Ground-penetrating Radar Field Data Research Articles

Examining the information content of time-lapse crosshole GPR data collected under different infiltration conditions to estimate unsaturated soil hydraulic properties

Time-lapse geophysical data acquired during transient hydrological experiments are being increasingly employed to estimate subsurface hydraulic properties at the field scale. In particular, crosshole ground-penetrating radar (GPR) data, collected while water infiltrates into the subsurface either by natural or artificial means, have been demonstrated in a number of studies to contain valuable information concerning the hydraulic properties of the unsaturated zone. Previous work in this domain has considered a variety of infiltration conditions and different amounts of time-lapse GPR data in the estimation procedure. However, the particular benefits and drawbacks of these different strategies as well as the impact of a variety of key and common assumptions remain unclear. Using a Bayesian Markov-chain-Monte-Carlo stochastic inversion methodology, we examine in this paper the information content of time-lapse zero-offset-profile (ZOP) GPR traveltime data, collected under three different infiltration conditions, for the estimation of van Genuchten–Mualem (VGM) parameters in a layered subsurface medium. Specifically, we systematically analyze synthetic and field GPR data acquired under natural loading and two rates of forced infiltration, and we consider the value of incorporating different amounts of time-lapse measurements into the estimation procedure. Our results confirm that, for all infiltration scenarios considered, the ZOP GPR traveltime data contain important information about subsurface hydraulic properties as a function of depth, with forced infiltration offering the greatest potential for VGM parameter refinement because of the higher stressing of the hydrological system. Considering greater amounts of time-lapse data in the inversion procedure is also found to help refine VGM parameter estimates. Quite importantly, however, inconsistencies observed in the field results point to the strong possibility that posterior uncertainties are being influenced by model structural errors, which in turn underlines the fundamental importance of a systematic analysis of such errors in future related studies.

Waveguide properties recovered from shallow diffractions in common offset GPR

[1] Near-surface heterogeneities produce diffractions in common offset ground-penetrating radar (GPR) data from the Gnangara Groundwater Mound, north of Perth, Western Australia. These diffracted wavefields can be enhanced and show a dispersion pattern if they propagate along a waveguide caused by a low velocity surface layer, such as moist sand on top of dry sand. Until now, GPR waveguide dispersion has been analyzed and inverted using common midpoint data. Using numerical modeling, we demonstrate that the same dispersion information can also be recovered from a diffracted electromagnetic wavefield recorded with common offset geometry. Frequency-slowness analysis of shallow diffractions in common offset GPR field data reveals high resolution dispersion curves. Inverting picked dispersion maxima to modeled curves (i.e., modal wave propagation in waveguide layer) allows estimation of waveguide height and velocities of waveguide and the underlying material. Data analysis in the frequency-wavenumber domain provides an alternative technique for extracting dispersion curves. Preliminary results validate this approach, which could be favorable in large-scale applications due to minimal processing requirement and inherent yet adjustable spatial averaging. The differences between waveguide parameters recovered from two surveys appear to be consistent with seasonal changes in moisture content and lateral changes due to variations in depositional environment. Our approach presents a new method to quantify the shallow dielectric permittivity structure of the subsurface from common offset gathers—the most commonly acquired type of GPR data. Potential applications of this method include estimation of shallow moisture distribution, early target identification for unexploded ordnance (UXO) detection, concrete slab characterization, pedological investigations, or planetary exploration.

Location of Agricultural Drainage Pipes and Assessment of Agricultural Drainage Pipe Conditions Using Ground Penetrating Radar

Methods are needed to not only locate buried agricultural drainage pipe, but to also determine if the pipes are functioning properly with respect to water delivery. The primary focus of this research project was to confirm the ability of ground penetrating radar (GPR) to locate buried drainage pipe, and then determine if GPR provides insight into drain line water conveyance functionality. Ground penetrating radar surveys using [Formula: see text] transmitter/receiver antennas were conducted at a specially designed test plot under drained, moderately wet soil conditions (water table below drain lines) and undrained, extremely wet soil conditions (water table above drain lines). The test plot contained four drain lines: one a clay tile to corrugated plastic tubing (CPT) drain line that was completely open to flow; one comprised of CPT with an isolated obstruction near the midpoint, completely preventing through-flow of water; one comprised of CPT but filled with soil; and one comprised of CPT but severed near its midpoint, producing a partial obstruction to water flow. Subsequent GPR computer modeling simulations were employed to assist with interpretation of the GPR field data. Results of the GPR field surveys indicate that given suitable shallow hydrologic conditions, GPR not only finds drainage pipes, but can also determine the position along a drain line where there is an isolated obstruction that completely blocks water flow. However, results show that a partial pipe obstruction is difficult to locate using GPR. Surprisingly, the soil-filled drain line was clearly detectable under both soil hydrologic conditions tested. The GPR computer modeling simulations indicate that soil had likely settled within the pipe, and that the GPR responses obtained at the test plot for the soil-filled pipe were responses representative of a pipe that was in fact only partially filled with soil. Overall, these research results provide valuable information for those contemplating the use of GPR to locate agricultural drainage pipes and then determine their functionality.

Railroad Ballast Evaluation Using Ground-Penetrating Radar

Ballast fouling in the railroad substructure is detrimental to the effectiveness of the railroad track and its structural capacity. The early detection of ballast fouling is of utmost importance to the safety of the rail system and its life-cycle cost-effectiveness. Ground-penetrating radar (GPR), a nondestructive evaluation tool, has shown its potential as a means of assessing the condition of the railroad substructure rapidly, effectively, and continuously. However, an unknown ballast dielectric constant and an unclear interface between clean and fouled ballast limit the accuracy of GPR assessment. In the present study, controlled laboratory testing was conducted to measure accurately the dielectric constants of two common ballast types, granite and limestone, under various fouling and moisture conditions. In addition, a time–frequency method, short-time Fourier transform (STFT), was used to demonstrate graphically the frequency energy variation with the depth of the ballast under various conditions. This method indirectly reflects the ballast fouling condition. To validate the effectiveness of STFT for ballast fouling assessment, field GPR data from the Orin Subdivision in Wyoming were analyzed with the STFT technique and laboratory-measured dielectric constants. Comparison of the ground truth data and GPR measurements proved that the STFT method is effective and that its results are reasonably accurate when it is used to locate fouling and trapped water within ballast, especially when the laboratory-predicted ballast dielectric constants are used in the analysis.

A new approach to enhancement of ground penetrating radar target signals by pulse compression

Ground penetrating radar (GPR) is an effective tool for detecting shallow subsurface targets. In many GPR applications, these targets are veiled by the strong waves reflected from the ground surface, so that we need to apply a signal processing technique to separate the target signal from such strong signals. A pulse-compression technique is used in this research to compress the signal width so that it can be separated out from the strong contaminated clutter signals. This work introduces a filter algorithm to carry out pulse compression for GPR data, using a Wiener filtering technique. The filter is applied to synthetic and field GPR data acquired over a buried pipe.The discrimination method uses both the reflected signal from the target and the strong ground surface reflection as a reference signal for pulse compression. For a pulse-compression filter, reference signal selection is an important issue, because as the signal width is compressed the noise level will blow up, especially if the signal-to-noise ratio of the reference signal is low. Analysis of the results obtained from simulated and field GPR data indicates a significant improvement in the GPR image, good discrimination between the target reflection and the ground surface reflection, and better performance with reliable separation between them. However, at the same time the noise level slightly increases in field data, due to the wide bandwidth of the reference signal, which includes the higher-frequency components of noise. Using the ground-surface reflection as a reference signal we found that the pulse width could be compressed and the subsurface target reflection could be enhanced.

What can GPR tell us about cryoconite holes? 3D FDTD modeling, excavation and field GPR data

Cryoconite holes form on ice due to enhanced ablation around particles deposited on the surface, and are present in the ablation area of glaciers worldwide. Here we investigate the use of Ground Penetrating Radar (GPR) as a non-destructive method to monitor and map cryoconite holes. We compare GPR data obtained from the Jutulsessen blue ice area in Dronning Maud Land, Antarctica, with modeled GPR data. The modeled GPR response to cryoconite holes is numerically calculated by solving Maxwell's equations with a 3D Finite-Difference Time-Domain (FDTD) scheme. The model includes a realistic shielded bowtie antenna and dimensions and constituent parameters of cryoconite holes excavated in the field. We have performed what-if scenarios with controlled variation of single parameters. We show that GPR can be used to determine the horizontal extent, depth and whether a cryoconite hole is frozen or contains liquid water, information unavailable from visual surface inspection. The cryoconite thickness can, for completely frozen holes, be determined to within a 1/4 of the GPR center frequency wavelength. The exact water content is not readily extractable because the GPR response is influenced by many other factors such as: cryoconite thickness, shape and roughness, as well as antenna ground coupling.

Removal of ringing noise in GPR data by signal processing

Ringing is a common type of coherent noise in ground penetrating radar (GPR) data. When this kind of coherent noise is strong and is not properly removed, deeper structure may be completely masked. Ringing appears as nearly horizontal and periodic events, which are the most important features enabling us to remove the noise by signal processing. In this study, we have reviewed basic principles of various signal processing techniques to remove the ringing noise and compared their performances using field GPR data contaminated by severe ringing noise. The reviewed methods include background removal. f-k filtering, predictive deconvolution with filtering in wavenumber domain, and filtering by radon transform. Furthermore, it is shown that ringing can be successfully removed by the eigenimage filtering method, where GPR image is decomposed into eigenimages by singular value decomposition. This comparative analysis shows that the refined techniques are definitely more effective than the simple methods for the ringing noise removal with less distortion of GPR signals and each method has its own advantage as well as limitations. Moreover, preservation of the horizontally linear events from geological targets can be possible only through a kind of selective or local filtering such as the eigenimage filtering method.

Ground-penetrating radar theory and application of thin-bed offset-dependent reflectivity

Offset-dependent reflectivity or amplitude-variation-with-offset (AVO) analysis of ground-penetrating radar (GPR) data may improve the resolution of subsurface dielectric permittivity estimates. A horizontally stratified medium has a limiting layer thickness below which thin-bed AVO analysis is necessary. For a typical GPR signal, this limit is approximately 0.75 of the characteristic wavelength of the signal. Our approach to modeling the GPR thin-bed response is a broadband, frequency-dependent computation that utilizes an analytical solution to the three-interface reflectivity and is easy to implement for either transverse electric (TE) or transverse magnetic (TM) polarizations. The AVO curves for TE and TM modes differ significantly. In some cases, constraining the interpretation using both TE and TM data is critical. In two field examples taken from contaminated-site characterization data, we find quantitative thin-bed modeling agrees with the GPR field data and available characterization data.

Numerical simulation of antenna transmission and reception for crosshole ground-penetrating radar

Numerical models that account for realistic transmitter and receiver antenna behavior are necessary to develop waveform-based inversion methods for crosshole ground-penetrating radar (GPR) data. A challenge in developing such models is simulating the antennae in a computationally efficient manner so that inversions can be performed in a reasonable amount of time. We present an approach to efficiently simulate crosshole GPR transmission and reception in heterogeneous media. The core of our approach is a finite-difference time-domain (FDTD) solution of Maxwell's equations in 2D cylindrical coordinates. First, we determine the behavior of the current on a realistic GPR antenna in a borehole through detailed FDTD modeling of the antenna and its immediate surroundings. To model transmission and reception, we then replicate this antenna current behavior on a much-coarser grid using a superposition of point-electric-dipole source and receiver responses. Results obtained with our technique agree with analytical results, with numerical modeling results where the transmitter antenna and borehole are explicitly accounted for using a fine discretization, and with crosshole GPR field data.

Stochastic estimation of facies using ground penetrating radar data

Explicitly defining large-scale heterogeneity is a necessary step of groundwater model calibration if accurate estimates of flow and transport are to be made. In this work, neural networks are used to estimate radar facies probabilities from ground penetrating radar (GPR) images, yielding stochastic facies-based models that honour the large-scale architecture of the subsurface. For synthetic GPR images, a neural network was able to correctly identify radar facies with an accuracy of approximately 90%. Manual interpretation of a set of 450 MHz GPR field data from the Borden aquifer resulted in the identification of four radar facies. Of these, a neural network was able to identify two facies with an accuracy of near 80% and one with an accuracy of 44%. The neural network was not able to identify the fourth facies, likely due to the choice of defining facies characteristics. Sequential indicator simulation was used to generate facies realizations conditioned to the radar facies probabilities. Numerical simulations indicate that significant improvements in the prediction of solute transport are possible when GPR is used to constrain the facies model compared to using well data alone, especially when data are sparse.

Forward modeling of ground‐penetrating radar data using digitized outcrop images and multiple scenarios of water saturation

Simple petrophysical models and a sedimentologically interpreted outcrop photograph corresponding to the plane of a ground‐penetrating radar (GPR) survey are combined to create models for the simulation of GPR. This makes possible the comparison of GPR field data, synthetic GPR sections, and a lithology image. On the basis of this comparison the usefulness of the method for identifying hydrologically significant lithofacies and the sensitivity of the results to different subsurface conditions may be investigated. In particular, GPR simulations are performed for an outcrop model at three states of water saturation: uniformly drained (uniform residual saturation), nonuniformly saturated, and fully saturated. As predicted by reflection coefficient calculations, comparison among the synthetic simulations highlights the importance of the existing pore water distribution in determining the “visibility” of lithologic elements in GPR sections. Comparisons of the synthetic GPR sections with the field data show overall agreement, though the occurrence of various observed reflections depends on the presence and distribution of pore water. Conclusions are also drawn about extending outcrop analog‐derived results to investigations of real (fully saturated) aquifers.

Evaluation of Ground‐Penetrating Radar to Detect Free‐Phase Hydrocarbons in Fractured Rocks—Results of Numerical Modeling and Physical Experiments

AbstractThe suitability of common‐offset ground‐penetrating radar (GPR) to detect free‐phase hydrocarbons in bedrock fractures was evaluated using numerical modeling and physical experiments. The results of one‐ and two‐dimensional numerical modeling at 100 megahertz indicate that GPR reflection amplitudes are relatively insensitive to fracture apertures ranging from 1 to 4 mm. The numerical modeling and physical experiments indicate that differences in the fluids that fill fractures significantly affect the amplitude and the polarity of electromagnetic waves reflected by subhorizontal fractures. Air‐filled and hydrocarbon‐filled fractures generate low‐amplitude reflections that are in‐phase with the transmitted pulse. Water‐filled fractures create reflections with greater amplitude and opposite polarity than those reflections created by air‐filled or hydrocarbon‐filled fractures.The results from the numerical modeling and physical experiments demonstrate it is possible to distinguish water‐filled fracture reflections from air‐ or hydrocarbon‐filled fracture reflections, nevertheless subsurface heterogeneity, antenna coupling changes, and other sources of noise will likely make it difficult to observe these changes in GPR field data. This indicates that the routine application of common‐offset GPR reflection methods for detection of hydrocarbon‐filled fractures will be problematic. Ideal cases will require appropriately processed, high‐quality GPR data, ground‐truth information, and detailed knowledge of subsurface physical properties.Conversely, the sensitivity of GPR methods to changes in subsurface physical properties as demonstrated by the numerical and experimental results suggests the potential of using GPR methods as a monitoring tool. GPR methods may be suited for monitoring pumping and tracer tests, changes in site hydrologic conditions, and remediation activities.

Forensic GPR: finite-difference simulations of responses from buried human remains

Time domain 2.5-D finite-difference simulations of ground-penetrating radar (GPR) responses from models of buried human remains suggest the potential of GPR for detailed non-destructive forensic site investigation. Extraction of information beyond simple detection of cadavers in forensic investigations should be possible with current GPR technology. GPR responses are simulated for various body cross-sections with different depths of burial, soil types, soil moisture contents, survey frequencies and antenna separations. Biological tissues have high electrical conductivity so diagnostic features for the imaging of human bodies are restricted to the soil/skin interface and shallow tissue interfaces. A low amplitude reflection shadow zone occurs beneath a body because of high GPR attenuation within the body. Resolution of diagnostic features of a human target requires a survey frequency of 900 MHz or greater and an increment between recording stations of 10 cm or less. Depth migration focuses field GPR data into an image that reveals accurate information on the number, dimensions, locations and orientations of body elements. The main limitation on image quality is attenuation in the surrounding soil and within the body. 3-D imaging is also feasible.

Detection of welding in pyroclastic flows with ground penetrating radar: insights from field and forward modeling data

We investigate the potential of ground penetrating radar (GPR) as a tool to delineate welded portions of pyroclastic flows by testing interpretations of field GPR data with numerical modeling. Specifically, we test the hypothesis that regions of changing porosity with depth and regions of constant porosity are characterized by distinct signals in radargrams. We model the propagation of electromagnetic waves through pyroclastic flow deposits with vertical variations in porosity ( Φ). The actual Φ profiles are gradational but are represented in our models by a series of 1-cm-thick, homogeneous layers. Each layered porosity profile is converted into a layered K′ profile using an empirical law relating K′ to Φ of dry volcanic rocks that is based on laboratory measurements. The resulting synthetic traces indicate that moderate, gradational changes in welding produce multiple low amplitude crests and troughs rather than strong individual reflections. The lower the peak frequency of the source wavelet, the greater the amplitude of the signal generated and thus the greater the potential signal to noise ratio. Extremely high rates of change in porosity with depth produce distinct, strong reflections. Densely welded or unwelded portions, where porosity is relatively constant, produce sections of zero amplitude. These preliminary results suggest that GPR can be used to map the effects of welding in pyroclastic flows. Specifically, characteristic radar signals can be used to identify zones of changing degree of welding and zones of relatively constant degree of welding.

Recognizing surface scattering in ground‐penetrating radar data

Ground‐penetrating radar (GPR) data may show strong noise events as a result of scattering by surface objects on the ground or above the survey line. The relative strength of these events can be large in comparison to reflections from geologic features, because radar signals in the ground attenuate exponentially whereas signals that travel in the air attenuate geometrically. Migration of GPR field data from clastic and carbonate sequences in central Oklahoma distinguishes between scattered events and geologic events because the former are focused at the air‐wave velocity, while the latter are focused at the ground‐wave velocity. Forward modeling using locations of scatterers derived from migration confirms the presence of scattered events, and common midpoint (CMP) gathers are helpful in identifying surface scattering. Scattered events displayed at a horizontal/vertical scale of 1:1 are easily mistaken for subhorizontal, geologic reflections. Methods of recognizing scattered events and removing them, if possible, are therefore crucial to correct geological interpretation of GPR data.