Refine
Year of publication
Document Type
- Article (51)
- Postprint (3)
- Conference Proceeding (1)
- Other (1)
Language
- English (56) (remove)
Keywords
- Ground-penetrating radar (4)
- Ground penetrating radar (3)
- Controlled source electromagnetics (CSEM) (2)
- Electromagnetics (2)
- Global inversion (2)
- Inverse theory (2)
- Inversion (2)
- ground-penetrating radar (2)
- preferential flow (2)
- tracer (2)
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.
The study deals with the identification and characterization of rapid subsurface flow structures through pedo- and geo-physical measurements and irrigation experiments at the point, plot and hillslope scale. Our investigation of flow-relevant structures and hydrological responses refers to the general interplay of form and function, respectively. To obtain a holistic picture of the subsurface, a large set of different laboratory, exploratory and experimental methods was used at the different scales. For exploration these methods included drilled soil core profiles, in situ measurements of infiltration capacity and saturated hydraulic conductivity, and laboratory analyses of soil water retention and saturated hydraulic conductivity. The irrigation experiments at the plot scale were monitored through a combination of dye tracer, salt tracer, soil moisture dynamics, and 3-D time-lapse ground penetrating radar (GPR) methods. At the hillslope scale the subsurface was explored by a 3-D GPR survey. A natural storm event and an irrigation experiment were monitored by a dense network of soil moisture observations and a cascade of 2-D time-lapse GPR "trenches". We show that the shift between activated and non-activated state of the flow paths is needed to distinguish structures from overall heterogeneity. Pedo-physical analyses of point-scale samples are the basis for sub-scale structure inference. At the plot and hillslope scale 3-D and 2-D time-lapse GPR applications are successfully employed as non-invasive means to image subsurface response patterns and to identify flow-relevant paths. Tracer recovery and soil water responses from irrigation experiments deliver a consistent estimate of response velocities. The combined observation of form and function under active conditions provides the means to localize and characterize the structures (this study) and the hydrological processes (companion study Angermann et al., 2017, this issue).
In many hydrological applications, ground-wave velocity measurements are increasingly used to map and monitor shallow soil water content. In this study, we propose an automated spectral velocity analysis method to determine the direct ground-wave (DGW) velocity from common midpoint (CMP) or multi-offset ground-penetrating radar (GPR) data. The method introduced in this paper is a variation of the well-known spectral velocity analysis for seismic and GPR reflection events where velocity spectra are computed using different coherency measures along hyperbolas following the normal moveout model. Here, the unnormalized cross-correlation is computed between waveforms across data gathers that are corrected with a linear moveout equation using a predefined range of velocities. Peaks in the resulting velocity spectra identify linear events in the GPR data gathers like DGW events and allow for estimating the corresponding velocities. In addition to obtaining a DGW velocity measurement, we propose a robust method to estimate the associated velocity uncertainties based on the width of the peak in the calculated velocity spectrum. Our proposed method is tested on synthetic data examples to evaluate the influence of subsurface velocity, surveying geometry and signal frequency on the accuracy of estimated ground-wave velocities. In addition, we investigate the influence of such velocity uncertainties on subsequent soil water content estimates using an established petrophysical relationship. Furthermore, we apply our approach to analyse field data, which were collected across a test site in Canada to monitor a wide range of seasonal soil moisture variations. A comparison between our spectral velocity estimates and results derived from manually picked ground-wave arrivals shows good agreement, which illustrates that our spectral velocity analysis is a feasible tool to analyse DGW arrivals in multi-offset GPR data gathers in an objective and more automated manner.
In many near-surface geophysical studies it is now common practice to collect co-located disparate geophysical data sets to explore subsurface structures. Reconstruction of physical parameter distributions underlying the available geophysical data sets usually requires the use of tomographic reconstruction techniques. To improve the quality of the obtained models, the information content of all data sets should be considered during the model generation process, e.g., by employing joint or cooperative inversion approaches. Here, we extend the zonal cooperative inversion methodology based on fuzzy c-means cluster analysis and conventional single-input data set inversion algorithms for the cooperative inversion of data sets with partially co-located model areas. This is done by considering recent developments in fuzzy c-means cluster analysis. Additionally, we show how supplementary a priori information can be incorporated in an automated fashion into the zonal cooperative inversion approach to further constrain the inversion. The only requirement is that this a priori information can be expressed numerically; e.g., by physical parameters or indicator variables. We demonstrate the applicability of the modified zonal cooperative inversion approach using synthetic and field data examples. In these examples, we cooperatively invert S- and P-wave traveltime data sets with partially co-located model areas using water saturation information expressed by indicator variables as additional a priori information. The approach results in a zoned multi-parameter model, which is consistent with all available information given to the zonal cooperative inversion and outlines the major subsurface units. In our field example, we further compare the obtained zonal model to sparsely available borehole and direct-push logs. This comparison provides further confidence in our zonal cooperative inversion model because the borehole and direct-push logs indicate a similar zonation.
In this paper, we present an efficient kinematic ground-penetrating radar (GPR) surveying setup using a self- tracking total station (TTS). This setup combines the ability of modern GPR systems to interface with Global Positioning System (GPS) and the capability of the employed TTS system to immediately make the positioning information available in a standardized GPS data format. Wireless communication between the GPR and the TTS system is established by using gain variable radio modems. Such a kinematic surveying setup faces two major potential limitations. First, possible crosstalk effects between the GPR and the positioning system have to be evaluated. Based on multiple walkaway experiments, we show that, for reasonable field setups, instrumental crosstalk has no significant impact on GPR data quality. Second, we investigate systematic latency (i.e., the time delay between the actual position measurement by TTS and its fusion with the GPR data) and its impact on the positional precision of kinematically acquired 2-D and 3-D GPR data. To quantify latency for our kinematic survey setup, we acquired forward-reverse profile pairs across a well-known subsurface target. Comparing the forward and reverse GPR images using three fidelity measures allows determining the optimum latency value and correcting for it. Accounting for both of these potential limitations allows us to kinematically acquire high- quality and high-precision GPR data using off-the-shelf instrumentation without further hardware modifications. Until now, these issues have not been investigated in detail, and thus, we believe that our findings have significant implications also for other geophysical surveying approaches.
Mapping hydrological parameter distributions in high resolution is essential to understand and simulate groundwater flow and contaminant transport. Of particular interest is surface-based ground-penetrating radar (GPR) reflection imaging in electrically resistive sediments because of the expected close link between the subsurface water content and the dielectric permittivity, which controls GPR wave velocity and reflectivity. Conventional tools like common midpoint (CMP) velocity analysis provide physical parameter models of limited resolution only. We present a novel reflection amplitude inversion workflow for surface-based GPR data capable of resolving the subsurface dielectric permittivity and related water content distribution with markedly improved resolution. Our scheme is an adaptation of a seismic reflection impedance inversion scheme to surface-based GPR data. Key is relative-amplitude-preserving data preconditioning including GPR deconvolution, which results in traces with the source-wavelet distortions and propagation effects largely removed. The subsequent inversion for the underlying dielectric permittivity and water content structure is constrained by in situ dielectric permittivity data obtained by direct-push logging. After demonstrating the potential of our novel scheme on a realistic synthetic data set, we apply it to two 2-D 100 MHz GPR profiles acquired over a shallow sedimentary aquifer resulting in water content images of the shallow (3-7 m depth) saturated zone having decimeter resolution.
Assessing the human and economic threat introduced by sliding or creeping masses is of major importance in landslide hazard assessment and mitigation. Especially, in the densely populated alpine region unstable hillslopes represent a major hazard to men and infrastructure. Detailed knowledge, especially, of the dominant site-specific controlling factors such as subsurface architecture and geology is thereby key in assessing slope vulnerability. In order to quantify the geological variations at a creeping hillslope in the Austrian Alps, we have collected six 2D refraction seismic profiles. We propose using a layer-based inversion strategy to reconstruct P-wave velocity models from first arrival times. Considering the geological complexity at such sites, the selected inversion approach eases the interpretability of geological structures given intrinsic optimization for only a discrete, user-defined, number of layers. As the applied layer-based inversion approach fits our travel time data equally well as traditional smooth inversion approaches, it represents a feasible mean to summarize the structural complexity often present at such sites. Analysis of the inversion results illustrates that bedrock topography clearly deviates from a previously assumed planar surface and exhibits distinct variations across the slope extension. Bedrock topography additionally impacts the intermediate geological units and, thus, this information is critical for further analyses such as geomechanical modeling. (C) 2012 Elsevier B.V. All rights reserved.
We have collected magnetic, 3D ground-penetrating-radar (GPR), and topographic data at an archaeological site within the Palace Garden of Paretz, Germany. The survey site covers an area of approximately 35 x 40 m across a hill structure (dips of up to 15 degrees) that is partly covered by trees. The primary goal of this study was to detect and locate the remains of ancient architectural elements, which, from historical records, were expected to be buried in the subsurface at this site. To acquire our geophysical data, we used a recently developed surveying approach that combines the magnetic and GPR instrument with a tracking total station (TTS). Besides efficient data acquisition, this approach provides positional information at an accuracy within the centimeter range. At the Paretz field site, this information was critical for processing and analyzing our geophysical data (in particular, GPR data) and enabled us to generate a high-resolution digital terrain model (DTM) of the surveyed area. Integrated analysis and interpretation based on composite images of the magnetic, 3D GPR, and high-resolution DTM data as well as selected attributes derived from these data sets allowed us to outline the remains of an artificial grotto and temple. Our work illustrates the benefit of using multiple surveying technologies, analyzing and interpreting the resulting data in an integrated fashion. It further demonstrates how modern surveying solutions allow for efficient, accurate data acquisition even in difficult terrain.
Three-dimensional (3D) ground-penetrating radar (GPR) represents an efficient high-resolution geophysical surveying method allowing to explore archaeological sites in a non-destructive manner. To effectively analyze large 3D GPR data sets, their combination with modern visualization techniques (e.g., 3D isoamplitude displays) has been acknowledged to facilitate interpretation beyond classical time-slice analysis. In this study, we focus on the application of data attributes (namely energy, coherency, and similarity), originally developed for petroleum reservoir related problems addressed by reflection seismology, to emphasize temporal and spatial variations within GPR data cubes. Based on two case studies, we illustrate the potential of such attribute based analyses towards a more comprehensive 3D GPR data interpretation. The main goal of both case studies was to localize and potentially characterize tombs inside medieval chapels situated in the state of Brandenburg, Germany. By comparing the calculated data attributes to the conventionally processed data cubes, we demonstrate the superior interpretability of the coherency and the similarity attribute for target identification and characterization.