@article{SchmelzbachTronickeDietrich2011, author = {Schmelzbach, C. and Tronicke, Jens and Dietrich, P.}, title = {Three-dimensional hydrostratigraphic models from ground-penetrating radar and direct-push data}, series = {Journal of hydrology}, volume = {398}, journal = {Journal of hydrology}, number = {3-4}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0022-1694}, doi = {10.1016/j.jhydrol.2010.12.023}, pages = {235 -- 245}, year = {2011}, abstract = {Three-dimensional models of hydraulic conductivity and porosity are essential to understand and simulate groundwater flow in heterogeneous geological environments. However, considering the inherent limitations of traditional hydrogeological field methods in terms of resolution, alternative field approaches are needed to establish such 3-D models with sufficient accuracy. In this study, we developed a workflow combining 3-D structural information extracted from ground penetrating radar (GPR) images with 1-D in situ physical-property estimates from direct-push (DP) logging to construct a 3-D hydrostratigraphic model. To illustrate this workflow, we collected an similar to 70 m x 90 m 100 MHz 3-D GPR data set over a shallow sedimentary aquifer system resolving six different GPR facies down to similar to 15 m depth. DP logs of the relative dielectric permittivity, the relative hydraulic conductivity, the cone resistance, the sleeve friction and the pore pressure provided crucial data (1) to establish a GPR velocity model for 3-D depth migration and to check the time-to-depth conversion of the GPR data, and (2) to construct a 3-D hydrostratigraphic model. This model was built by assigning porosity values, which were computed from the DP relative dielectric permittivity logs, and DP relative hydraulic conductivity estimates to the identified GPR facies. We conclude that the integration of 3-D GPR structural images and 1-D DP logs of target physical parameters provides an efficient way for detailed 3-D subsurface characterization as needed, for example, for groundwater flow simulations.}, language = {en} } @article{BoenigerTronicke2012, author = {Boeniger, Urs and Tronicke, Jens}, title = {High-resolution GPR data analysis using extended tree-based pursuit}, series = {Journal of applied geophysics}, volume = {78}, journal = {Journal of applied geophysics}, number = {5}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0926-9851}, doi = {10.1016/j.jappgeo.2011.04.006}, pages = {44 -- 51}, year = {2012}, abstract = {Decomposition of geophysical signals (e.g., seismic and ground-penetrating radar data) into the time-frequency domain can provide valuable information for advanced interpretation (e.g., tuning effects) and processing (e.g., inverse Q-filtering). The quality of these subsequent processing steps is strongly related to the resolution of the selected time-frequency representation (TFR). In this study, we introduce a high-resolution spectral decomposition approach representing an extension of the recently proposed Tree-Based Pursuit (TBP) method. TBP significantly reduces the computational cost compared to the well known Matching Pursuit (MP) technique by introducing a tree structure prior to the actual matching procedure. Following the original implementation of TBP, we additionally incorporate waveforms commonly used in geophysical data processing and present an alternative approach to take phase shifts into account. Application of the proposed method to synthetic data and comparison of the results with other typically used decomposition approaches, illustrate the ability of our approach to provide decomposition results highly localized in both time and frequency. Applying our procedure to field GPR data illustrates its applicability to real data and provides examples for potential applications such as analyzing thin-bed responses and modulating the data frequency content.}, language = {en} } @article{AllroggenBoothBakeretal.2019, author = {Allroggen, Niklas Robin and Booth, Adam D. and Baker, Sandra E. and Ellwood, Stephen A. and Tronicke, Jens}, title = {High-resolution imaging and monitoring of animal tunnels using 3D ground-penetrating radar}, series = {Near surface geophysics}, volume = {17}, journal = {Near surface geophysics}, number = {3}, publisher = {Wiley}, address = {Hoboken}, issn = {1569-4445}, doi = {10.1002/nsg.12039}, pages = {291 -- 298}, year = {2019}, abstract = {Ground-penetrating radar is widely used to provide highly resolved images of subsurface sedimentary structures, with implications for processes active in the vadose zone. Frequently overlooked among these structures are tunnels excavated by fossorial animals (e.g., moles). We present two repeated ground-penetrating radar surveys performed a year apart in 2016 and 2017. Careful three-dimensional data processing reveals, in each data set, a pattern of elongated structures that are interpreted as a subsurface mole tunnel network. Our data demonstrate the ability of three-dimensional ground-penetrating radar imaging to non-invasively delineate the small animal tunnels (similar to 5 cm diameter) at a higher spatial and geolocation resolution than has previously been achieved. In turn, this makes repeated surveys and, therefore, long-term monitoring possible. Our results offer valuable insight into the understanding of the near-surface and showcase a potential new application for a geophysical method as well as a non-invasive method of ecological surveying.}, language = {en} } @article{KoyanTronicke2020, author = {Koyan, Philipp and Tronicke, Jens}, title = {3D modeling of ground-penetrating radar data across a realistic sedimentary model}, series = {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}, volume = {137}, journal = {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}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0098-3004}, doi = {10.1016/j.cageo.2020.104422}, pages = {9}, year = {2020}, abstract = {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.}, language = {en} }