle thermal field of Gao et al. (2021) and presented in Rodriguez Piceda et al. (under review). Each of these files contains the following columns: -Northing as " X COORD (m [UTM Zone 19S]) " -Easting as " Y COORD (m [UTM Zone 19S]) " -Depth to the top surface as " Z COORD (m.a.s.l.)" -Temperature in degree Celsius as " TEMP (deg. C) " -Yield strength in MPa as “STRENGTH (MPa)” -Effective viscosity in base-10 logarithm of Pa*s as “EFF VISCOSITY (log10(Pa*s))” The dimensions of the model is 700 km x 1100 km x 200 km. The horizontal resolution is 5 km, while the vertical resolution depends on the thickness of the structural units.
    Keywords: Lithosphere ; Rheology ; Subduction ; Andes ; EARTH SCIENCE ; EARTH SCIENCE 〉 SOLID EARTH ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOMORPHIC LANDFORMS/PROCESSES 〉 TECTONIC LANDFORMS 〉 MOUNTAINS ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOMORPHIC LANDFORMS/PROCESSES 〉 TECTONIC PROCESSES 〉 SUBDUCTION ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 PLATE TECTONICS 〉 STRESS
    Type: Dataset , Dataset
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  • 5
    Publication Date: 2022-03-22
    Description: Abstract
    Description: Despite the amount of research focused on the Alpine orogen, significant unknowns remain regarding the thermal field and long term lithospheric strength in the region. Previous published interpretations of these features primarily concern a limited number of 2D cross sections, and those that represent the region in 3D typically do not conform to measured data such as wellbore or seismic measurements. However, in the light of recently published higher resolution region specific 3D geophysical models, that conform to secondary data measurements, the generation of a more up to date revision of the thermal field and long term lithospheric yield strength is made possible, in order to shed light on open questions of the state of the orogen. 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, with the Central and Eastern Alps and the northern foreland being the best covered regions.
    Keywords: Alps ; Forelands ; Po Basin ; Molasse Basin ; Upper Rhine Graben ; Ivrea Body ; European Crust ; Adriatic Crust ; Sediment Thickness ; Crustal Thickness ; Vosges Massif ; Black Forest Massif ; Bohemian Massif ; Mantle Density ; 4DMB ; Mountain Building Processes in 4d ; EARTH SCIENCE ; EARTH SCIENCE 〉 SOLID EARTH ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOMORPHIC LANDFORMS/PROCESSES 〉 TECTONIC LANDFORMS 〉 MOUNTAINS ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOTHERMAL DYNAMICS 〉 GEOTHERMAL TEMPERATURE ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 PLATE TECTONICS 〉 STRESS ; lithosphere ; lithosphere 〉 earth's crust ; lithosphere 〉 earth's crust 〉 continental shelf 〉 continent ; lithosphere 〉 earth's crust 〉 sedimentary basin ; physical property 〉 viscosity ; science 〉 natural science 〉 earth science 〉 geophysics
    Type: Dataset , Dataset
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  • 6
    Publication Date: 2022-03-31
    Description: Abstract
    Description: This dataset includes the results of Particle Image Velocimetry (PIV) of one experiment on subduction megathrust earthquakes (with interacting asperities) performed at the Laboratory of Experimental Tectonics (LET) Univ. Roma Tre in the framework of AspSync, the Marie Curie project (grant agreement 658034; https://aspsync.wordpress.com). Detailed descriptions of the experiments and monitoring techniques can be found in Corbi et al. (2017). This data set is from one experiment characterized by the presence of a 7 cm wide barrier separating two asperities with equal size, geometry and friction. Here we provide PIV data relative to a 16.3 min long interval during which the experiment produces 138 analog earthquakes with an average recurrence time of 7 s. The PIV analysis yields quantitative information about the velocity field characterizing two consecutive frames, measured in this case at the model surface. For a detailed description of the experimental procedure, set-up and materials used, please refer to the article of Corbi et al. (2017) paragraph 2. This data set has been used for: a) studying velocity variations (Fig. 2 in Corbi et al., 2021) and rupture patterns (Fig. 3a, b in Corbi et al., 2021) occurring during the velocity peak of one of the two asperities (aka trigger).
    Description: Methods
    Description: The evolution of the analog model was monitored with a digital top-view camera (PIKE-ALLIED with resolution 1600 × 1200 pixels), capturing one frame every 0.133 s. Digital images were then analyzed with MatPIV (Sveen, 2004), which is an open-source software for PIV running under the MATLAB package. This software uses a cross-correlation technique that allows calculating horizontal components (i.e., on the image plane) of surface displacement with about one tenth of a pixel of accuracy. We used the multi-pass protocol with window size of 128 x 128 pixels and 64 x 64 pixels and 50% overlap. Other information e.g., surface displacement can be easily computed from the velocity field knowing the time between frames.
    Keywords: analogue models of geologic processes ; subduction megathrust earthquakes ; asperities ; multi-scale laboratories ; EPOS ; Analog modelling results ; Software tools ; deformation ; geologic process ; tectonic process ; subduction ; Digital Image Correlation (DIC) / Particle Image Velocimetry (PIV) 〉 MatPIV ; Earthquake simulator ; Wedge simulator ; Gelatine ; plate margin setting ; subduction zones ; thrust fault ; Videocamera ; EARTH SCIENCE 〉 SOLID EARTH ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 EARTHQUAKES ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 EARTHQUAKES 〉 EARTHQUAKE OCCURRENCES ; geological process 〉 seismic activity ; geological process 〉 seismic activity 〉 earthquake ; science 〉 natural science 〉 earth science ; science 〉 natural science 〉 earth science 〉 geophysics
    Type: Dataset , Dataset
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  • 7
    Publication Date: 2022-05-13
    Description: Abstract
    Description: A seismic network was installed in the Helsinki capital area of Finland to monitor the response to a 6 km deep geothermal stimulation experiment in 2018. The Institute of Seismology, University of Helsinki (ISUH), installed these 100 geophones in addition to five surface broadband sensors and a 13-site borehole network deployed by the operating company. The stations operated for 106 days between 7 May and 20 August 2018 (day 127 to 232). The data set consists of raw CUBE-recorder data and converted MSEED data.
    Keywords: enhanced geothermal system ; induced seismicity ; array of arrays ; monitoring ; In Situ Land-based Platforms 〉 GEOPHYSICAL STATIONS/NETWORKS 〉 SEISMOLOGICAL STATIONS ; geology ; EARTH SCIENCE 〉 SOLID EARTH ; 201802 ; Otaniemi Reservoir stimulation (ORS)
    Language: English
    Type: Dataset , temporary seismological network
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  • 8
    Publication Date: 2022-05-13
    Description: Abstract
    Description: Bedload transport is a key process in fluvial morphodynamics and hydraulic engineering, but is notoriously difficult to measure. The recent advent of stream-side seismic monitoring techniques provides an alternative to in-stream monitoring techniques, which are often costly, staff-intensive, and cannot be deployed during large floods. Seismic monitoring is a surrogate method requiring several steps to convert seismic data into bedload data. State-of-the-art approaches of conversion exploit physical models predicting the seismic signal generated by bedload transport. Here, we did an active seismic survey (2017-11) and used seismic data from a flood event (2016-02-22) on the Nahal Ehstemoa to constrain a seismic bedload model. We conducted the active seismic survey to determine the local seismic ground properties, i.e., the Green’s function. We also used water depth and bedload grain size distribution to constrain the seismic bedload model and were able to compare the bedload flux obtained from the seismic data using the model with high-quality independent bedload measurements from slot samplers on the site. The complementary non-seismic data is published in a separate data publication (Lagarde et al., 2020).
    Keywords: Ground properties ; Green’s function ; Environmental seismology ; EARTH SCIENCE 〉 SOLID EARTH ; geology
    Type: Dataset , Dataset
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  • 9
    Publication Date: 2022-05-13
    Description: Abstract
    Description: Raw-, SEG-Y and other supplementary data of the landside deployment from the amphibious wide-angle seismic experiment ALPHA are presented. The aim of this project was to reveal the crustal and lithospheric structure of the subducting Adriatic plate and the external accretionary wedge in the southern Dinarides. Airgun shots from the RV Meteor were recorded along two profiles across Montenegro and northern Albania.
    Keywords: Seismology ; Adriatic Plate ; Montenegro ; Albania
    Language: English
    Type: Dataset , controlled source data
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  • 10
    Publication Date: 2022-05-30
    Description: Abstract
    Description: Py4HIP is an open-source software tool for Heat-In-Place calculations implemented as a self-explanatory Jupyter notebook written in Python (Py4HIP.ipynb) Calculating the Heat In Place (HIP) is a standard method for assessing the geothermal potential for a defined geological unit (e.g., Nathenson, 1975; Muffler and Cataldi, 1978; Garg and Combs, 2015). The respective implementation in Py4HIP is based on a volumetric quantification of contained energy after Muffler and Cataldi (1978), where the geological unit at hand is considered spatially variable in terms of its temperature, thickness, porosity, density and volumetric heat capacity of its solid and fluid (brine) components. The energy values provided by Py4HIP as ASCII lists and map representations correspond to the stored energy in J/m^2.
    Description: TechnicalInfo
    Description: Requirements: Py4HIP requires Python 〉= 3.5, JupyterLab, and uses the following packages: • numpy • pandas • pathlib (for creating folders) • matplotlib (for plotting figures)
    Keywords: heat in place ; geothermal potential ; contained energy ; subsurface reservoir ; rock properties ; EARTH SCIENCE ; EARTH SCIENCE 〉 SOLID EARTH ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOTHERMAL DYNAMICS
    Type: Software , Software
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