7 documents found in 216ms
# 1
Kueck, Jochem
Abstract: Compilation of downhole logging data from the borehole PTA2 inside Bradshaw Army Camp in the saddle region between Mauna Kea and Mauna Loa on the Big Island of Hawai'i (Composite OSG Logging Data Hawaii PTA2.asc, ASCII). The PTA2 borehole was fully cored into a lava dominated rock sequence; open hole bit size was HQ. The data were derived from the following logging runs in February and June 2016: GR total natural Gamma ray, SGR spectrum natural Gamma ray, MS magnetic susceptibility, BS borehole sonic, DIP dipmeter, and ABI43 acoustic borehole imager. All sondes were run in an open hole section below the casing shoe: 885 - 1566 m except for the SGR, which was also measured in the cased upper section and the ABI43, which also logged a 40 m long section inside the casing. The logging data are complemented by Acoustic borehole image data that were measured in June 2016 in the open hole section below the casing shoe: 889 - 1566 m; open hole bit size was HQ. Logging sonde: ABI43 (ALT). The images are oriented to north (magnetic orientation). File formats are DLIS and WCL (WellCAD 5.2). The data are further described in Jerram et al. (2019, https://doi.org/10.5194/sd-25-15-2019). The logging data was measured and processed by the Operational Support Group (OSG) of ICDP hosted by GFZ Potsdam (see https://www.icdp-online.org/support/service/downhole-logging/?type=12&tx_icdpdatatables_pi1%5Bajaxcall%5D=1 for further information). Detailed information about the OSG Slimhole Wireline Logging Sondes ist provided at https://www.icdp-online.org/fileadmin/icdp/services/img/Logging/OSG_Slimhole_Sondes_Specs_pics_2019-05.pdf. The data are also described in Jerram et al. (2019), Millet et al. (2017, 2018) and Willoughby, L. (2015). The file structure is described in the header of the data file.
# 2
Radosavljevic, Boris • Quinteros, Javier • Bertelmann, Roland • Hemmleb, Susanne • Elger, Kirsten • (et. al.)
Abstract: This publication contains tabular summaries of the data management survey carried out at the Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, as well as the diagrams of individual questions shown in Radosavljevic et al. (2019). The online survey was conducted from August 27 to September 27, 2019. The survey design leaned on similar surveys carried out at German universities and research institutions (e.g. Paul-Stüve et al., 2015; Simukovic et al., 2013) The survey queried aspects of the complete data life cycle - from the planning stage to reuse in 37 questions: 16 single response (SR); where only one answer was possible, and 20 multiple response (MR) where multiple answers could be selected, and one free text question. Research staff at all career levels was the target audience for the survey. Invitations to participate in the completely anonymous online survey were sent out over the general GFZ lists. The survey was carried out with the Questback EFS Survey platform. 226 attempts, out of 411, led to completed questionnaires corresponding to a 55% completion rate. Compared to the target audience at GFZ, the participation rate amounted to ca. 24%. However, less than 20% of employees classified as infrastructure support employees or bachelor’s and master’s students and student assistants completed the survey. Replies falling into these categories were grouped into “others” in the report as well as in the data presented here. Data summaries are given in two tab-separated tables corresponding to response counts or percentage for each question. These are grouped by department, role and employment length. Questions 5 and 34 were ranking questions and the corresponding responses in the percentages table represent arithmetic means of the replies for these questions – not percentages. The response counts for these question are presented in the “Counts” table. Free text replies are omitted from these results. In addition, the diagrams of individual questions are presented Radosavljevic et al. (2019) are also provided in png and pdf formats.
# 3
Eggert, Daniel • Sips, Mike • Dransch, Doris
Abstract: gms-vis is a web-based implementation of our visual-analytics approach for assessing remote-sensing data. It is implemented based on the GWT framework. Once deployed through a webserver it acts as the user interface for the GeoMultiSens (GMS) platform. Within the interface users can intuitively define spatial, temporal as well as quality constraints, for remote sensing scenes. A heatmap enables the user to assess the spatial distribution of selected scenes, while a time histogram allows the user to assess their temporal distribution. Finally, users can specify a workflow which will be executed by the GeoMultiSens platform. Though gms-vis is part of the GeoMultiSens platform, it is relatively self-contained and can be attached to different analysis frameworks and platforms with reasonable effort.
# 4
Eggert, Daniel • Sips, Mike • Dransch, Doris
Abstract: Gms-index-mediator is a standalone index for spatio-temporal data acting as a mediator between an application and a database. Even modern databases need several minutes to execute a spatio-temporal query to huge tables containing several million entries. Our index-mediator speeds the execution of such queries up by several magnitues, resulting in response times around 100ms. This version is tailored towards the GeoMultiSens database, but can be adapted to work with custom table layouts with reasonable effort.
# 5
Brunke, Heinz-Peter
Abstract: This data publication includes a matlab software package as described in Brunke (2017). In addition to the Matlab software, we provide three test dataset from the Niemegk magnetic observatories (NGK). We present a numerical method, allowing for the evaluation of an arbitrary number (minimum 5 as there are 5 independent parameters) of telescope orientations. The traditional measuring schema uses a fixed number of eight orientations (Jankowski et al, 1996). Our method provides D, I and Z base values and calculated uncertitudes of them. A general approach has significant advantages. Additional measurements may by seamlessly incorporate for higher accuracy. Individual erroneous readings are identified and can be discarded without invalidating the entire data set, a-priory information can be incorporated. We expect the general method to ease requirements also for automated DI-flux measurements. The method can reveal certain properties of the DI-theodolite, which are not captured by the conventional method. Based on the alternative evaluation method, a new faster and less error prone measuring schema is presented. It avoids the need to calculate the magnetic meridian prior to the inclination measurements. Measurements in the vicinity of the magnetic equator become possible with theodolites without zenith ocular.
# 6
Meeßen, Christian
Abstract: This code is a python implementation of the p- and s-wave velocity to density conversion approach after Goes et al. (2000). The implementation has been optimised for regular 3D grids using lookup tables instead of Newton iterations. Goes et al. (2000) regard the expansion coefficient as temperature dependent using the relation by Saxena and Shen (1992). In `Conversion.py`, the user can additionally choose between a constant expansion coefficient or a pressure- and temperature dependent coefficient that was derived from Hacker and Abers (2004).For detailed information on the physics behind the approach have a look at the original paper by Goes et al. (2000). Up-to-date contact information are given on the author's github profile https://github.com/cmeessen.
# 7
Ullah, Shahid • Abdrakhmatov, Kanat • Sadykova, Alla • Ibragimov, Roman • Ishuk, Anatoly • (et. al.)
Abstract: Area Source model for Central AsiaThe area sources for Central Asia within the EMCA model are defined by mainly considering the pattern of crustal seismicity down to 50 km depth. Although tectonic and geological information, such as the position and strike distribution of known faults, have also been taken into account when available. Large area sources (see, for example source_id 1, 2, 5, 45 and 52, source ids are identified by parameter “source_id” in the related shapefile) are defined where the seismicity is scarce and there are no tectonic or geological features that would justify a further subdivision. Smaller area sources (e.g., source_id values 36 and 53) have been designed where the seismicity can be assigned to known fault zones. In order to obtain a robust estimation of the necessary parameters for PSHA derived by the statistical analysis of the seismicity, due to the scarcity of data in some of the areas covered by the model, super zones are introduced. These super zones are defined by combining area sources based on similarities in their tectonic regime, and taking into account local expert’s judgments. The super zones are used to estimate: (1) the completeness time of the earthquake catalogue, (2) the depth distribution of seismicity, (3) the tectonic regime through focal mechanisms analysis, (4) the maximum magnitude and (5) the b values via the GR relationship.The earthquake catalogue for focal mechanism is extracted from the Harvard Global Centroid Moment Tensor Catalog (Ekström and Nettles, 2013). For the focal mechanism classification, the Boore et al. (1997) convention is used. This means that an event is considered to be strike-slip if the absolute value of the rake angle is <=30 or >=150 degrees, normal if the rake angle is <-30 or >-150 and reverse (thrust) if the rake angle is >30 or <150 degrees. The distribution of source mechanisms and their weights are estimated for the super zones. For area sources, the maximum magnitude is usually taken from the historical seismicity, but due to some uncertainties in the magnitudes of the largest events, the opinions of the local experts are also included in assigning the maximum magnitude to each super zone. Super zones 2 and 3, which belongs to stable regions, are each assigned a maximum magnitude of 6, after Mooney et al. (2012), which concludes after analyses and observation of modern datasets that at least an event of magnitude 6 can occur anywhere in the world. For hazard calculations, each area source is assigned the maximum magnitude of their respective super zone.For processing the GR parameters (a and b values) for the area sources, the completeness analysis results estimated for the super zones are assigned to the respective smaller area sources. If the individual area source has at least 20 events, the GR parameters are then estimated for the area source. Otherwise, the b value is adopted from the respective super zone to which the smaller area source belongs, and the a value is estimated based on the Weichert (1980) method. This ensures the stability in the b value as well as the variation of activity rate for different sources. The hypocentral depth distribution is estimated from the seismicity inside each super zone. The depth distribution is considered for maximum up to three values. Based on the number of events, the weights are assigned to each distribution. These depth distributions, along with corresponding weights, are further assigned to the area sources within the same super zones.
Distribution file: "EMCA_seismozonesv1.0_shp.zip"Version: v1.0Release date: 2015-07-30Format: ESRI ShapefileGeometry type: polygonsNumber of features: 63Spatial Reference System: +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs Distribution file: "EMCA_seismozonesv1.0_nrml.zip"Version: v1.0Release date: 2015-07-30Format: NRML (XML) Format compatible with the GEM OpenQuake platform (http://www.globalquakemodel.org/openquake/about/platform/) Feature attributes:src_id : Id of the seismic sourcesrc_name : Name of the seismic sourcetect_reg: Tectonic regime of the seismic sourceupp_seismo : Upper level of the the seismogenic depth (km)low_seismo : Lower level of the seismogenic depth (km)mag_scal_r: Magnitude scaling relationshiprup_asp_ra: Rupture aspect ratiomfd_type : Magnitude frequency distribution typemin_mag: Minimum magnitude of the magnitude frequency relationshipmax_mag: Maximum magnitude of the magnitude frequency relationshipa_value: a value of the magnitude frequency relationshipb_balue : b value of the magnitude frequency relationshipnum_npd: number of nodal plane distributionweight_1 : weight of 1st nodal plane distributionstrike_1: Strike of the seismic source (degrees)rake_1: rake of the seismic source (degrees)dip_1: dip of the seismic source (degrees)num_hdd: number of hypocentral depth distributionhdd_d_1: Depth of 1st hypocentral depth distribution (km)hdd_w_1: Weight of 1st hypocentral depth distribution
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