A strategy for the determination of the dielectric permittivity of a lossy soil exploiting GPR surface measurements and a cooperative target

In this paper we deal with an indirect measure of the dielectric permittivity of the soil starting from GPR surface data collected on a buried “cooperative” target, meant as an object buried on purpose and whose extent is known a-priori. This target is exploited in order to achieve, from its image obtained from a suitable GPR data processing, an indirect measure of the dielectric permittivity of the embedding soil. GPR data processing is based on a linear microwave tomographic approach funded on the Born Approximation. Using this Born approach on two-dimensional inversion tests, we investigate the effect of the soil's electrical conductivity and permittivity on this indirect measure and demonstrate that the electrical field scattered by a spot-like buried object permits an accurate estimation of the soil permittivity even when no information of the soil conductivity is available.     

Application of the Brewster angle to quantify the dielectric properties of ground ice formations

Previous studies of ground ice using moveout type ground-penetrating radar (GPR) surveys indicate that the dielectric permittivity can constrain the type of ground ice present in the subsurface. Due to the high-loss nature of the active layer over permafrost targets, however, the signal strength of GPR signals is often insufficient to resolve the basal boundary required for determining the dielectric permittivity of an underlying unit. We apply a non-conventional antenna orientation and post-processing method to determine the dielectric permittivity of the unit underlying the lowest resolvable boundary. We conduct moveout surveys using a 450 MHz GPR with collinear parallel oriented antennas on two adjacent ground ice formations in the region of Thomas Lee Inlet, Devon Island, Nunavut. We exploit the Brewster angle to calculate the approximate dielectric permittivity of ground ice formations below the active layer. The results agree within 1 dielectric unit with on-ice permittivity measurements made during a complementary study of the site.     

Soil moisture estimation using tomographic ground penetrating radar in a MCMC–Bayesian framework

In this study, we focus on a hydrogeological inverse problem specifically targeting monitoring soil moisture variations using tomographic ground penetrating radar (GPR) travel time data. Technical challenges exist in the inversion of GPR tomographic data for handling non-uniqueness, nonlinearity and high-dimensionality of unknowns. We have developed a new method for estimating soil moisture fields from crosshole GPR data. It uses a pilot-point method to provide a low-dimensional representation of the relative dielectric permittivity field of the soil, which is the primary object of inference: the field can be converted to soil moisture using a petrophysical model. We integrate a multi-chain Markov chain Monte Carlo (MCMC)–Bayesian inversion framework with the pilot point concept, a curved-ray GPR travel time model, and a sequential Gaussian simulation algorithm, for estimating the dielectric permittivity at pilot point locations distributed within the tomogram, as well as the corresponding geostatistical parameters (i.e., spatial correlation range). We infer the dielectric permittivity as a probability density function, thus capturing the uncertainty in the inference. The multi-chain MCMC enables addressing high-dimensional inverse problems as required in the inversion setup. The method is scalable in terms of number of chains and processors, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. The proposed inversion approach can successfully approximate the posterior density distributions of the pilot points, and capture the true values. The computational efficiency, accuracy, and convergence behaviors of the inversion approach were also systematically evaluated, by comparing the inversion results obtained with different levels of noises in the observations, increased observational data, as well as increased number of pilot points.     

Simulation for ground penetrating radar (GPR) study of the subsurface structure of the Moon

Ground penetrating radar (GPR) is currently within the scope of China's Chang-E 3 lunar mission, to study the shallow subsurface of the Moon. In this study, key factors that could affect a lunar GPR performance, such as frequency, range resolution, and antenna directivity, are discussed firstly. Geometrical optics and ray tracing techniques are used to model GPR echoes, considering the transmission, attenuation, reflection, geometrical spreading of radar waves, and the antenna directivity. The influence on A-scope GPR echoes and on the simulated radargrams for the Sinus Iridum region by surface and subsurface roughness, dielectric loss of the lunar regolith, radar frequency and bandwidth, and the distance between the transmit and receive antennas are discussed. Finally, potential scientific return about lunar subsurface properties from GPR echoes is also discussed. Simulation results suggest that subsurface structure from several to hundreds of meters can be studied from GPR echoes at P and VHF bands, and information about dielectric permittivity and thickness of subsurface layers can be estimated from GPR echoes in combination with regolith composition data.     

Modelling of GPR waves for lossy media obeying a complex power law of frequency for dielectric permittivity

The attenuation of ground‐penetrating radar (GPR) energy in the subsurface decreases and shifts the amplitude spectrum of the radar pulse to lower frequencies (absorption) with increasing traveltime and causes also a distortion of wavelet phase (dispersion). The attenuation is often expressed by the quality factor Q. For GPR studies, Q can be estimated from the ratio of the real part to the imaginary part of the dielectric permittivity. We consider a complex power function of frequency for the dielectric permittivity, and show that this dielectric response corresponds to a frequency‐independent‐Q or simply a constant‐Q model. The phase velocity (dispersion relationship) and the absorption coefficient of electromagnetic waves also obey a frequency power law. This approach is easy to use in the frequency domain and the wave propagation can be described by two parameters only, for example Q and the phase velocity at an arbitrary reference frequency. This simplicity makes it practical for any inversion technique. Furthermore, by using the Hilbert transform relating the velocity and the absorption coefficient (which obeys a frequency power law), we find the same dispersion relationship for the phase velocity. Both approaches are valid for a constant value of Q over a restricted frequency‐bandwidth, and are applicable in a material that is assumed to have no instantaneous dielectric response. Many GPR profiles acquired in a dry aeolian environment have shown a strong reflectivity inside dunes. Changes in water content are believed to be the origin of this reflectivity. We model the radar reflections from the bottom of a dry aeolian dune using the 1D wavelet modelling method. We discuss the choice of the reference wavelet in this modelling approach. A trial‐and‐error match of modelled and observed data was performed to estimate the optimum set of parameters characterizing the materials composing the site. Additionally, by combining the complex refractive index method (CRIM) and/or Topp equations for the bulk permittivity (dielectric constant) of moist sandy soils with a frequency power law for the dielectric response, we introduce them into the expression for the reflection coefficient. Using this method, we can estimate the water content and explain its effect on the reflection coefficient and on wavelet modelling.     

Recursive impedance inversion of ground-penetrating radar data in stochastic media

The travel time and amplitude of ground-penetrating radar (GPR) waves are closely related to medium parameters such as water content, porosity, and dielectric permittivity. However, conventional estimation methods, which are mostly based on wave velocity, are not suitable for real complex media because of limited resolution. Impedance inversion uses the reflection coefficient of radar waves to directly calculate GPR impedance and other parameters of subsurface media. We construct a 3D multiscale stochastic medium model and use the mixed Gaussian and exponential autocorrelation function to describe the distribution of parameters in real subsurface media. We introduce an elliptical Gaussian function to describe local random anomalies. The tapering function is also introduced to reduce calculation errors caused by the numerical simulation of discrete grids. We derive the impedance inversion workflow and test the calculation precision in complex media. Finally, we use impedance inversion to process GPR field data in a polluted site in Mongolia. The inversion results were constrained using borehole data and validated by resistivity data.     

Ground penetrating radar inversion in 1-D: an approach for the estimation of electrical conductivity, dielectric permittivity and magnetic permeability

This paper presents a method for inverting ground penetrating radargrams in terms of one-dimensional profiles. We resort to a special type of linearization of the damped E-field wave equation to solve the inverse problem. The numerical algorithm for the inversion is iterative and requires the solution of several forward problems, which we evaluate using the matrix propagation approach. Analytical expressions for the derivatives with respect to physical properties are obtained using the self-adjoint Green's function method. We consider three physical properties of materials; namely dielectrical permittivity, magnetic permeability and electrical conductivity. The inverse problem is solved minimizing the quadratic norm of the residuals using quadratic programming optimization. In the iterative process to speed up convergence we use the Levenberg–Mardquardt method. The special type of linearization is based on an integral equation that involves derivatives of the electric field with respect to magnetic permeability, electrical conductivity and dielectric permittivity; this equation is the result of analyzing the implication of the scaling properties of the electromagnetic field. The ground is modeled using thin horizontal layers to approximate general variations of the physical properties. We show that standard synthetic radargrams due to dielectric permittivity contrasts can be matched using electrical conductivity or magnetic permeability variations. The results indicate that it is impossible to differentiate one property from the other using GPR data.     

Improvements in crosshole GPR full-waveform inversion and application on data measured at the Boise Hydrogeophysics Research Site

Crosshole ground penetrating radar (GPR) tomography has been widely used and has the potential to improve the obtained subsurface models due to its high spatial resolution compared to other methods. Recent advances in full-waveform inversion of crosshole GPR data show that higher resolution images can be obtained compared to conventional ray-based GPR inversion because it can exploit all information present in the observed data. Since the first application of full-waveform inversion on synthetic and experimental GPR data, the algorithm has been significantly improved by extending the scalar to a vectorial approach, and changing the stepped permittivity and conductivity update into a simultaneous update. Here, we introduce new normalized gradients that do not depend on the number of sources and receivers which enable a comparison of the gradients and step lengths for different crosshole survey layouts. An experimental data set acquired at the Boise Hydrogeophysics Research Site is inverted using different source–receiver setups and the obtained permittivity and conductivity images, remaining gradients and final misfits are compared for the different versions of the full-waveform inversion. Moreover, different versions of the full-waveform inversion are applied to obtain an overview of all improvements. Most improvements result in a reducing final misfit between the measured and synthetic data and a reducing remaining gradient at the final iteration. Regions with relatively high remaining gradient amplitudes indicate less reliable inversion results. Comparison of the final full-waveform inversion results with Neutron–Neutron porosity log data and capacitive resistivity log data show considerably higher spatial frequencies for the logging data compared to the full-waveform inversion results. To enable a better comparison, we estimated a simple wavenumber filter and the full-waveform inversion results show an improved fit with the logging data. This work shows the potential of full-waveform inversion as an advanced method that can provide high resolution images to improve hydrological models.     

Simulation and analysis of GPR signal based on stochastic media model with an ellipsoidal autocorrelation function

Target detection using ground penetrating radar (GPR) is based on the contrast between the electrical parameters of the target and the background medium, such as dielectric permittivity, conductivity and permeability. The application mainly concentrates on the detection of the medium interface and the target shape. In any theoretical study, a simulation model is built with a homogeneous medium. However, real detection encounters heterogeneous media which might produce scattering and diffraction at electrical interfaces and distort the radar pulse shape and affect the detection resolution. In this paper, we build multi-scale random media model with an ellipsoidal autocorrelation function and use FDTD method to simulate the GPR signal response. We then estimate and analyze the arrival time, layer thickness, permittivity and the physics relation in different scale random models according to the S transform method and the transmission wave method. The results demonstrate that we can use GPR to obtain geophysical information of multi-scale heterogeneous media, and provide a foundation for real media detection and complex media inversion.     

Estimation of in-situ density and moisture content in HMA pavements based on GPR trace reflection amplitude using different frequencies

The basic goal of the present research is to investigate the estimation of both the in-situ density and moisture content within the Hot Mix Asphalt (HMA) pavement layer(s) in a non-destructive way using Ground Penetrating Radar (GPR) trace reflection amplitude. For this purpose, an extensive pavement survey was conducted using an air-coupled GPR system, operating at 1 GHz or alternatively with a 2 GHz central frequency. The collected data were analyzed comparatively for the two antennae. The variability of electric permittivity caused by variations in HMA material is discussed, while the effect of the different frequencies is compared on the ability to retrieve permittivity, in-situ density and moisture content of the compacted HMA material using relationships suggested in reviewed international literature. The main finding of the present research is that for the same type of HMA material, the assessment of the material properties appears to be independent from the two central frequencies of investigation. However, there is evidence concerning the variations between the GPR wave data for the two different frequencies. The research highlights that the increased penetration depth of the 1 GHz antenna can provide an increased identification of areas of potential moisture within the body of HMA layer, and suggests that the variations between the permittivity values for the two different frequencies could be used to assess the homogeneity of material density with depth as an indicator of the mixture compaction. Additional findings are included within the paper.     

Determination of electromagnetic wave velocity in horizontally layered sedimentary target: A ground-penetrating radar study from Silurian limestones,Estonia

Ground-penetrating radar (GPR) is a non-destructive geophysical technique to obtain information about shallow subsurface by transmitting electromagnetic waves into the ground and registering signals reflected from objects or layers with different dielectric properties. The present GPR study was conducted in Võhmuta limestone quarry in Estonia in order to describe the relationship between GRP responses to the variations in petrophysical properties. Sub-horizontally oriented cores for petrophysical measurements were drilled from the side wall of the quarry. The GPR profiles were run at the sloped trench floor and on the top of side wall in order to correlate traceable reflections with physical properties. Based on three techniques: (i) hyperbola fitting, (ii) wide angle reflection and refraction (WARR), and (iii) topographic, a mean electromagnetic wave velocity value of 9.25 cm ns^?1 (corresponding to relative dielectric permittivity of 10.5) was found to describe the sequence and was used for time-to-depth conversion. Examination of radar images against petrophysical properties revealed that major reflections appear in levels where the changes in porosity occur.     

基于改进全变差正则化的GPR多尺度全波形双参数同步反演

针对探地雷达（GPR）双参数全波形反演中电导率反演精度差、双参数存在串扰现象、反演计算量大、易陷入局部极值等问题.作者将具有多参数调节功能的L-BFGS算法引入到GPR时间域全波形反演中,它避免了对Hessian矩阵的直接存储与精确求解,减小了存储量和计算量.结合参数调节因子的选取,有效减小了同步反演时介电常数与电导率的串扰影响,在不降低介电常数反演精度的前提下,提高电导率参数的反演精度.通过在反演目标函数中加载改进全变差正则化方法,提高了反演的稳定性,使目标体边缘轮廓更加清晰.首先以简单模型为例,对比了单尺度反演与多尺度串行反演策略的优劣,说明多尺度串行反演有利于逐步搜索全局最优解;而开展参数调节因子的选取实验,说明合适的参数调节因子可以有效改善介质电导率的反演精度;测试了不同正则化的反演效果,表明改进全变差正则化能提高反演稳定性,显著降低模型重构误差.最后,分别对含噪合成数据和实测数据进行了反演测试,说明本文提出的多尺度、双参数反演具有较强的鲁棒性,能提供更丰富的信息约束,重构图像界面清晰、反演效果好.     

An electromagnetic modelling tool for the detection of hydrocarbons in the subsoil

Electromagnetic geophysical methods, such as ground-penetrating radar (GPR), have proved to be optimal tools for detecting and mapping near-surface contaminants. GPR has the capability of mapping the location of hydrocarbon pools on the basis of contrasts in the effective permittivity and conductivity of the subsoil. At radar frequencies (50 MHz to 1 GHz), hydrocarbons have a relative permittivity ranging from 2 to 30, compared with a permittivity for water of 80. Moreover, their conductivity ranges from zero to 10 mS/m, against values of 200 mS/m and more for salt water. These differences indicate that water/hydrocarbon interfaces in a porous medium are electromagnetically 'visible'. In order to quantify the hydrocarbon saturation we developed a model for the electromagnetic properties of a subsoil composed of sand and clay/silt, and partially saturated with air, water and hydrocarbon. A self-similar theory is used for the sandy component and a transversely isotropic constitutive equation for the shaly component, which is assumed to possess a laminated structure. The model is first verified with experimental data and then used to obtain the properties of soils partially saturated with methanol and aviation gasoline. Finally, a GPR forward-modelling method computes the radargrams of a typical hydrocarbon spill, illustrating the sensitivity of the technique to the type of pore-fluid. The model and the simulation algorithm provide an interpretation methodology to distinguish different pore-fluids and to quantify their degree of saturation.     

Radar wave scattering loss in a densely packed discrete random medium: Numerical modeling of a box-of-boulders experiment in the Mie regime

In rough geologic media such as alluvial gravels, glacial tills, talus or colluvium, the grain sizes may span the range of GPR in situ wavelengths. Here we experimentally and numerically modeled the scattering loss from both rough-surface and subsurface dielectric scatterers. The combination of the selected radar frequency and the dimension of the scatterers placed the scattering within the Mie regime. We compared the GPR signal amplitude and waveform reflected from the metal sheet on the bottom of a large box filled with boulders with the numerically computed response from a discrete random medium (DRM) model. The DRM consists of a collection of densely packed ellipsoids. The size and orientation of the ellipsoids are randomized; the size has a Gaussian distribution similar to the physical experiment. The dielectric permittivity of the ellipsoids is constant and their electric conductivity is negligible. The starting in situ dominant pulse wavelength at 900 MHz was about 17 cm, as was about the average rock dimension. Experimentally, the 900-MHz radar pulse underwent most dispersion within the first in situ wavelength of depth, and then, at 500–700 MHz dominant frequency, the pulses underwent a near inverse range dependency loss rate, as if the media were a pure dielectric. The numerical model agrees well with the experimental data. Both experimental and numerical results support a significant scattering loss in Mie regime. Besides the scattering attenuation loss, velocity dispersion has also been observed from both observation and simulation. However, the scattering attenuation and dispersion cannot be fit by the Kramers–Kronig relation that is commonly found in intrinsic attenuation and worth further theoretical investigations.     

不依赖源子波的跨孔雷达时间域波形反演

波形反演是近年来较热门的反演方法,其分辨率可以达到亚波长级别.在波形反演的实际应用中,源子波的估计十分重要.传统方法使用反褶积来估计源子波并随着反演过程更新,该方法在合成数据波形反演中效果较好,但在实际数据反演过程中存在一系列的问题.由于实际数据信噪比较低,在源子波估计过程中需要大量的人为干涉,且结果并不一定可靠.本文使用一种基于褶积波场的新型目标函数,令反演过程不再依赖源子波.详细推导了针对跨孔雷达波形反演的梯度及步长公式,实现介电常数和电导率的同步反演.针对一个合成数据模型同时反演介电常数和电导率,结果表明该方法能够反演出亚波长尺寸异常体的形状和位置.接着,将该方法应用到两组实际数据中,并与基于估计源子波的时间域波形反演结果进行比较.结果表明不依赖源子波的时间域波形反演结果分辨率更高,也更准确.     

利用探地雷达频谱反演层状介质几何与电性参数

通过对地下层状介质探地雷达(GPR)回波广义反射系数的奇偶分解,建立了联系GPR反射系数序列频谱与介质几何参数、电性参数的代价函数,这些介质参数包括地下反射面的深度、层厚度以及各层的介电常数和电导率,从而提出了一种由GPR频谱同时估算地下介质多参数的全局优化反演方法.为了对多参数全局优化算法给出一个合理的参数初值,研究了不同参数对反射系数序列频谱属性的影响规律,提出了利用不同频谱属性分别估算不同参数的分步反演方法.以分步反演方法得到的结果作为多参数全局优化反演的初值,可以极大地提高反演计算的效率和反演结果的可靠性.用理论模型合成数据和GPR公路检测数据对本文方法进行了测试,结果表明本文方法效果良好,具有较高的分辨率,能较好的给出厚度小于调谐厚度的薄层的深度、厚度和介电常数等参数.     

Geoelectrical constraints on radar probing of shallow water-saturated zones within karstified carbonates in semi-arid environments

Shallow carbonates are of utmost importance as potential sources of groundwater in karstified semi-arid terrains. Ground-Penetrating Radar (GPR) is being increasingly used as a prominent mapping tool in such environments. However, its potential in exploring and identifying shallow water-saturated zones (WSZs) in carbonates is constrained by the geoelectrical properties of carbonate soils as a function of moisture content. We report results of a case study that includes laboratory geoelectrical characterization and their comparison to in situ GPR attenuation measurements performed on Cretaceous Edwards Formation rudist mounds in central Texas, which we hypothesize as analogs for water-bearing formations in semi-arid karstified carbonate terrains. Dielectric measurements on field-collected rock samples carried out in the laboratory under controlled conditions of moisture saturation suggest that real and imaginary parts of dielectric constants of rocks with higher porosity and/or permeability have steeper dependence on pore moisture content; they produce better dielectric contrasts but allow shallower penetration. Our analyses suggest that within carbonates, dielectric contrasts improve with decrease in sounding frequency and/or increase in moisture content; and the relationship between dielectric permittivity and moisture content may be represented by 3rd order polynomial equations. GPR surveys using a wide-band 400 MHz antenna reveal subsurface mound morphologies with heights of ～ 1–2 m and basal diameters of ～ 8–10 m resembling outcrop analogs. Each mound appears to be composed of smaller amalgamated lithounits that seem geoelectrically similar. Amplitudes decays of the backscattered radar signal correlate to moisture distribution. Measuring the differences in signal attenuation allows differentiation between saturated and non-saturated zones. Velocity analyses of GPR profiles enable estimation of moisture distribution in the vicinity of the mounds. Optimal delineation and production of high-resolution GPR data up to a depth of ～ 10 m were observed for a sounding frequency of ～ 250 MHz with moisture content of ～ 5% by weight. Below this moisture level, the dielectric contrast is insufficient to uniquely identify water-saturated zones from the surrounding geoelectrical context, and above it, the radar signal is substantially attenuated leading to a total inefficiency of the method.     

用地质雷达数据资料反演二维地下介质的方法

从二维麦克斯韦方程组出发推导出反演介电常数和电导率等二维介质物性参数的反演公式.反演的步骤是: 建立初始猜测模型,利用电磁波时间域有限差分法模拟正演数据,用正演数据与观测数据之间的数据残差建立目标函数,通过引入一个由麦克斯韦方程计算的伴随场,将目标函数对介质参数的导数表示成显式形式,应用最优化理论得出对初始猜测模型的修改,用共轭梯度法迭代,最终得到反演结果.用合成数据反演具有粗糙地表的非导电介质的介电常数,用实验数据同时反演介电常数和电导率,并比较了麦克斯韦方程反演结果与声波方程反演结果、波动方程偏移剖面的差异.     

Synthetic radargrams from electrical conductivity and magnetic permeability variations

The objective of this work is to assess the importance of electrical conductivity and magnetic permeability variations in ground penetrating radar (GPR) reflections commonly interpreted only in terms of permittivity variations. We use the matrix propagator approach to obtain the surface electric field associated with a horizontally layered model whose three electromagnetic properties vary from layer to layer. The solution is based on the plane wave boundary value problem using inverse Fourier transformation to accommodate particular GPR pulses. Our results indicate that while magnetic permeability is unimportant, reflections from electrical conductivity variations can be of the same order as those associated with electrical permittivity boundaries. In particular, we show that a realistic ground model composed of thin conductive layers can produce radargrams similar to those caused by a lossless permittivity contrast.     

甚高频时岩石介电常数的测试方法和特性

本文讨论20—200MHz频率范围内平行板电容法测量岩石介电常数和电导率的方法,指出常用的静电场公式的局限性,给出较精确的似稳场动态公式,并讨论20—50MHz频率范围内的岩石介电特性。