scholarly journals New core and downhole geophysical data sets from the Bells Corners Borehole Calibration Facility Ottawa, Ontario

2021 ◽  
Author(s):  
H L Crow ◽  
K D Brewer ◽  
T J Cartwright ◽  
S Gaines ◽  
D Heagle ◽  
...  
Keyword(s):  
Geophysical Data ◽  
Data Sets ◽  
Calibration Facility

scholarly journals A Review of Geophysical Modeling Based on Particle Swarm Optimization

2021 ◽  
Author(s):  
Francesca Pace ◽  
Alessandro Santilano ◽  
Alberto Godio
Keyword(s):  
Particle Swarm Optimization ◽  
Inverse Modeling ◽  
Critical Evaluation ◽  
Particle Swarm ◽  
Geophysical Data ◽  
Magnetic Data ◽  
Data Sets ◽  
Swarm Optimization ◽  
Geophysical Modeling ◽  
Original Works

AbstractThis paper reviews the application of the algorithm particle swarm optimization (PSO) to perform stochastic inverse modeling of geophysical data. The main features of PSO are summarized, and the most important contributions in several geophysical fields are analyzed. The aim is to indicate the fundamental steps of the evolution of PSO methodologies that have been adopted to model the Earth’s subsurface and then to undertake a critical evaluation of their benefits and limitations. Original works have been selected from the existing geophysical literature to illustrate successful PSO applied to the interpretation of electromagnetic (magnetotelluric and time-domain) data, gravimetric and magnetic data, self-potential, direct current and seismic data. These case studies are critically described and compared. In addition, joint optimization of multiple geophysical data sets by means of multi-objective PSO is presented to highlight the advantage of using a single solver that deploys Pareto optimality to handle different data sets without conflicting solutions. Finally, we propose best practices for the implementation of a customized algorithm from scratch to perform stochastic inverse modeling of any kind of geophysical data sets for the benefit of PSO practitioners or inexperienced researchers.

scholarly journals Dissecting a Zombie: Shallow Volcanic Structure Revealed by Multiple Geophysical Data Sets at Uturuncu Volcano, Bolivia

2021 ◽  
Author(s):  
Patricia MacQueen ◽  
Joachim Gottsmann ◽  
Matthew Pritchard ◽  
Nicola Young ◽  
Faustino Ticona J. ◽  
...  
Keyword(s):  
Geophysical Data ◽  
Data Sets ◽  
Volcanic Structure

EPOS-Norway Portal

2021 ◽  
Author(s):  
Jan Michalek ◽  
Kuvvet Atakan ◽  
Christian Rønnevik ◽  
Helga Indrøy ◽  
Lars Ottemøller ◽  
...  
Keyword(s):  
Web Services ◽  
Visual Analysis ◽  
Earth Science ◽  
National Research Council ◽  
Geophysical Data ◽  
Multidimensional Data ◽  
Data Sets ◽  
Complex Data ◽  
Submarine Landslides ◽  
Data Repositories

<p>The European Plate Observing System (EPOS) is a European project about building a pan-European infrastructure for accessing solid Earth science data, governed now by EPOS ERIC (European Research Infrastructure Consortium). The EPOS-Norway project (EPOS-N; RCN-Infrastructure Programme - Project no. 245763) is a Norwegian project funded by National Research Council. The aim of the Norwegian EPOS e‑infrastructure is to integrate data from the seismological and geodetic networks, as well as the data from the geological and geophysical data repositories. Among the six EPOS-N project partners, four institutions are providing data – University of Bergen (UIB), - Norwegian Mapping Authority (NMA), Geological Survey of Norway (NGU) and NORSAR.</p><p>In this contribution, we present the EPOS-Norway Portal as an online, open access, interactive tool, allowing visual analysis of multidimensional data. It supports maps and 2D plots with linked visualizations. Currently access is provided to more than 300 datasets (18 web services, 288 map layers and 14 static datasets) from four subdomains of Earth science in Norway. New datasets are planned to be integrated in the future. EPOS-N Portal can access remote datasets via web services like FDSNWS for seismological data and OGC services for geological and geophysical data (e.g. WMS). Standalone datasets are available through preloaded data files. Users can also simply add another WMS server or upload their own dataset for visualization and comparison with other datasets. This portal provides unique way (first of its kind in Norway) for exploration of various geoscientific datasets in one common interface. One of the key aspects is quick simultaneous visual inspection of data from various disciplines and test of scientific or geohazard related hypothesis. One of such examples can be spatio-temporal correlation of earthquakes (1980 until now) with existing critical infrastructures (e.g. pipelines), geological structures, submarine landslides or unstable slopes.  </p><p>The EPOS-N Portal is implemented by adapting Enlighten-web, a server-client program developed by NORCE. Enlighten-web facilitates interactive visual analysis of large multidimensional data sets, and supports interactive mapping of millions of points. The Enlighten-web client runs inside a web browser. An important element in the Enlighten-web functionality is brushing and linking, which is useful for exploring complex data sets to discover correlations and interesting properties hidden in the data. The views are linked to each other, so that highlighting a subset in one view automatically leads to the corresponding subsets being highlighted in all other linked views.</p>

scholarly journals Constrained optimization framework for joint inversion of geophysical data sets

2013 ◽  
Vol 195 (3) ◽  
pp. 1745-1762 ◽  
Author(s):  
A. Sosa ◽  
A. A. Velasco ◽  
L. Velazquez ◽  
M. Argaez ◽  
R. Romero
Keyword(s):  
Constrained Optimization ◽  
Joint Inversion ◽  
Geophysical Data ◽  
Data Sets ◽  
Optimization Framework

scholarly journals Geophysical characterisation of two segments of the Møre-Trøndelag Fault Complex, Mid-Norway

2011 ◽  
Vol 3 (1) ◽  
pp. 159-186
Author(s):  
A. Nasuti ◽  
C. Pascal ◽  
J. Ebbing ◽  
J. F. Tønnesen
Keyword(s):  
Tectonic Evolution ◽  
Deep Structure ◽  
Normal Fault ◽  
Geophysical Data ◽  
Data Sets ◽  
Normal Faulting ◽  
The South ◽  
The Past ◽  
Magnetic Resistivity ◽  
Wide Zone

Abstract. The Møre-Trøndelag Fault Complex (MTFC) has controlled the tectonic evolution of Mid-Norway and its shelf for the past 400 Myr through repeated reactivations during Paleozoic, Mesozoic and perhaps Cenozoic times, the very last phase of reactivation involving normal to oblique slip faulting. Despite its pronounced signature in the landscape, its deep structure has remained unresolved until now. We focused on two specific segments of the MTFC (i.e. the so-called "Tjellefonna" and "Bæverdalen" faults) and acquired multiple geophysical data sets (i.e. gravity, magnetic, resistivity and shallow refraction profiles). A 100–200 m wide zone of gouge and/or brecciated bedrock dipping steeply to the south is interpreted as being the "Tjellefonna Fault" stricto sensu. The fault appears to be flanked by two additional but minor damage zones. A secondary normal fault also steeply dipping to the south but involving indurated breccias was detected ~1 km farther north. The "Bæverdalen Fault" is interpreted as a ~700 m wide and highly deformed zone involving fault gouge, breccias and lenses of intact bedrock, as such it is probably the most important fault segment in the studied area and accommodated most of the strain during presumably late Jurassic normal faulting. Our geophysical data are indicative of a "Bæverdalen Fault" dipping steeply towards the south, in agreement with the average orientation of the local tectonic grain. Our findings suggest that the influence of Mesozoic normal faulting along the MTFC on landscape development is more complex than previously anticipated.

Rapid multi-scale analysis of near-surface geophysical anomaly maps: Application to an archaeo-geophysical data set

Geophysics ◽  
2020 ◽  
pp. 1-41 ◽  
Author(s):  
Jens Tronicke ◽  
Niklas Allroggen ◽  
Felix Biermann ◽  
Florian Fanselow ◽  
Julien Guillemoteau ◽  
...  
Keyword(s):  
Random Noise ◽  
Geophysical Data ◽  
Magnetic Data ◽  
Engineering Practice ◽  
Data Sets ◽  
Stripe Pattern ◽  
Data Set ◽  
Near Surface ◽  
Multi Scale ◽  
Topographic Data

In near-surface geophysics, ground-based mapping surveys are routinely employed in a variety of applications including those from archaeology, civil engineering, hydrology, and soil science. The resulting geophysical anomaly maps of, for example, magnetic or electrical parameters are usually interpreted to laterally delineate subsurface structures such as those related to the remains of past human activities, subsurface utilities and other installations, hydrological properties, or different soil types. To ease the interpretation of such data sets, we propose a multi-scale processing, analysis, and visualization strategy. Our approach relies on a discrete redundant wavelet transform (RWT) implemented using cubic-spline filters and the à trous algorithm, which allows to efficiently compute a multi-scale decomposition of 2D data using a series of 1D convolutions. The basic idea of the approach is presented using a synthetic test image, while our archaeo-geophysical case study from North-East Germany demonstrates its potential to analyze and process rather typical geophysical anomaly maps including magnetic and topographic data. Our vertical-gradient magnetic data show amplitude variations over several orders of magnitude, complex anomaly patterns at various spatial scales, and typical noise patterns, while our topographic data show a distinct hill structure superimposed by a microtopographic stripe pattern and random noise. Our results demonstrate that the RWT approach is capable to successfully separate these components and that selected wavelet planes can be scaled and combined so that the reconstructed images allow for a detailed, multi-scale structural interpretation also using integrated visualizations of magnetic and topographic data. Because our analysis approach is straightforward to implement without laborious parameter testing and tuning, computationally efficient, and easily adaptable to other geophysical data sets, we believe that it can help to rapidly analyze and interpret different geophysical mapping data collected to address a variety of near-surface applications from engineering practice and research.

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