Time-lapse Ground-penetrating Radar Research Articles

Comparison of Time-Lapse Ground-Penetrating Radar and Electrical Resistivity Tomography Surveys for Detecting Pig (Sus spp.) Cadaver Graves in an Australian Environment

Comparison of Time-Lapse Ground-Penetrating Radar and Electrical Resistivity Tomography Surveys for Detecting Pig (Sus spp.) Cadaver Graves in an Australian Environment

Time-Lapse Ground Penetrating Radar (GPR) Imaging of Used Engine Oil Contamination.

Time-Lapse Ground Penetrating Radar (GPR) was employed to study used engine oil (UEO) contamination of sandy environment in laboratory setting. GPR is a near-surface geophysical methods that uses electromagnetic fields to provide image of the dielectric properties of earth materials to detect structures and changes in materials properties within the subsurface. This research aimed to detect, monitor and map the migration of UEO contaminant in sand. The results of this study revealed that the migration of the UEO contamination with a homogeneously laid sand is non-uniform. UEO plumes were identified as high amplitude signals with enhanced reflectivity. There was a progressive decrease in GPR signal amplitudes (reflection reduction) within the contaminated area of the tank with time. This attenuation of GPR signal amplitudes was interpreted as caused by the evaporation of some portion of the UEO in the vadose zone as a result of temperature increase in time and due to the occurrence of UEO biodegradation. The time-lapse GPR proved to be an effective technique for detecting, monitoring, and mapping UEO migration within sand tank in laboratory setting.

Advanced Time-Lapse Ground-Penetrating Radar Data Processing for Quantitatively Monitoring of Small-Scale Fluid Infiltration

Advanced Time-Lapse Ground-Penetrating Radar Data Processing for Quantitatively Monitoring of Small-Scale Fluid Infiltration

Continuous Automatic Estimation of Volumetric Water Content Profile During Infiltration Using Sparse Multi-Offset GPR Data

Ground-penetrating radar (GPR) is a non-destructive and non-invasive geophysical survey method that has been used to characterize soil volumetric water content (VWC) dynamics. An array antenna GPR system was used to collect nearly seamless, time-lapse multi-offset GPR data during an in-situ infiltration test on sand dunes with limited traces. Because the data volume was significant, an approach was utilized to automatically determine electromagnetic wave velocities from sparse common midpoint (CMP) data using standard velocity analysis, such as semblance analysis. The objective of this study was to develop a methodology that allows one to automatically perform velocity analysis by interpolating sparse CMP data obtained with the array GPR system. The proposed method determined the optimal normal moveout velocity values and the removal range of the F-K zone pass filter that minimized errors between the original and interpolated CMP data using leave-one-out cross-validation (LOOCV). After interpolating the sparse CMP data with the F-K zone pass filter, semblance analysis was used to determine the time-lapse velocity structure of the soil profile during water infiltration. The velocity data were converted to VWC data based on the Topp equation, which relates the soil VWC to the soil dielectric constant. The proposed method was tested using CMP data obtained via numerical simulation and experiments. The VWC profile from the proposed approach matched well with the independently observed VWC profiles obtained from an invasive probe-type soil moisture sensor.

Fast Segmentation and Dynamic Monitoring of Time-Lapse 3D GPR Data Based on U-Net

As the amount of ground-penetrating radar (GPR) data increases significantly with the high demands of nondestructive detection methods under urban roads, a method suitable for time-lapse data dynamic monitoring should be developed to quickly identify targets on GPR profiles and compare time-lapse datasets. This study conducted a field experiment aiming to monitor one backfill pit using three-dimensional GPR (3D GPR), and the time-lapse data collected over four months were used to train U-Net, a fast neural network based on convolutional neural networks (CNNs). Consequently, a trained network model that could effectively segment the backfill pit from inline profiles was obtained, whose Intersection over Union (IoU) was 0.83 on the test dataset. Moreover, segmentation masks were compared, demonstrating that a change in the southwest side of the backfill pit may exist. The results demonstrate the potential of machine learning algorithms in time-lapse 3D GPR data segmentation and dynamic monitoring.

Coupled full-waveform inversion of horizontal borehole ground penetrating radar data to estimate soil hydraulic parameters: A synthetic study

Coupled inversion is a promising technique for determining soil hydraulic properties from time-lapse geophysical measurements. In this inversion approach, a hydrological model is coupled with ground penetrating radar (GPR) forward modelling to avoid interpretation errors from data processing. In this study, a workflow for coupled GPR full-waveform inversion (CFWI) is proposed that combines the benefits of coupled inversion and full-waveform inversion (FWI) to estimate soil hydraulic properties from time-lapse horizontal borehole GPR measurements. In particular, a synthetic modelling study is presented that compares the performance of coupled inversion of full waveforms and first arrival time data from zero-offset profile (ZOP) borehole measurements obtained during an infiltration event for estimating hydraulic parameters and the thickness of the first layer for a 2-layer soil profile. It was found that the thickness of the first layer could be more accurately estimated by CFWI because of the additional information contained in reflected and refracted waves from the air–soil layer boundary. Furthermore, the hydraulic parameters estimated by the coupled inversion of GPR travel times slightly deviated from true values and showed a relatively large uncertainty, whereas the results of CFWI precisely matched the known water retention and hydraulic conductivity functions. Despite these promising results, several challenges should be solved before CFWI can be applied to experimental GPR data. First, conducting CFWI needs accurate conceptual setups for the hydro(geo-)logical model. Furthermore, a robust approach should be developed to accurately estimate an effective source wavelet from the experimental ZOP data, and a more sophisticated hydrological modelling approach has to be considered to better estimate the distribution of soil electrical conductivity during the infiltration event. Finally, the accuracy and efficiency of current GPR modelling methods may need to be improved.

Full-Waveform Inversion of Time-Lapse Crosshole GPR Data Using Markov Chain Monte Carlo Method

Crosshole ground-penetrating radar (GPR) is an important tool for a wide range of geoscientific and engineering investigations, and the Markov chain Monte Carlo (MCMC) method is a heuristic global optimization method that can be used to solve the inversion problem. In this paper, we use time-lapse GPR full-waveform data to invert the dielectric permittivity. An inversion based on the MCMC method does not rely on an accurate initial model and can introduce any complex prior information. Time-lapse ground-penetrating radar has great potential to monitor the properties of a subsurface. For the time-lapse inversion, we used the double difference method to invert the time-lapse target area accurately and full-waveform data. We propose a local sampling strategy taking advantage of the a priori information in the Monte Carlo method, which can sample only the target area with a sequential Gibbs sampler. This method reduces the calculation and improves the inversion accuracy of the target area. We have provided inversion results of the synthetic time-lapse waveform data that show that the proposed method significantly improves accuracy in the target area.

Coupling time-lapse ground penetrating radar surveys and infiltration experiments to characterize two types of non-uniform flow

Understanding linkages between heterogeneous soil structures and non-uniform flow is fundamental for interpreting infiltration processes and improving hydrological simulations. Here, we utilized ground-penetrating radar (GPR) as a non-invasive technique to investigate those linkages and to complement current traditional methods that are labor-intensive, invasive, and non-repeatable. We combined time-lapse GPR surveys with different types of infiltration experiments to create three-dimensional (3D) diagrams of the wetting dynamics. We carried out the GPR surveys and validated them with in situ observations, independent measurements and field excavations at two experimental sites. Those sites were selected to represent different mechanisms that generate non-uniform flow: (1) preferential water infiltration initiated by tree trunk and root systems; and (2) lateral subsurface flow due to soil layering. Results revealed links between different types of soil heterogeneity and non-uniform flow. The first experimental site provided evidence of root-induced preferential flow paths along coarse roots, emphasizing the important role of coarse roots in facilitating preferential water movement through the subsurface. The second experimental site showed that water infiltrated through the restrictive layer mainly following the plant root system. The presented approach offers a non-invasive, repeatable and accurate way to detect non-uniform flow.

Four-dimensional tracer flow reconstruction in fractured rock through borehole ground-penetrating radar (GPR) monitoring

Abstract. Two borehole ground-penetrating radar (GPR) surveys were conducted during saline tracer injection experiments in fully saturated crystalline rock at the Grimsel Test Site in Switzerland. The saline tracer is characterized by an increased electrical conductivity in comparison to formation water. It was injected under steady-state flow conditions into the rock mass that features sub-millimeter fracture apertures. The GPR surveys were designed as time-lapse reflection GPR from separate boreholes and a time-lapse transmission survey between the two boreholes. The local increase in conductivity, introduced by the injected tracer, was captured by GPR in terms of reflectivity increase for the reflection surveys, and attenuation increase for the transmission survey. Data processing and difference imaging was used to extract the tracer signal in the reflection surveys, despite the presence of multiple static reflectors that could shadow the tracer reflection. The transmission survey was analyzed by a difference attenuation inversion scheme, targeting conductivity changes in the tomography plane. By combining the time-lapse difference reflection images, it was possible to reconstruct and visualize the tracer propagation in 3D. This was achieved by calculating the potential radially symmetric tracer reflection locations in each survey and determining their intersections, to delineate the possible tracer locations. Localization ambiguity imposed by the lack of a third borehole for a full triangulation was reduced by including the attenuation tomography results in the analysis. The resulting tracer flow reconstruction was found to be in good agreement with data from conductivity sensors in multiple observation locations in the experiment volume and gave a realistic visualization of the hydrological processes during the tracer experiments. Our methodology was demonstrated to be applicable for monitoring tracer flow and transport and characterizing flow paths related to geothermal reservoirs in crystalline rocks, but it can be transferred in a straightforward manner to other applications, such as radioactive repository monitoring or civil engineering projects.

Influence of water content investigation on GPR wave attenuation for early age concrete in natural air-drying condition

In this study, an efficient application to evaluate water content of concrete in a non-destructive way in natural air-drying conditions by time-lapse Ground-penetrating radar (GPR) measurements is described. This was achieved by carrying out time-lapse GPR measurements on a concrete block with 2 GHz shielded antenna in 24 measurement days between day three and the 150th day of concrete casting. The characteristics of the electromagnetic (EM) wave are directly influenced by the presence of water content in a material. Change in water content results in variations in dielectric properties, including dielectric permittivity and conductivity. The study focused on variation of EM wave attenuation, which is related to direct and reflected wave amplitudes due to decrease of water content in the sample. In order to obtain a reflected wave a reinforced bar was embedded at 10 cm depth. The ratio of the direct wave and reflected wave on each measurement day decreased with respect to the reflection amplitude, due to concrete desiccation. These results are a guide to determining the relationship between volumetric water content (VWC) and EM wave attenuation. The method has significant potential on freshly produced young concrete samples to monitor their quality. The suggested method may also have potential for practical on-site studies to determine possible corrosion risk due to water intrusion.

Computing Localized Breakthrough Curves and Velocities of Saline Tracer from Ground Penetrating Radar Monitoring Experiments in Fractured Rock

Solute tracer tests are an established method for the characterization of flow and transport processes in fractured rock. Such tests are often monitored with borehole sensors which offer high temporal sampling and signal to noise ratio, but only limited spatial deployment possibilities. Ground penetrating radar (GPR) is sensitive to electromagnetic properties, and can thus be used to monitor the transport behavior of electrically conductive tracers. Since GPR waves can sample large volumes that are practically inaccessible by traditional borehole sensors, they are expected to increase the spatial resolution of tracer experiments. In this manuscript, we describe two approaches to infer quantitative hydrological data from time-lapse borehole reflection GPR experiments with saline tracers in fractured rock. An important prerequisite of our method includes the generation of GPR data difference images. We show how the calculation of difference radar breakthrough curves (DRBTC) allows to retrieve relative electrical conductivity breakthrough curves for theoretically arbitrary locations in the subsurface. For sufficiently small fracture apertures we found the relation between the DRBTC values and the electrical conductivity in the fracture to be quasi-linear. Additionally, we describe a flow path reconstruction procedure that allows computing approximate flow path distances using reflection GPR data from at least two boreholes. From the temporal information during the time-lapse GPR surveys, we are finally able to calculate flow-path averaged tracer velocities. Our new methods were applied to a field data set that was acquired at the Grimsel Test Site in Switzerland. DRBTCs were successfully calculated for previously inaccessible locations in the experimental rock volume and the flow path averaged velocity field was found to be in good accordance with previous studies at the Grimsel Test Site.

Sequential and coupled inversion of horizontal borehole ground penetrating radar data to estimate soil hydraulic properties at the field scale

Horizontal borehole ground penetrating radar (GPR) measurements can provide valuable information on soil water content (SWC) dynamics in the vadose zone, and hence show potential to estimate soil hydraulic properties. In this study, the performance of both sequential and coupled inversion workflows to obtain soil hydraulic properties from time-lapse horizontal borehole GPR data obtained during an infiltration experiment were compared using a synthetic modelling study and the analysis of actual field data. The sequential inversion using the vadose zone flow model HYDRUS-1D directly relied on SWC profiles determined from the travel time of GPR direct waves using the straight-wave approximation. The synthetic modelling study showed that sequential inversion did not provide accurate estimates of the soil hydraulic parameters due to interpretation errors in the estimated SWC near the infiltration front and the ground surface. In contrast, the coupled inversion approach, which combined HYDRUS-1D with a forward model of GPR wave propagation (gprMax3D) and GPR travel time information, provided accurate estimates of the hydraulic properties in the synthetic modelling study. The application of the coupled inversion approach to measured borehole GPR data also resulted in plausible estimates of the soil hydraulic parameters. It was concluded that coupled inversion should be preferred over sequential inversion of time-lapse horizontal borehole GPR data in the presence of strong SWC gradients that occur during infiltration events.

On the usage of diffractions in ground-penetrating radar reflection data: Implications for time-lapse gas migration monitoring

Time-lapse ground-penetrating radar (GPR) measurements are used to image/monitor, for example, water infiltration, water table changes, and fluid/gas flow patterns. Although crosshole GPR is often preferred over surface-reflection GPR in such studies, its application is limited by the selected borehole geometry, which may be difficult to define in an optimal way, especially in experiments in which flow pathways are difficult to predict. Surface-reflection GPR data sets are generally faster to collect over relatively large areas and are therefore more efficient for covering the volume when a fast-moving tracer (e.g., gas) may infiltrate a heterogeneous subsurface medium. We have used a diffraction imaging approach on time-lapse surface-reflection GPR data to detect changes in radar wave velocity associated with gas (CO2) injected into a heterogeneous chalk succession. We initially test and evaluate the diffraction imaging approach on synthetic GPR data. Afterward, we apply the methodology to time-lapse GPR field data, and we evaluate the robustness of using information from diffractions in light of the obtained data quality. The synthetic tests indicate that diffractions provide essential information for delimiting the area affected by gas in the heterogeneous chalk section studied. Our field experiment shows that using the diffraction information alone allows for detection of gas-affected zones and, therefore, potential flow characteristics of gas movement. We infer that the CO2 flow patterns in our study most likely are determined by small-scale fractures rather than the porosity/permeability of the rock matrix. Moreover, the approach used may serve as an initial study for future more targeted experiments or for further detail-retrieving full-waveform inversion.

Time-lapse ground penetrating radar difference reflection imaging of saline tracer flow in fractured rock

The characterization of flow and transport processes in fractured rock is challenging because they cannot be observed directly and hydrologic tests can only provide sparse and local data. Time-lapse ground penetrating radar (GPR) can be a valuable tool to monitor such processes in the subsurface, but it requires highly reproducible data. As part of a tracer injection experiment at the Grimsel Test Site (GTS) in Switzerland, borehole reflection GPR data were acquired in a time-lapse survey to monitor saline tracer flow through a fracture network in crystalline rock. Because the reflections from the tracer in the sub-mm fractures appear extremely weak, a differencing approach has been necessary to identify the tracer signal. Furthermore, several processing steps and corrections had to be applied to meet the reproducibility requirements. These steps include (1) single-trace preprocessing, (2) temporal trace alignment, (3) correction of sampling rate fluctuations, (4) spatial trace alignment, (5) spike removal, and (6) postprocessing procedures applied to the difference images. This allowed successful tracer propagation monitoring with a clear signal that revealed two separate tracer flow paths. The GPR results are confirmed by conductivity meters that were placed in boreholes in the GTS. If sufficient data processing is applied, GPR is shown to be capable of resolving tracer flow through sub-mm aperture fractures by difference reflection imaging even in challenging surroundings where many reflectors are present.

Ground-penetrating radar monitoring of fast subsurface processes

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.

Detecting infiltrated water and preferential flow pathways through time-lapse ground-penetrating radar surveys

The objective of this paper was to identify the incidence and extent of preferential flow at two experimental areas located in Lyon, France. We used time-lapse ground-penetrating radar (GPR) surveys in conjunction with automatized single-ring infiltration experiments to create three-dimensional (3D) representations of infiltrated water. In total we established three 100 cm × 100 cm GPR grids and used differenced radargrams from pre- and post-infiltration surveys to detect wetting patterns. The analyzed time-lapse GPR surveys revealed the linkage between nonuniform flow and heterogeneous soil structures and plant roots. At the first experimental area, subsurface coarse gravels acted as capillary barriers that concentrated flow into narrow pathways via funneled flow. At the second experimental area, the interpolated 3D patterns closely matched direct observation of dyed patterns, thereby validating the applied protocol. They also highlighted the important role of plant roots in facilitating preferential water movement through the subsurface. The protocol presented in this study represents a valuable tool for improving the hydraulic characterization of highly heterogeneous soils, while also alleviating some of the excessive experimental efforts currently needed to detect preferential flow pathways in the field.

Reflection tomography of time-lapse GPR data for studying dynamic unsaturated flow phenomena

Abstract. Ground-penetrating radar (GPR) reflection tomography algorithms allow non-invasive monitoring of water content changes resulting from flow in the vadose zone. The approach requires multi-offset GPR data that are traditionally slow to collect. We automate GPR data collection to reduce the survey time significantly, thereby making this approach to hydrologic monitoring feasible. The method was evaluated using numerical simulations and laboratory experiments that suggest reflection tomography can provide water content estimates to within 5 % vol vol−1–10 % vol vol−1 for the synthetic studies, whereas the empirical estimates were typically within 5 %–15 % of measurements from in situ probes. Both studies show larger observed errors in water content near the periphery of the wetting front, beyond which additional reflectors were not present to provide data coverage. Overall, coupling automated GPR data collection with reflection tomography provides a new method for informing models of subsurface hydrologic processes and a new method for determining transient 2-D soil moisture distributions.

Subsurface Diagnosis With Time-Lapse GPR Slices and Change Detection Algorithms

This article explores the capability of applying time-lapse ground penetrating radar (GPR) data to investigate the health condition of an urban subsurface. A workflow is proposed to semi-automatically extract changes from time-lapse GPR C-scans. The developed workflow consists of two main steps, in which the first step is image registration and intensity normalization. The workflow uses benchmark points on the ground to normalize the global intensity of time-lapse GPR C-scans. The second step classifies pixels into change or unchanged group. Two kinds of information are considered to construct two difference-maps: changes in the image intensity and the object structure. K-means clustering is responsible for extracting pixels that possess both intensity changes and object structure changes – where potential subsurface defects most likely occurred. The workflow was verified by a site experiment, and the area of excavation with pipe replacement was successfully identified. The performance of the proposed workflow was promising in excluding small and random scattering noise, which was the main challenge in a time-lapse GPR survey. The article serves as a prototype and demonstrates the feasibility and necessity of conducting temporal diagnosis on the subsurface structure.

Preferential flow through shallow fractured bedrock and a 3D fill-and-spill model of hillslope subsurface hydrology

The role of preferential flow through unsaturated saprock (fractured bedrock with weathering restricted to fracture margins) in hillslope hydrology remains inadequately described. To address this issue, ground-penetrating radar (GPR), controlled infiltration, and high-frequency subsurface moisture monitoring were integrated to characterize saprock preferential flow (SPF) in the Susquehanna Shale Hills Critical Zone Observatory in Pennsylvania, U.S.A. In a planar hillslope with shallow fractured shale bedrock (starting at 0.1–0.3 m below ground), two pulses of water (79.5 L in total) were released followed by time-lapse GPR surveys. Differentiating GPR images collected before and after infiltration revealed lateral SPF in the direction of bedding plane fractures near the infiltration trench but with limited development of SPF down gradient along the hillslope. This was confirmed by soil and saprock moisture monitoring at a soil pit (0.2 m downslope of the GPR grid) where only one out of fifteen probes responded to the controlled infiltration. Lateral SPF frequently occurred at the GPR grid during a 24-day period with ten rainfall events, especially under the wet initial conditions. Additional infiltration experiments in a convex hillslope and a nearby bare slope with exposed saprock demonstrated the impact of fracture patterns on the routing of SPF. Three types of SPF in hillslope hydrology were identified, including (1) vertical percolation, (2) exfiltration from saprock to soil, and (3) stormwater transported downslope from planar and convex hillslopes to concave hillslopes. A 3D fill-and-spill model is proposed for the study site and similar areas that recognizes the importance of subsurface flow networks, with shallow saprock and concave hillslopes as essential controls of hillslope subsurface flow.

Soil hydraulic material properties and layered architecture from time-lapse GPR

Abstract. Quantitative knowledge of the subsurface material distribution and its effective soil hydraulic material properties is essential to predict soil water movement. Ground-penetrating radar (GPR) is a noninvasive and nondestructive geophysical measurement method that is suitable to monitor hydraulic processes. Previous studies showed that the GPR signal from a fluctuating groundwater table is sensitive to the soil water characteristic and the hydraulic conductivity function. In this work, we show that the GPR signal originating from both the subsurface architecture and the fluctuating groundwater table is suitable to estimate the position of layers within the subsurface architecture together with the associated effective soil hydraulic material properties with inversion methods. To that end, we parameterize the subsurface architecture, solve the Richards equation, convert the resulting water content to relative permittivity with the complex refractive index model (CRIM), and solve Maxwell's equations numerically. In order to analyze the GPR signal, we implemented a new heuristic algorithm that detects relevant signals in the radargram (events) and extracts the corresponding signal travel time and amplitude. This algorithm is applied to simulated as well as measured radargrams and the detected events are associated automatically. Using events instead of the full wave regularizes the inversion focussing on the relevant measurement signal. For optimization, we use a global–local approach with preconditioning. Starting from an ensemble of initial parameter sets drawn with a Latin hypercube algorithm, we sequentially couple a simulated annealing algorithm with a Levenberg–Marquardt algorithm. The method is applied to synthetic as well as measured data from the ASSESS test site. We show that the method yields reasonable estimates for the position of the layers as well as for the soil hydraulic material properties by comparing the results to references derived from ground truth data as well as from time domain reflectometry (TDR).