GPR Data Research Articles

Combining geomorphological mapping and near surface geophysics (GPR and ERT) to study piping systems

This paper aims to provide a more comprehensive characterization of piping systems in mountainous areas under a temperate climate using geomorphological mapping and geophysical methods (electrical resistivity tomography – ERT and ground penetrating radar – GPR). The significance of piping in gully formation and hillslope hydrology has been discussed for many years, and most of the studies are based on surface investigations. However, it seems that most surface investigations underestimate this subsurface process. Therefore, our purpose was to estimate the scale of piping activity based on both surface and subsurface investigations. We used geophysical methods to detect the boundary of lateral water movement fostering pipe development and recognize the internal structure of the underlying materials. The survey was carried out in the Bereźnica Wyżna catchment, in the Bieszczady Mountains. (Eastern Carpathians, Poland), where pipes develop in Cambisols at a mean depth of about 0.7–0.8m. The geophysical techniques that were used are shown to be successful in identifying pipes. GPR data suggest that the density of piping systems is much larger than that detectible from surface observations alone. Pipe length can be >6.5–9.2% (maximum=49%) higher than what surface mapping suggests. Thus, the significance of piping in hillslope hydrology and gully formation can be greater than previously assumed. These results also draw attention to the scale of piping activity in the Carpathians, where this process has been neglected for many years. The ERT profiles reveal areas affected by piping as places of higher resistivity values, which are an effect of a higher content of air-filled pores (due to higher soil porosity, intense biological activity, and well-developed soil structure). In addition, the ERT profiles show that the pipes in the study area develop at the soil–bedrock interface, probably above the layers of shales or mudstones which create a water restrictive layer. Our results illustrate the suitability and limitations of GPR and ERT to study soil piping. In general, geophysical surveying is useful for gathering more information on pipe density, potential pipe detection, and recognition of the internal structure of materials underlying the pipes. However, the interpretation of radargrams and ERT profiles should be always accompanied by detailed terrain mapping due to potential disturbances affecting geophysical profiles.

Use of electromagnetic two-layer wave-guided propagation in the GPR frequency range to characterize water transfer in concrete

The objective of this paper is to adapt a recent innovative technique for extracting and exploiting the Electromagnetic (EM) waveguide dispersion of civil engineering materials by means of GPR, and allowing to monitor the water ingress front during the absorption process for various concrete mixes. This technique is based on an inversion procedure that applies the Electromagnetic Waveguide Model (WGM) to invert phase velocity dispersion curves in their modal form. A Parallel homogenization model, derived from the Lichtenecker-Rother equation, has been employed to extend the waveguide model from a one-layer to a two-layer medium. The WGM outputs are then used to estimate the geometric parameters of the propagation medium and offer a primary application to water transfer monitoring in concrete through capillarity effects. The initial WGM validation is carried out on FDTD-simulated propagation signals, while the second validation relies on GPR data acquired from homogeneous materials. Then, a broad-based experimental study is conducted for the purpose of correlating electromagnetic waveguide dispersion parameters with both the geometric and hydric characteristics of various concrete mixes. Results obtained using the two-layer WGM serve to monitor the water ingress front during an absorption process. These results are then compared to the moisture gradients generated on cores using gammadensimetry, which is set as the reference. This procedure yields a number of trends, which in turn provide key information on the conditioning state of the studied concretes.

Texture Attribute Analysis of GPR Data for Archaeological Prospection

We evaluate the applicability and the effectiveness of texture attribute analysis of 2-D and 3-D GPR datasets obtained in different archaeological environments. Textural attributes are successfully used in seismic stratigraphic studies for hydrocarbon exploration to improve the interpretation of complex subsurface structures. We use a gray-level co-occurrence matrix (GLCM) algorithm to compute second-order statistical measures of textural characteristics, such as contrast, energy, entropy, and homogeneity. Textural attributes provide specific information about the data, and can highlight characteristics as uniformity or complexity, which complement the interpretation of amplitude data and integrate the features extracted from conventional attributes. The results from three archaeological case studies demonstrate that the proposed texture analysis can enhance understanding of GPR data by providing clearer images of distribution, volume, and shape of potential archaeological targets and related stratigraphic units, particularly in combination with the conventional GPR attributes. Such strategy improves the interpretability of GPR data, and can be very helpful for archaeological excavation planning and, more generally, for buried cultural heritage assessment.

A versatile tuneable curvelet-like directional filter with application to fracture detection in two-dimensional GPR data

The present work introduces a curvelet-like directional filter and discusses its application to edge detection in general images and fracture detection in GPR data. The filter is essentially a curvelet of adjustable anisotropy and orientation that can be tuned on any given (target) wavenumber; while retaining the properties of curvelets, it is not bound to the scaling rules of the Curvelet Frame but is individually steerable to any local trait of the data, hence it is dubbed “Curveletiform”. Curveletiforms can be used in single- or multi-directional modes in a manner simple, computationally inexpensive and demonstrably efficient. GPR data generally contains straight or curved edge-like objects comprising reflections from planar interfaces and is notoriously susceptible to broadband noise. Fractures are an important class of interfaces as they determine the health state of rocks or man-made structures and are primary targets of GPR surveys in geotechnical, engineering and environmental applications. As demonstrated with examples, Curveletiforms can efficiently recover information of specific scale and geometry from straight or curved edges in general images. In GPR data they may distinguish reflections from small and large fractures, discriminate between groups of fractures, resolve fracture density and aid the assessment of damage in rocks and structures.

Understanding depth-amplitude effects in assessment of GPR data from concrete bridge decks

The variation of concrete cover thickness on bridge decks has been observed to significantly affect the rebar reflection amplitude of the ground penetrating radar signal. Several depth correction approaches have been previously proposed in which it is assumed that, for any bridge, at least a portion of the deck area is sound concrete. The 90th percentile linear regression is a commonly used procedure to extract the depth-amplitude relationship of the assumed sound concrete. It is recommended herein that normalizing the depth-dependent amplitudes be divided into two components. The first component takes into account the geometric loss due to inverse-square effect and the dielectric loss caused by the dissipation of electromagnetic energy in sound concrete. The second component is the conductive loss as a result of increased free charges associated with concrete deterioration. Whereas the conventional depth correction techniques do not clearly differentiate the two components and tend to incorporate both in the regression line, they are separately addressed in this research. Specifically, while the first component was accounted for based on a library of GPR signals collected from sound areas of twenty four bare concrete bridge decks, the conductive loss caused by an increased conductivity is linearly normalized by the two-way travel time. The implementation of the proposed method in two case studies showed that, while the method significantly improves the accuracy of GPR data analysis, the conventional methods may lead to a loss of information regarding the background attenuation that would indicate the overall deterioration of bridge decks.

Multi Population Genetic Algorithm to estimate snow properties from GPR data

Multi-population genetic algorithms (DGA or MGA) are based on the partition of the population into several semi-isolated subpopulations (demes). Each sub-population is associated to an independent GA and explores different promising regions of the search space. We evaluate the sensitivity of some parameters to solve a non-linear problem in georadar data analysis. Particularly, we adapt the DGAs to optimize the model parameters of a data set of variable-offset data, collected in variable offset modality with Ground Penetrating Radar, to estimate porosity, saturation and density of snowpack in a glacial environment. The data set comes from investigation on glaciers to estimate the thickness and density of the seasonal snow. The main strategies to select the best parameters of the optimization process are outlined. We analyze the sensitivity on the solution of the optimization problems of some parameters of DGA; we deal with the effects of population and sub-population, and mutation properties. We consider the reflection traveltimes in a layered medium including a relationship between the traveltimes, porosity and saturation of the snow. We solve the problem for the layer thickness and the porosity, saturation and structural exponent of the snow. Reliable results are obtained in the snow density estimating, while the evaluation of free water content into the snow still remains challenging.

Can a simple Numerical Model Help to Fine-Tune the Analysis of Ground-Penetrating Radar Data? Hochebenkar Rock Glacier as a Case Study

ABSTRACTLittle is known about the thickness of active Alpine rock glaciers, yet they are important components of the local hydrology. We use GPR data to determine the depth of the bedrock of Äußeres Hochebenkar rock glacier (Austria). There is no detailed information available regarding density and composition of the rock glacier, and assumptions about the signal propagation velocity have to be made when processing the GPR data. We use a simple creep model based on surface displacement and slope to calculate the thickness of the rock glacier along a flow line. We calculated bedrock profiles along the flow line for three different time periods, using input from multitemporal digital elevation models. We improved the fit of the profiles by calibrating the values used for layer densities and considered the model valid where the modelled bedrock profiles are within error of each other. We then compared the modeled values with the GPR data to check whether our assumptions for the propagation velocity produced results that match the model. While the fit is good at the lower end of the rock glacier, the GPR data appear to overestimate depth in the upper region. We adjusted the propagation velocity accordingly and find maximum thicknesses of over 50 m and a mean thickness of 30–40 m. The insights gained from the modeling approach thereby improved the fine-tuning of the GPR analysis.

A case study of the use of GPR for rehabilitation of a classified Art Deco building: The InovaDomus house

Ancient buildings in historical town centers can be protected by Cultural Heritage legislation, thus implying that any rehabilitation must respect their main architectural features. These concerns also apply to Modern and Contemporary buildings, in particular if they are important examples of architectural styles from those periods.These extra problems, or motivations, add to the inherent structural delicacy of ancient building restoration that requires detailed knowledge of the building foundations, characteristics and materials, modification history, infrastructure mapping, current pathologies, etc., all relevant information for an informed rehabilitation project.Such knowledge is seldom available before the actual rehabilitation works begin, and the usual invasive preliminary surveys are frequently expensive, time-consuming and likely significantly alter/damage the building's main features or structural integrity. Hence, the current demand for indirect, non-invasive, reliable and high resolution imagery techniques able to produce relevant information at the early stages of a rehabilitation project.The present work demonstrates that Ground Penetrating Radar (GPR or Georadar) surveys can provide a priori knowledge on the structure, construction techniques, materials, history and pathologies in a classified Modern Age building. It is also shown that the use of GPR on these projects requires carefully designed surveys, taking into account the known information, spatial constraints, environmental noise, nature and dimensions of the expected targets and suitable data processing sequences.Thus, if properly applied, GPR produces high-resolution results crucial for sound engineering/architectural interventions aiming to restore and renovate Modern and Contemporary buildings, with (1) focus on the overall quality of the end-result, (2) no damage inflicted to the existing structure, (3) respect of the building's historical coherence and architectural elements and characteristics, that is, its Cultural Heritage value.Most of the findings and applications discussed in this work can be seen as an approximation to model studies, so that, relevant information can be drawn from the different investigated situations. Therefore, owing to the nature and the range of the problems encountered in this case study, it is also expected that the presented GPR data and interpretation will provide important clues and guidance in the planning and investigation of similar projects and problems.

Integrating auxiliary data and geophysical techniques for the estimation of soil clay content using CHAID algorithm

This study was conducted to estimate soil clay content in two depths using geophysical techniques (Ground Penetration Radar—GPR and Electromagnetic Induction—EMI) and ancillary variables (remote sensing and topographic data) in an arid region of the southeastern Iran. GPR measurements were performed throughout ten transects of 100m length with the line spacing of 10m, and the EMI measurements were done every 10m on the same transect in six sites. Ten soil cores were sampled randomly in each site and soil samples were taken from the depth of 0–20 and 20–40cm, and then the clay fraction of each of sixty soil samples was measured in the laboratory. Clay content was predicted using three different sets of properties including geophysical data, ancillary data, and a combination of both as inputs to multiple linear regressions (MLR) and decision tree-based algorithm of Chi-Squared Automatic Interaction Detection (CHAID) models. The results of the CHAID and MLR models with all combined data showed that geophysical data were the most important variables for the prediction of clay content in two depths in the study area. The proposed MLR model, using the combined data, could explain only 0.44 and 0.31% of the total variability of clay content in 0–20 and 20–40cm depths, respectively. Also, the coefficient of determination (R2) values for the clay content prediction, using the constructed CHAID model with the combined data, was 0.82 and 0.76 in 0–20 and 20–40cm depths, respectively. CHAID models, therefore, showed a greater potential in predicting soil clay content from geophysical and ancillary data, while traditional regression methods (i.e. the MLR models) did not perform as well. Overall, the results may encourage researchers in using georeferenced GPR and EMI data as ancillary variables and CHAID algorithm to improve the estimation of soil clay content.

Rock fracture characterization with GPR by means of deterministic deconvolution

In this work I address GPR characterization of rock fracture parameters, namely thickness and filling material. Rock fractures can generally be considered as thin beds, i.e., two interfaces whose separation is smaller than the resolution limit dictated by the Rayleigh's criterion. The analysis of the amplitude of the thin bed response in the time domain might permit to estimate fracture features for arbitrarily thin beds, but it is difficult to achieve and could be applied only to favorable cases (i.e., when all factors affecting amplitude are identified and corrected for). Here I explore the possibility to estimate fracture thickness and filling in the frequency domain by means of GPR. After introducing some theoretical aspects of thin bed response, I simulate GPR data on sandstone blocks with air- and water-filled fractures of known thickness. On the basis of some simplifying assumptions, I propose a 4-step procedure in which deterministic deconvolution is used to retrieve the magnitude and phase of the thin bed response in the selected frequency band. After deconvolved curves are obtained, fracture thickness and filling are estimated by means of a fitting process, which presents higher sensitivity to fracture thickness. Results are encouraging and suggest that GPR could be a fast and effective tool to determine fracture parameters in non-destructive manner. Further GPR experiments in the lab are needed to test the proposed processing sequence and to validate the results obtained so far.

Long-term Geophysical Monitoring of Simulated Clandestine Graves using Electrical and Ground Penetrating Radar Methods: 4-6 Years After Burial.

This ongoing monitoring study provides forensic search teams with systematic geophysical data over simulated clandestine graves for comparison to active cases. Simulated "wrapped," "naked," and "control" burials were created. Multiple geophysical surveys were collected over 6 years, here showing data from 4 to 6 years after burial. Electrical resistivity (twin electrode and ERI), multifrequency GPR, grave and background soil water were collected. Resistivity surveys revealed that the naked burial had low-resistivity anomalies up to year four but then difficult to image, whereas the wrapped burial had consistent large high-resistivity anomalies. GPR 110- to 900-MHz frequency surveys showed that the wrapped burial could be detected throughout, but the naked burial was either not detectable or poorly resolved. 225-MHz frequency GPR data were optimal. Soil water analyses showed decreasing (years 4 to 5) to background (year 6) conductivity values. Results suggest both resistivity and GPR surveying if burial style unknown, with winter to spring surveys optimal and increasingly important as time increases.

Glaciological and geophysical investigations aimed at organization of a new airfield at the Station Mirny (East Antarctica)

Main results of glaciological and geophysical engineering surveys, conducted during three summer field seasons of 2013– 2016 (59–61st Russian Antarctic Expeditions – RAE) near the Russian Station Mirny (East Antarctica), are discussed in the paper. Objective of these works was to site and then to organize a new airfield for landing of medium-range aircrafts with ski landing gears. Investigations included aerial photography, GPR surveys (georadar profiling), ice core drilling, and installation of landmarks to measure velocity of the glacier motion. The GSSI ground-penetrating radars with the main frequencies of 270 MHz and 900 MHz were used. In addition, special explorations were conducted for detecting the englacial crevasses by means of remote-sensing methods. The GPR data allowed a revealing the boundary between snow-andfirn thickness and atmospheric ice. In the course of processing of 252 travel-time curves of the diffracted waves a kinematic model of the sub-surface part of the glacier has been constructed. It was found that the dielectric permittivity of the snowfirn thickness averages 2.43; similar value for the atmospheric ice amounts to 3.0. The GPR data made it possible to determine intraglacial (englacial) crevasses and to choose the most favorable field for the landing. On February 10, 2016, the first middle-range aircraft DC-3T (BT-67) had landed onto the new run-way near the station Mirny.

Full-waveform inversion of GPR data acquired between boreholes in Rustrel carbonates

Full waveform inversion (FWI) of seismic or Ground Penetrating Radar data provides high-resolution quantitative images of the constitutive parameters of the rock/soil which control seismic/GPR wave propagation. We developed a 2D inversion tool in the frequency domain adapted to the multi-parameter physics controlling GPR propagation in isotropic non dispersive media, i.e. dielectric permittivity and electrical conductivity. This inversion engine was previously tested using synthetic 2D data to mitigate the trade-off between the two parameter classes. In this paper, we present the required processing techniques and first inversion results obtained on a real GPR dataset acquired in carbonates with a cross-hole configuration. The presence of the 2 m diameter underground gallery at depth constitutes a nice target to test the robustness, efficiency and resolution of the inversion in such high-contrasts context. Starting from a time tomographic image for the dielectric permittivity and from a homogeneous conductivity, we show that FWI is efficient to retrieve high resolution images of dielectric permittivity but struggles with electrical conductivity. As a quality control, we compare real and synthetic radargrams computed from the tomography and final images, showing the efficiency of the process to reconstruct some events but also underlying some issues, particularly on large incidence angles amplitude traces.

The Use of Three-dimensional Analysis of GPR Data in Evaluation of Operational Safety of Airfield Pavements

Diagnosis of airfield pavements is an important component of airport managing. Proper diagnosis makes possible to take optimal decisions in terms of ongoing maintenance and repairs, which in the case of airfields is of particular importance, among others, in the context of seasonal changes in the intensity of air traffic. The completeness and accuracy of gathered data is important in the diagnostic activities, what means that the entire airfield road network should be measured and identification of all relevant pavement construction parameters at regular intervals should be done. These capabilities give the Ground Penetrating Radar technique (GPR), which enables the evaluation of the pavement structure in different ways and outlining different aspects of construction.GPR application as a tool supporting the process of state assessment gives a wider and better understanding of the potential damage of pavement. Properly prepared methodology of measurement, configuration and selection of the measurement system creates the possibility of observation of the investigated object, not only in a single plane of a typical radar profiling, but also in the three-dimensional image. Spatial representation obtained on the basis of synchronized profiling allows precise localization of interlayer boundaries in longitudinal and transverse directions. An important advantage of three-dimensional analysis is the ability of imaging data by the use of horizontal cuts (slices). This makes it possible to identify plane direction and depth of the cracks and crevices of concrete slabs covered with layers of asphalt or concrete. An additional element of the GPR data analysis can be quantitative assessment of dowels in concrete slabs, reinforcement of prefabricated elements supporting pavement structure, as well as location of pipes, cables, tie bars and other.The paper presents the series of examples illustrating the use of GPR technique as supporting in the process airfield pavement assessment.

Impact of Wood Sample Shape and Size on Moisture Content Measurement Using a GPR-Based Sensor

Nondestructive, GPR-based real-time sensors have been shown to be an effective tool for measuring moisture content in wood samples within the forest products industry. Moisture content is derived from either the early time electromagnetic pulse amplitude or the pulse travel time through the wood sample. When used on samples that are comparable in size to the sensor antenna and wavelength within the sample, the GPR sensor will measure a moisture content that is dependent on the sample shape and size. In this study, we look at a cylindrical sample, representative of a typical wood log sample. We have used numerical modeling with both simplified, unshielded Hertzian dipole antennas and a realistic shielded GPR antenna system to estimate these effects. The numerical modeling shows that for measurements performed on the sides or ends of small diameter logs, the curvature of the log, and closeness of the log boundaries has a significant impact on the early time amplitude and signal travel time through the log that result in reduced accuracy in moisture content measurements. Wood logs have electrical properties that are anisotropic and vary radially within the log. Our numerical models are assumed to be isotropic and homogeneous. GPR data acquired on the ends of wood logs show similar dependency on log diameter to those observed in the modeling, and numerical model results compare reasonably well with data measured on measured logs. The numerical modeling results also demonstrate the importance of using realistic shielded antenna models in this application.

Railway Ballast Fouling Detection Using GPR Data: Introducing a Combined Time–Frequency and Discrete Wavelet Techniques

ABSTRACTGround‐penetrating radar has been recently used for quantifying railway ballast fouling conditions. This paper discusses two approaches for processing the railway ballast ground‐penetrating radar signal: the discrete wavelet transform method and the short‐time Fourier transform method. Ground‐penetrating radar field data collected in Wyoming in 2007 by two 2‐GHz air‐coupled antennas were used to verify both approaches. The collected ground‐penetrating radar signals were processed by discrete wavelet transform. The signal standard deviation values were fitted by linear regression of the fouling indices, which were calculated using ground‐truth sieving data. The spectrogram generated by short‐time Fourier transform was used to analyse the ballast fouling condition level by comparing the energy attenuation speed. It was observed that both discrete wavelet transform and short‐time Fourier transform approaches can be used to analyse ballast fouling conditions. The short‐time Fourier transform method is easier to visualize, whereas the discrete wavelet transform approach can more quantitatively predict the fouling level. However, the discrete wavelet transform method provides the fouling condition of the whole ballast layer, whereas the spectrogram provides the fouling condition with respect to the depth profile.

MULTI GEOPHYSICAL OBSERVATIONS AT BLAWAN - IJEN VOLCANO GEOTHERMAL COMPLEX FOR REGIONAL DEVELOPMENT

Geothermal resource investigation by using multi geophysical observation was accomplished for Blawan-Ijen geothermal system. Geological and surface investigation found about 21 hot springs have been found in Blawan area with the surface temperature ranged from about 40 o C-55 o C. Based on resistivity and GPR data known that the underground seepage of hot water following the fault direction. This fault structure is identified based on the high distribution of microseismicity and thermal infrared remote sensing (TIR) analysis which associated with high land surface temperature (LST). Meanwhile, the heat source of Blawan - Ijen geothermal system are found in the southwest part based on high magnetic anomaly which represents the igneous rocks. All methods used shows the results indicating that Blawan-Ijen volcano complex is an interesting area for geothermal energy development and suitable for pilot project on regional development of volcano geothermal region.

Evaluation of historical bridges through recreation of GPR models with the FDTD algorithm

This work presents the evaluation of a medieval masonry bridge that has suffered different restorations throughout history. Ground penetrating radar was used to define the internal state of the structure. Given that the heterogeneity in masonry complicates the interpretation of field data, numerical modelling was employed to improve such interpretation. The combination of photogrammetric and thermographic data, jointly with the development of custom algorithms, was used to create the synthetic model; while real GPR data supported the media characterization. The resulting data allowed for the interpretation of both composition and distribution of different materials in the interior of the bridge.

Monitoring CO2 migration in a shallow sand aquifer using 3D crosshole electrical resistivity tomography

Three-dimensional (3D) crosshole electrical resistivity tomography (ERT) was used to monitor a pilot CO2 injection experiment at Vrøgum, western Denmark. The purpose was to evaluate the effectiveness of the ERT method for detection of small electrical conductivity (EC) changes during the first 2 days of CO2 injection in a shallow siliciclastic aquifer and to study the early-time behavior of a controlled small gaseous CO2 release. 45kg of CO2 was injected over a 50-h period at 9.85m depth. ERT data were collected using horizontal bipole-bipole (HBB) and vertical bipole-bipole (VBB) arrays. The combined HBB and VBB data sets were inverted using a difference inversion algorithm for cancellation of coherent noises and enhanced resolution of small changes. ERT detected the small bulk EC changes (<10%) from conductive dissolved CO2 and resistive gaseous CO2. The primary factors that control the migration of a CO2 plume consist of buoyancy of gaseous CO2, local heterogeneity, groundwater flow and external pressure exerted by the injector. The CO2 plume at the Vrøgum site migrated mostly upward due to buoyancy and it also skewed toward northeastern region by overcoming local groundwater flow. The conductive eastern part is more porous and becomes the preferential pathway for the CO2 plume, which was trapped within the slightly more porous glacial sand layer between 5m and 10m depths. The gaseous and dissolved CO2 plumes are collocated and grow in tandem for the first 24h and their opposite effects resulted in a small bulk EC increase. After raising the injection rate from 10g/min to 20g/min at the 24-h mark, the CO2 plume grew quickly. The bulk EC changes from ERT agreed partially with water sample EC and GPR data. The apparent disagreement between high CO2 gas saturation and prevailing positive bulk EC changes may be caused by limited and variable ERT resolution, low ERT sensitivity to resistive anomalies and uncalibrated CO2 gas saturation. ERT data show a broader CO2 plume while water sample EC had higher fine-scale variability. Our ERT electrode configuration can be optimized for more efficient data acquisition and better spatial resolution.

Ground‐Penetrating Radar for Archaeology (3rd Edn)Lawrence B.Conyers, Series Editors: Lawrence B.Conyers and Kenneth L.Kvamme, Geophysical Methods for Archaeology No. 4, AltaMira Press, Lanham, MD, 2013, xv + 241 pp., £22.95, ISBN 978‐0‐7591‐2349‐6 (paperback)

Keywords: Ground-penetrating radar; Archaeology; GPR data acquisition; GPR data processing; GPR data interpretation; GPR equipment