Near Surface Geophysics - Current Issue

Numerical modelling of a ground‐penetrating radar (GPR) has been widely used for predicting and assessing its performance. As the transmitter and the receiver are the most essential components of a GPR system, an accurate representation of them should be included in a model. Simulating a real system is particularly challenging, especially when it comes to commercial GPR systems. A three‐dimensional model based on a 2000 MHz ‘palm’ antenna from Geophysical Survey Systems, Inc. (GSSI) is presented in this paper. The geometric features of the transducers were modelled via visual inspection, whereas their unknown dielectric properties were estimated using global optimizers in order to minimize the differences between real and synthetic measurements. In particular, the antenna was calibrated in free space and on top of a metal plate. Subsequently, the resulting model was successfully tested in various case studies to assess its performance. Models of two units of the same transducer were developed, showing that units of the same system in general are not identical. The results support the premise that global optimizers can be used to provide information on key aspects of the dielectric structure of the transducer and allow us to accurately model its behaviour in various environments.

Ground penetrating radar (GPR) is regulated regarding emission limits for ultra‐wideband in a number of jurisdictions. The definitions of these regulations employ concepts and terminology that are more suited to traditional narrow band radio transmitters. Further, the emissions limits were based on limited quantitative factual information and have resulted in stringent limitations on GPR technology advancement. Factual theoretical and experimental information on the emissions from actual GPR devices is not generally available, and the relationship with regulatory requirements is poorly understood by users. This information gap must be filled if a compelling argument for less stringent emissions levels is to be mounted in the future. Moreover, the current regulations have the potential to trigger further review of emission limits in the future which could be detrimental to the use of GPR. In this paper, we present the basic steps entailed in translating impulse time‐domain GPR instrument behaviour into ‘regulatory’ parameters. To achieve this, we also employ three‐dimensional finite‐difference time‐domain numerical modelling to simulate the transient electromagnetic field variation around dipole antennas placed on the surface of a half‐space or at a height over it to illustrate the dependency on sensor height and ground permittivity. The ultimate goal is to establish the foundation for more sensible rule making, if and when, the regulatory standards come under scrutiny for revision and further user understanding.

As the transmitter and receiver (Tx and Rx, respectively) are located in close proximity during a typical ground‐penetrating radar (GPR) survey, the powerful signal generated by the Tx and which is then recorded by the Rx at various time delays, can be saturated at early times (i.e., this is the direct wave (DW) signal reaching the Rx). This often causes the masking of shallow targets, complicating data interpretation. In this study, our aim is to examine the spatial distribution of the electromagnetic signals around the Tx, attempting to locate areas where the DW becomes minimum, whereas the signal strength from subsurface targets (i.e., reflected wave – RW) remains ideally unchanged. The position of these local minima in the DW signal could give rise to advantageous Tx–Rx configurations, where clear reflections from subsurface targets lying at shallow depths can be obtained with the least possible involvement of the DW. To perform such a study, we carried out static field measurements over a flat lying reflector as well as numerical simulations in a reflection, common‐offset mode around a transmitting antenna. In the field, we also collected wide‐angle reflection–refraction data to determine the GPR wave velocity in the uppermost layer. GPR signals were recorded by the Rx around the Tx in three concentric circles of various radii (i.e., varying the Tx/Rx separation), using a specific angular step and varying the Tx/Rx polarization each time. The synthetic data were produced using a three‐dimensional finite‐difference time‐domain modelling tool. Field and numerically simulated data were analysed and compared to study the behaviour of both the DW and RW events around the Tx when changing the Tx/Rx distance, their respective angular position, as well as their relative polarization/orientation.

Timely and accurate detection of water pipe leakage is critical to preventing the loss of freshwater and predicting potential hazards induced by the change in underground water conditions, thereby developing mitigation strategies to improve the resilience of pipeline infrastructure. Ground‐penetrating radar (GPR) has been widely applied to investigating ground conditions and detecting pipe leakage. However, due to uncertainties of complex underground environments and time‐lapse change, a proper interpretation of GPR data has been a challenging task. This paper aims to leverage hydromechanical (HM) modelling to predict electromagnetic (EM) responses of water leakage detection in diverse leakage cases. A high‐fidelity 3D digital model of an actual pipeline network, hosting pipes with various sizes and materials, was reconstructed to represent the complex geometry and various mediums. The interoperability between the digital model and the numerical models utilized in HM and EM simulations was improved to better capture the irregular pipelines. Based on Kriging interpolation and the volumetric complex refractive index model, a linking technique was employed to replicate material heterogeneity caused by water intrusion. Thus, a framework was developed to accommodate the interoperability among digital modelling, HM modelling and finite‐difference time‐domain forward modelling. Moreover, sensitivity studies were conducted to evaluate the influences of different time stages, leak positions and pipe types on GPR responses. In GPR B‐scans, the presence of hyperbolic motion and horizontal reflections serve as indicators to estimate the location and scale of water leakage. Specifically, a downward‐shifting hyperbola indicates that the pipeline is submerged by leaked water, whereas the emergence of horizontal reflection is linked to the wetting front of saturated areas. The developed framework can be expanded for complicated applications, such as unknown locations and unforeseen failure modes of pipelines. It will increase the efficiency and accuracy of traditional interpretations of GPR‐based water leakage detection and thus enable automated interpretations by data‐driven methods.

Ground‐penetrating radar is an effective tool for detecting landmines and improvised explosive devices, but its performance is strongly influenced by subsurface properties as well as the characteristics of the target. To complement or replace labour‐intensive experiments on test sites, cost‐efficient electromagnetic wave propagation simulations using the finite‐difference time‐domain method are being increasingly used. However, to obtain realistic synthetic data, accurate modelling of signal alteration caused by dispersion, scattering from soil material, target contrast, shape, and inner setup, as well as the coupling effects of the antenna to the ground is required. In this study, we present a detailed three‐dimensional model of a shielded ground‐penetrating radar antenna applied to various scenarios containing metallic and non‐metallic targets buried in different soils. The frequency‐dependent intrinsic material properties of soil samples were measured with the coaxial transmission‐line technique, while a discrete random media was used to implement the heterogeneity of a gravel based on its grain‐size distribution. Our simulations show very good agreement with experimental validation data collected under controlled conditions. We accurately reproduce the amplitude, frequency, and phase of target signals, the subsurface background noise, antenna crosstalk and associated interference with target signals, and the effect of antenna elevation. The approach allows for a systematic investigation of the effects of soil, target, and sensor properties on detection performance, providing insight into novel and complex ground‐penetrating radar scenarios and the potential for a wide range of simulation possibilities for demining with ground‐penetrating radar. These investigations have the potential to improve the safety and effectiveness of landmine and improvised explosive device detection in the future, such as building a database for training deminers or developing automatic signal pattern recognition algorithms.

Ground penetrating radar (GPR) is a commonly used tool for railway trackbed inspection due to its ability to collect information about subsurface materials at high resolution and high speed. Although GPR recording systems allow for the collection of vast quantities of data (hundreds of kilometres per day), accurate ground truth information is difficult to obtain. Models of trackbed can be used to generate synthetic radargrams to provide a better understanding and predictability of GPR responses to a wide range of trackbed conditions. In this research, we produced models of ballast using randomly shaped 3D particles, with a range of particle size distributions to represent various stages of ballast breakdown. Additionally, void spaces are partially filled with a constant dielectric material to represent ballast contamination. We used gprMax to simulate the GPR response for a 2 GHz horn antenna over the trackbed models. These simulations resulted in radargrams that are visually indistinct from real recorded data in known conditions. These radargrams, along with their formative models, have provided valuable insights into how variations in trackbed conditions can impact GPR data.

Scattering is often detected when ground‐penetrating radar (GPR) surveys are performed on glaciers at different latitudes and in various environments. This event is often seen as an undesirable feature on data, but it can be exploited to quantify the debris content in mountain glaciers through a dedicated scattering inversion approach. At first, we considered the possible variables affecting the scattering mechanisms, namely the dielectric properties of the scatterers, their size, shape and quantity, as well as the wavelength of the electromagnetic (EM) incident field to define the initial conditions for the inversion. Each parameter was independently evaluated with forward modelling tests to quantify its effect in the scattering mechanism. After extensive tests, we found that the dimension and the amount of scatterers are the crucial parameters. We further performed modelling randomizing the scatterer distribution and dimension, critically evaluating the stability of the approach and the complexity of the models. After the tests on synthetic data, the inversion procedure was applied to field datasets, acquired on the Eastern Gran Zebrù glacier (Central Italian Alps). The results show that even a low percentage of debris can produce high scattering. The proposed methodology is quite robust and able to provide quantitative estimates of the debris content within mountain glaciers in different conditions.

Fracture curvature has been observed from the millimetre to the kilometre scales. Nevertheless, characterizing curvature remains challenging due to data sparsity and geometric ambiguities. As a result, most numerical models often assume planar fractures to ease computations. To address this limitation, we present a novel approach for inferring fracture geometry from travel‐time data of electromagnetic or seismic waves. Our model utilizes co‐kriging interpolation of control points in a three‐dimensional surface mesh to simulate fracture curvature effectively, resulting in an unstructured triangular grid. We then refine the fracture surface into a structured grid with equidistant elements so that both small‐scale heterogeneities and large‐scale curvature can be modelled. To constrain the fracture geometry, we perform a deterministic travel‐time inversion to optimally place these control points. We validate our methodology with synthetic data and address its limitations. Finally, we infer the geometry of a large (more than 200 m) fracture observed in single‐hole ground‐penetrating radar field data. The fracture surface closely agrees with borehole televiewer observations and is also constrained far from the boreholes. Our modelling approach can be trivially adapted to multi‐offset ground‐penetrating radar or active seismic data.

Determining ground‐penetrating radar (GPR) velocity has always been a critical problem. The GPR velocity estimation method based on common midpoint (CMP) data has been widely used because of its simplicity. However, we found that in sediment investigation and soil assessment, transversal heterogeneity is universal, which violates the basic assumption of velocity estimation through CMP data. Due to the rapid change of underground media and the limitation of the scope of some surveying areas, the CMP survey line will inevitably be selected in the area where the velocity changes laterally, making it difficult to obtain accurate velocity. To address this problem, we propose a velocity correction method. First, we determined the characteristics of CMP data and the corresponding velocity spectra acquired in transversely heterogeneous media through numerical simulations. Subsequently, we found that the simulated CMP data could determine the location of changes in the underground medium, and that the velocity obtained from the semblance analysis could be corrected according to the location where the medium changes laterally. We then used models wherein the thickness, relative permittivity and proportion of abnormal parts varied independently or simultaneously to verify the proposed velocity correction method. The results show that our method can control the GPR velocity error within 3.44%, and the precision is about 0.002 m/ns. Finally, we conducted a sediment investigation experiment on a channel bar in the lower reaches of the Yarlung Zangbo River. We determined the interface at which the sediment changed transversely and obtained the corresponding electromagnetic velocity using the proposed method. This study provides a reliable method for determining the GPR velocity in transversal heterogeneous media, which is of great significance for various practical applications.

Electromagnetic wave velocity in ground‐penetrating radar (GPR) constant offset data can be estimated via the diffraction hyperbola fitting method. This method is applicable when radargrams contain diffraction events (hyperbolic patterns) caused by scatters in the host smaller or equal to the dominant wavelength. An alternative method for velocity estimation, if no intrusive information is available for a direct correlation, requires the collection of multi‐offset data. The method is quite common for broad geophysical applications; however, it seems not to be fully utilized for engineering applications, such as slabs/walls where thickness estimation and depth of the embedded features are critical requirements for structural assessments. This method would also overcome the limitations in velocity calibration in environments with no hyperbolic signal signatures. The aim of this study is to explore multi‐offset high‐frequency GPR applications, specifically the wide‐angle reflection and refraction method, for structural engineering, to understand whether it is feasible, possible limitations, and advantages. Numerical models reproducing reinforced concrete elements and a cavity wall were analysed to understand the wave behaviour and predict the response prior to testing on real cases. The main purpose is to explore how reinforcing bars can affect the velocity spectra derived from semblance analysis and what the response would be in a case of multi‐layered structure with increasing velocity with depth (cavity wall). The comparison with real cases showed that, despite some intrinsic limitations, high‐frequency multi‐offset approach could be part of standard workflow for all those surveys where no other velocity estimation method is feasible.