TY - JOUR A1 - Arboleda-Zapata, Mauricio A1 - Guillemoteau, Julien A1 - Tronicke, Jens T1 - A comprehensive workflow to analyze ensembles of globally inverted 2D electrical resistivity models JF - Journal of applied geophysics N2 - Electrical resistivity tomography (ERT) aims at imaging the subsurface resistivity distribution and provides valuable information for different geological, engineering, and hydrological applications. To obtain a subsurface resistivity model from measured apparent resistivities, stochastic or deterministic inversion procedures may be employed. Typically, the inversion of ERT data results in non-unique solutions; i.e., an ensemble of different models explains the measured data equally well. In this study, we perform inference analysis of model ensembles generated using a well-established global inversion approach to assess uncertainties related to the nonuniqueness of the inverse problem. Our interpretation strategy starts by establishing model selection criteria based on different statistical descriptors calculated from the data residuals. Then, we perform cluster analysis considering the inverted resistivity models and the corresponding data residuals. Finally, we evaluate model uncertainties and residual distributions for each cluster. To illustrate the potential of our approach, we use a particle swarm optimization (PSO) algorithm to obtain an ensemble of 2D layer-based resistivity models from a synthetic data example and a field data set collected in Loon-Plage, France. Our strategy performs well for both synthetic and field data and allows us to extract different plausible model scenarios with their associated uncertainties and data residual distributions. Although we demonstrate our workflow using 2D ERT data and a PSObased inversion approach, the proposed strategy is general and can be adapted to analyze model ensembles generated from other kinds of geophysical data and using different global inversion approaches. KW - Near-surface geophysics KW - Electrical resistivity tomography KW - Non-uniqueness KW - Global inversion KW - Particle swarm optimization KW - Ensemble KW - analysis Y1 - 2021 U6 - https://doi.org/10.1016/j.jappgeo.2021.104512 SN - 0926-9851 SN - 1879-1859 VL - 196 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Arboleda-Zapata, Mauricio A1 - Angelopoulos, Michael A1 - Overduin, Pier Paul A1 - Grosse, Guido A1 - Jones, Benjamin M. A1 - Tronicke, Jens T1 - Exploring the capabilities of electrical resistivity tomography to study subsea permafrost JF - The Cryosphere N2 - Sea level rise and coastal erosion have inundated large areas of Arctic permafrost. Submergence by warm and saline waters increases the rate of inundated permafrost thaw compared to sub-aerial thawing on land. Studying the contact between the unfrozen and frozen sediments below the seabed, also known as the ice-bearing permafrost table (IBPT), provides valuable information to understand the evolution of sub-aquatic permafrost, which is key to improving and understanding coastal erosion prediction models and potential greenhouse gas emissions. In this study, we use data from 2D electrical resistivity tomography (ERT) collected in the nearshore coastal zone of two Arctic regions that differ in their environmental conditions (e.g., seawater depth and resistivity) to image and study the subsea permafrost. The inversion of 2D ERT data sets is commonly performed using deterministic approaches that favor smoothed solutions, which are typically interpreted using a user-specified resistivity threshold to identify the IBPT position. In contrast, to target the IBPT position directly during inversion, we use a layer-based model parameterization and a global optimization approach to invert our ERT data. This approach results in ensembles of layered 2D model solutions, which we use to identify the IBPT and estimate the resistivity of the unfrozen and frozen sediments, including estimates of uncertainties. Additionally, we globally invert 1D synthetic resistivity data and perform sensitivity analyses to study, in a simpler way, the correlations and influences of our model parameters. The set of methods provided in this study may help to further exploit ERT data collected in such permafrost environments as well as for the design of future field experiments. Y1 - 2022 U6 - https://doi.org/10.5194/tc-16-4423-2022 SN - 1994-0424 VL - 16 SP - 4423 EP - 4445 PB - Copernicus CY - Katlenburg-Lindau ER - TY - GEN A1 - Arboleda-Zapata, Mauricio A1 - Angelopoulos, Michael A1 - Overduin, Pier Paul A1 - Grosse, Guido A1 - Jones, Benjamin M. A1 - Tronicke, Jens T1 - Exploring the capabilities of electrical resistivity tomography to study subsea permafrost T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Sea level rise and coastal erosion have inundated large areas of Arctic permafrost. Submergence by warm and saline waters increases the rate of inundated permafrost thaw compared to sub-aerial thawing on land. Studying the contact between the unfrozen and frozen sediments below the seabed, also known as the ice-bearing permafrost table (IBPT), provides valuable information to understand the evolution of sub-aquatic permafrost, which is key to improving and understanding coastal erosion prediction models and potential greenhouse gas emissions. In this study, we use data from 2D electrical resistivity tomography (ERT) collected in the nearshore coastal zone of two Arctic regions that differ in their environmental conditions (e.g., seawater depth and resistivity) to image and study the subsea permafrost. The inversion of 2D ERT data sets is commonly performed using deterministic approaches that favor smoothed solutions, which are typically interpreted using a user-specified resistivity threshold to identify the IBPT position. In contrast, to target the IBPT position directly during inversion, we use a layer-based model parameterization and a global optimization approach to invert our ERT data. This approach results in ensembles of layered 2D model solutions, which we use to identify the IBPT and estimate the resistivity of the unfrozen and frozen sediments, including estimates of uncertainties. Additionally, we globally invert 1D synthetic resistivity data and perform sensitivity analyses to study, in a simpler way, the correlations and influences of our model parameters. The set of methods provided in this study may help to further exploit ERT data collected in such permafrost environments as well as for the design of future field experiments. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1285 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-571234 SN - 1866-8372 IS - 1285 SP - 4423 EP - 4445 ER - TY - JOUR A1 - Klose, Tim A1 - Guillemoteau, Julien A1 - Vignoli, Giulio A1 - Tronicke, Jens T1 - Laterally constrained inversion (LCI) of multi-configuration EMI data with tunable sharpness JF - Journal of applied geophysics N2 - Frequency-domain electromagnetic (FDEM) data are commonly inverted to characterize subsurface geoelectrical properties using smoothness constraints in 1D inversion schemes assuming a layered medium. Smoothness constraints are suitable for imaging gradual transitions of subsurface geoelectrical properties caused, for example, by varying sand, clay, or fluid content. However, such inversion approaches are limited in characterizing sharp interfaces. Alternative regularizations based on the minimum gradient support (MGS) stabilizers can, instead, be used to promote results with different levels of smoothness/sharpness selected by simply acting on the so-called focusing parameter. The MGS regularization has been implemented for different kinds of geophysical data inversion strategies. However, concerning FDEM data, the MGS regularization has only been implemented for vertically constrained inversion (VCI) approaches but not for laterally constrained inversion (LCI) approaches. We present a novel LCI approach for FDEM data using the MGS regularization for the vertical and lateral direction. Using synthetic and field data examples, we demonstrate that our approach can efficiently and automatically provide a set of model solutions characterized by different levels of sharpness and variable lateral consistencies. In terms of data misfit, the obtained set of solutions contains equivalent models allowing us also to investigate the non-uniqueness of FDEM data inversion. KW - frequency-domain electromagnetics KW - laterally constrained inversion KW - minimum gradient support regularization KW - peat characterization Y1 - 2022 U6 - https://doi.org/10.1016/j.jappgeo.2021.104519 SN - 0926-9851 VL - 196 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Koyan, Philipp A1 - Tronicke, Jens A1 - Allroggen, Niklas T1 - 3D ground-penetrating radar attributes to generate classified facies models BT - a case study from a dune island JF - Geophysics N2 - Ground-penetrating radar (GPR) is a standard geophysical technique used to image near-surface structures in sedimentary environments. In such environments, GPR data acquisition and processing are increasingly following 3D strategies. However, the processed GPR data volumes are typically still interpreted using selected 2D slices and manual concepts such as GPR facies analyses. In seismic volume interpretation, the application of (semi-)automated and reproducible approaches such as 3D attribute analyses as well as the production of attribute-based facies models are common practices today. In contrast, the field of 3D GPR attribute analyses and corresponding facies models is largely untapped. We have developed and applied a workflow to produce 3D attribute-based GPR facies models comprising the dominant sedimentary reflection patterns in a GPR volume, which images complex sandy structures on the dune island of Spiekeroog (Northern Germany). After presenting our field site and details regarding our data acquisition and processing, we calculate and filter 3D texture attributes to generate a database comprising the dominant texture features of our GPR data. Then, we perform a dimensionality reduction of this database to obtain meta texture attributes, which we analyze and integrate using composite imaging and (also considering additional geometric information) fuzzy c-means cluster analysis resulting in a classified GPR facies model. Considering our facies model and a corresponding GPR facies chart, we interpret our GPR data set in terms of near-surface sedimentary units, the corresponding depositional environments, and the recent formation history at our field site. Thus, we demonstrate the potential of our workflow, which represents a novel and clear strategy to perform a more objective and consistent interpretation of 3D GPR data collected across different sedimentary environments. KW - ground-penetrating radar KW - attributes KW - interpretation KW - sedimentology Y1 - 2021 U6 - https://doi.org/10.1190/GEO2021-0204.1 SN - 0016-8033 SN - 1942-2156 VL - 86 IS - 6 SP - B335 EP - B347 PB - Society of Exploration Geophysicists CY - Tulsa ER - TY - JOUR A1 - Koyan, Philipp A1 - Tronicke, Jens T1 - 3D modeling of ground-penetrating radar data across a realistic sedimentary model JF - Computers & geosciences : an international journal devoted to the publication of papers on all aspects of geocomputation and to the distribution of computer programs and test data sets ; an official journal of the International Association for Mathematical Geology N2 - Ground-penetrating radar (GPR) is an established geophysical tool to explore a wide range of near-surface environments. Today, the use of synthetic GPR data is largely limited to 2D because 3D modeling is computationally more expensive. In fact, only recent developments of modeling tools and powerful hardware allow for a time-efficient computation of extensive 3D data sets. Thus, 3D subsurface models and resulting GPR data sets, which are of great interest to develop and evaluate novel approaches in data analysis and interpretation, have not been made publicly available up to now.
We use a published hydrofacies data set of an aquifer-analog study within fluvio-glacial deposits to infer a realistic 3D porosity model showing heterogeneities at multiple spatial scales. Assuming fresh-water saturated sediments, we generate synthetic 3D GPR data across this model using novel GPU-acceleration included in the open-source software gprMax. We present a numerical approach to examine 3D wave-propagation effects in modeled GPR data. Using the results of this examination study, we conduct a spatial model decomposition to enable a computationally efficient 3D simulation of a typical GPR reflection data set across the entire model surface. We process the resulting GPR data set using a standard 3D structural imaging sequence and compare the results to selected input data to demonstrate the feasibility and potential of the presented modeling studies. We conclude on conceivable applications of our 3D GPR reflection data set and the underlying porosity model, which are both publicly available and, thus, can support future methodological developments in GPR and other near-surface geophysical techniques. KW - Applied geophysics KW - Ground-penetrating radar KW - 3D modeling Y1 - 2020 U6 - https://doi.org/10.1016/j.cageo.2020.104422 SN - 0098-3004 SN - 1873-7803 VL - 137 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Allroggen, Niklas A1 - Beiter, Daniel A1 - Tronicke, Jens T1 - Ground-penetrating radar monitoring of fast subsurface processes JF - Geophysics N2 - Earth and environmental sciences rely on detailed information about subsurface processes. Whereas geophysical techniques typically provide highly resolved spatial images, monitoring subsurface processes is often associated with enormous effort and, therefore, is usually limited to point information in time or space. Thus, the development of spatial and temporal continuous field monitoring methods is a major challenge for the understanding of subsurface processes. We have developed a novel method for ground-penetrating-radar (GPR) reflection monitoring of subsurface flow processes under unsaturated conditions and applied it to a hydrological infiltration experiment performed across a periglacial slope deposit in northwest Luxembourg. Our approach relies on a spatial and temporal quasicontinuous data recording and processing, followed by an attribute analysis based on analyzing differences between individual time steps. The results demonstrate the ability of time-lapse GPR monitoring to visualize the spatial and temporal dynamics of preferential flow processes with a spatial resolution in the order of a few decimeters and temporal resolution in the order of a few minutes. We observe excellent agreement with water table information originating from different boreholes. This demonstrates the potential of surface-based GPR reflection monitoring to observe the spatiotemporal dynamics of water movements in the subsurface. It provides valuable, and so far not accessible, information for example in the field of hydrology and pedology that allows studying the actual subsurface processes rather than deducing them from point information. Y1 - 2020 U6 - https://doi.org/10.1190/GEO2019-0737.1 SN - 0016-8033 SN - 1942-2156 VL - 85 IS - 3 SP - A19 EP - A23 PB - Society of Exploration Geophysicists CY - Tulsa ER - TY - JOUR A1 - Tronicke, Jens A1 - Allroggen, Niklas A1 - Biermann, Felix A1 - Fanselow, Florian A1 - Guillemoteau, Julien A1 - Krauskopf, Christof A1 - Lück, Erika T1 - Rapid multiscale analysis of near-surface geophysical anomaly maps BT - application to an archaeogeophysical data set JF - Geophysics N2 - In near- surface geophysics, ground-based mapping surveys are routinely used 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 have developed a multiscale processing, analysis, and visualization strategy. Our approach relies on a discrete redundant wavelet transform (RWT) implemented using cubic-spline filters and the a trous algorithm, which allows to efficiently compute a multiscale decomposition of 2D data using a series of 1D convolutions. The basic idea of the approach is presented using a synthetic test image, whereas our archaeogeophysical case study from northeast 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, whereas 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, multiscale 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. KW - archaeology KW - case history KW - near surface KW - magnetics KW - decomposition Y1 - 2020 U6 - https://doi.org/10.1190/GEO2019-0564.1 SN - 0016-8033 SN - 1942-2156 VL - 85 IS - 4 SP - B109 EP - B118 PB - Society of Exploration Geophysicists CY - Tulsa, Okla. ER - TY - JOUR A1 - Angelopoulos, Michael A1 - Overduin, Pier Paul A1 - Westermann, Sebastian A1 - Tronicke, Jens A1 - Strauss, Jens A1 - Schirrmeister, Lutz A1 - Biskaborn, Boris A1 - Liebner, Susanne A1 - Maksimov, Georgii A1 - Grigoriev, Mikhail N. A1 - Grosse, Guido T1 - Thermokarst lake to lagoon transitions in Eastern Siberia BT - do submerged taliks refreeze? JF - Journal of geophysical research : Earth surface N2 - As the Arctic coast erodes, it drains thermokarst lakes, transforming them into lagoons, and, eventually, integrates them into subsea permafrost. Lagoons represent the first stage of a thermokarst lake transition to a marine setting and possibly more saline and colder upper boundary conditions. In this research, borehole data, electrical resistivity surveying, and modeling of heat and salt diffusion were carried out at Polar Fox Lagoon on the Bykovsky Peninsula, Siberia. Polar Fox Lagoon is a seasonally isolated water body connected to Tiksi Bay through a channel, leading to hypersaline waters under the ice cover. The boreholes in the center of the lagoon revealed floating ice and a saline cryotic bed underlain by a saline cryotic talik, a thin ice-bearing permafrost layer, and unfrozen ground. The bathymetry showed that most of the lagoon had bedfast ice in spring. In bedfast ice areas, the electrical resistivity profiles suggested that an unfrozen saline layer was underlain by a thick layer of refrozen talik. The modeling showed that thermokarst lake taliks can refreeze when submerged in saltwater with mean annual bottom water temperatures below or slightly above 0 degrees C. This occurs, because the top-down chemical degradation of newly formed ice-bearing permafrost is slower than the refreezing of the talik. Hence, lagoons may precondition taliks with a layer of ice-bearing permafrost before encroachment by the sea, and this frozen layer may act as a cap on gas migration out of the underlying talik. KW - thermokarst lake KW - talik KW - lagoon KW - subsea permafrost KW - salt diffusion KW - Siberia Y1 - 2020 U6 - https://doi.org/10.1029/2019JF005424 SN - 2169-9003 SN - 2169-9011 VL - 125 IS - 10 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Guillemoteau, Julien A1 - Simon, Francois-Xavier A1 - Hulin, Guillaume A1 - Dousteyssier, Bertrand A1 - Dacko, Marion A1 - Tronicke, Jens T1 - 3-D imaging of subsurface magnetic permeability/susceptibility with portable frequency domain electromagnetic sensors for near surface exploration JF - Geophysical journal international N2 - The in-phase response collected by portable loop-loop electromagnetic induction (EMI) sensors operating at low and moderate induction numbers (<= 1) is typically used for sensing the magnetic permeability (or susceptibility) of the subsurface. This is due to the fact that the in-phase response contains a small induction fraction and a preponderant induced magnetization fraction. The magnetization fraction follows the magneto-static equations similarly to the magnetic method but with an active magnetic source. The use of an active source offers the possibility to collect data with several loop-loop configurations, which illuminate the subsurface with different sensitivity patterns. Such multiconfiguration soundings thereby allows the imaging of subsurface magnetic permeability/susceptibility variations through an inversion procedure. This method is not affected by the remnant magnetization and theoretically overcomes the classical depth ambiguity generally encountered with passive geomagnetic data. To invert multiconfiguration in-phase data sets, we propose a novel methodology based on a full-grid 3-D multichannel deconvolution (MCD) procedure. This method allows us to invert large data sets (e.g. consisting of more than a hundred thousand of data points) for a dense voxel-based 3-D model of magnetic susceptibility subject to smoothness constraints. In this study, we first present and discuss synthetic examples of our imaging procedure, which aim at simulating realistic conditions. Finally, we demonstrate the applicability of our method to field data collected across an archaeological site in Auvergne (France) to image the foundations of a Gallo-Roman villa built with basalt rock material. Our synthetic and field data examples demonstrate the potential of the proposed inversion procedure offering new and complementary ways to interpret data sets collected with modern EMI instruments. KW - Magnetic properties KW - Controlled source electromagnetics (CSEM) KW - Electromagnetic theory KW - Environmental magnetism KW - Inverse theory Y1 - 2019 U6 - https://doi.org/10.1093/gji/ggz382 SN - 0956-540X SN - 1365-246X VL - 219 IS - 3 SP - 1773 EP - 1785 PB - Oxford Univ. Press CY - Oxford ER -