Table of contents

A detailed analytical feasibility study is performed which identifies several important limitations in the problem of layered earth characterization with off-ground GPR in the mono-static or small baseline bistatic configurations. It is shown mathematically that the characterization of layered earth by radar is an ill-posed problem. The permittivity and thickness of the first layer may be estimated. However, for penetrable earth, one may not estimate the first layer's conductivity or the parameters of deeper layers without ambiguity. This problem may be partially circumvented via the use of a priori knowledge and several examples of this, applicable to practical problems, are considered in detail. The feasibility study identifies the limitations in question in the form of a mathematical proof. These limitations are demonstrated using extensive simulated and experimental results.

Measuring the electrical permittivity of civil engineering materials is important for a range of ground penetrating radar (GPR) and pavement moisture measurement applications. Compacted unbound granular (UBG) pavement materials present a number of preparation and measurement challenges using conventional characterisation techniques. As an alternative to these methods, a modified free-space (MFS) characterisation approach has previously been investigated. This paper describes recent work to optimise and validate the MFS technique. The research included finite difference time domain (FDTD) modelling to better understand the nature of wave propagation within material samples and the test apparatus. This research led to improvements in the test approach and optimisation of sample sizes. The influence of antenna spacing and sample thickness on the permittivity results was investigated by a series of experiments separating antennas and measuring samples of nylon and water. Permittivity measurements of samples of nylon and water approximately 100 mm and 170 mm thick were also compared, showing consistent results. These measurements also agreed well with surface probe measurements of the nylon sample and literature values for water. The results indicate permittivity estimates of acceptable accuracy can be obtained using the proposed approach, apparatus and sample sizes.

The broadband dielectric measurement method based on the vector network analysis technique, in combination with an open-ended coaxial probe, was applied to the determination of the dielectric relaxation behaviour of one- and two-component backfilling grout materials in the frequency range from 40 MHz to 2 GHz. The cement hydration process and the gelling of commercial grouts was monitored in real-time to investigate the application of non-destructive testing methods in the tunnelling industry. It was found that the time-dependent dielectric relaxation behaviour can accurately reveal the different stages of the hydration process and delineate the start of gel hardening. These measurement results demonstrate the practicability of the real-time dielectric measurement method to determine the broadband dielectric parameters of conventional backfill materials used in underground construction to determine construction integrity using non-destructive testing methods.

The knowledge of constitutive broadband electromagnetic (EM) properties of porous media such as soils and rocks is essential in the theoretical and numerical modeling of EM wave propagation in the subsurface. This paper presents an experimental and numerical study on the performance EM measuring instruments for broadband EM wave in the radio–microwave frequency range. 3-D numerical calculations of a specific sensor were carried out using the Ansys HFSS (high frequency structural simulator) to further evaluate the probe performance. In addition, six different sensors of varying design, application purpose, and operational frequency range, were tested on different calibration liquids and a sample of fine-grained soil over a frequency range of 1 MHz–40 GHz using four vector network analysers. The resulting dielectric spectrum of the soil was analysed and interpreted using a 3-term Cole–Cole model under consideration of a direct current conductivity contribution. Comparison of sensor performances on calibration materials and fine-grained soils showed consistency in the measured dielectric spectra at a frequency range from 100 MHz–2 GHz. By combining open-ended coaxial line and coaxial transmission line measurements, the observable frequency window could be extended to a truly broad frequency range of 1 MHz–40 GHz.

Large-scale sediment deformation structures formed by glaciotectonic processes have been identified south of Ludington, USA. Here, several apparent clay diapirs rise from below beach level to near the top of an approximately 60 m high bluff along the eastern shore of Lake Michigan. Throughout the area, the surface topography and locations of springs indicate a complicated subsurface structure and a preferred pattern of groundwater drainage. Since public borehole information is sparse, it is not known whether the structures exposed in the bluff are true diapirs or ridges, and if the latter, what is their orientation. In this paper we present the results of field, laboratory, and modeling studies to characterize the inland extent and orientation of these deformation structures using galvanic-source electrical geophysical methods. We exploit the large electrical contrast between a sandy sedimentary layer and an underlying clayey silt sedimentary layer in which the deformation occurred. Constant-spread traverses and multi-electrode tomographic data demonstrate that at least one of the narrow structures extends a significant distance inland.

Mapping the horizontal distribution of permeability is a key problem for the coal seam gas industry. Poststack seismic data with anisotropy attributes provide estimates for fracture density and orientation which are then interpreted in terms of permeability. This approach delivers an indirect measure of permeability and can fail if other sources of anisotropy (for instance stress) come into play. Seismo-electric methods, based on recording the electric signal from pore fluid movements stimulated through a seismic wave, measure permeability directly. In this paper we use numerical simulations to demonstrate that the seismo-electric method is potentially suitable to map the horizontal distribution of permeability changes across coal seams. We propose the use of an amplitude to offset (AVO) analysis of the electrical signal in combination with poststack seismic data collected during the exploration phase. Recording of electrical signals from a simple seismic source can be closer to production planning and operations. The numerical model is based on a sonic wave propagation model under the low frequency, saturated media assumption and uses a coupled high order spectral element and low order finite element solver. We investigate the impact of seam thickness, coal seam layering, layering in the overburden and horizontal heterogeneity of permeability.

We present a general finite-element solver, escript, tailored to solve geophysical forward and inverse modeling problems in terms of partial differential equations (PDEs) with suitable boundary conditions. Escript's abstract interface allows geoscientists to focus on solving the actual problem without being experts in numerical modeling. General-purpose finite element solvers have found wide use especially in engineering fields and find increasing application in the geophysical disciplines as these offer a single interface to tackle different geophysical problems. These solvers are useful for data interpretation and for research, but can also be a useful tool in educational settings. This paper serves as an introduction into PDE-based modeling with escript where we demonstrate in detail how escript is used to solve two different forward modeling problems from applied geophysics (3D DC resistivity and 2D magnetotellurics). Based on these two different cases, other geophysical modeling work can easily be realized. The escript package is implemented as a Python library and allows the solution of coupled, linear or non-linear, time-dependent PDEs. Parallel execution for both shared and distributed memory architectures is supported and can be used without modifications to the scripts.

High-velocity self-aerated flows are described as 'white waters' because of the entrained air bubbles. The air entrainment induces a drastic change in the multiphase flow structure of the water column and this leads to significant bubble-turbulence interactions, turbulence modulation and associated mixing processes impacting on the bulk flow properties. In these high-velocity free-surface turbulent flows, the phase-detection needle probe is a most reliable instrumentation. The signal processing of a phase-detection probe is re-visited herein. It is shown that the processing may be performed on the raw probe signal as well as the thresholded data. The latter yields the time-averaged void fraction, the bubble count rate, the particle chord time distributions and the particle clustering properties within the particulate flow regions. The raw probe signal analysis gives further the auto-correlation time scale and the power spectrum density function. Finally dimensional considerations are developed with a focus on the physical modelling of free-surface flows in hydraulic structures. It is argued that the notion of scale effects must be defined in terms of some specific set of air–water flow properties within well-defined testing conditions, while a number of free-surface flow characteristics are more prone to scale effects than others, even in large-size physical facilities.

Random noise attenuation is an important step in seismic data processing. In this paper, we propose a novel denoising approach based on compressive sensing and the curvelet transform. We formulate the random noise attenuation problem as an L₁ norm regularized optimization problem. We propose to use the curvelet transform as the sparse transform in the optimization problem to regularize the sparse coefficients in order to separate signal and noise and to use the gradient projection for sparse reconstruction (GPSR) algorithm to solve the formulated optimization problem with an easy implementation and a fast convergence. We tested the performance of our proposed approach on both synthetic and field seismic data. Numerical results show that the proposed approach can effectively suppress the distortion near the edge of seismic events during the noise attenuation process and has high computational efficiency compared with the traditional curvelet thresholding and iterative soft thresholding based denoising methods. Besides, compared with f-x deconvolution, the proposed denoising method is capable of eliminating the random noise more effectively while preserving more useful signals.

Waveform tomography is commonly tested using numerically generated synthetic seismic data, before the method is applied to field seismic data. However, there are often noticeable differences between idealized synthetic data and real field data, and many factors in the field data, such as noise, irregular source/receiver geometry, affect the inversion solutions. For exploring the potential of reflection seismic waveform tomography, we presented a more realistic test than the synthetic data test, by applying it to physical modelling data, to reconstruct a laboratorial model with complex velocity variation. First, we provided a formulation of the perfectly matched layer absorbing boundary condition, associated with the second-order acoustic wave equation, in order to suppress artificial reflections from subsurface model boundaries in seismic waveform simulation and tomography. Then, we demonstrated the successful implementation of a layer-striping inversion scheme applicable to reflection seismic waveform tomography. Finally, we confirmed the effectiveness of frequency grouping, rather than a single frequency at each iteration, a strategy specifically for the frequency-domain waveform tomography.

The common-midpoint (CMP) stacking technique plays an important role in enhancing the signal-to-noise ratio (SNR) in seismic data processing and imaging. Weighted stacking is often used to improve the performance of conventional equal-weight stacking in further attenuating random noise and handling the amplitude variations in real seismic data. In this study, we propose to use a hybrid framework of combining AB semblance and a local-similarity-weighted stacking scheme. The objective is to achieve an optimal stacking of the CMP gathers with class II amplitude-variation-with-offset (AVO) polarity-reversal anomaly. The selection of high-quality near-offset reference trace is another innovation of this work because of its better preservation of useful energy. Applications to synthetic and field seismic data demonstrate a great improvement using our method to capture the true locations of weak reflections, distinguish thin-bed tuning artifacts, and effectively attenuate random noise.

Injection of CO₂ into a geological subsurface will cause seismic dispersion and attenuation, which will change with the migration of the CO₂ plume. Therefore, temporal attenuation changes from the seismic section with the CO₂ plume can provide additional information about CO₂ storage, migration, and possible leakage. The frequency-dependent amplitude variation with offset (FDAVO) attribute, as a seismic characteristic, which quantifies frequency-dependent anomalies from various kinds of sources, is widely applied in fields of hydrocarbon indication and fluid identification. In this work we aim to investigate the potential of the FDAVO attribute as a monitoring tool during the process of CO₂ migration. We combine the Buckley–Leverett equation and the patchy-saturation model to simulate the substitution process. We then apply a novel tool, the FDAVO inversion method, to estimate the dispersion level at the target interface. What is more, the characteristic of the frequency-dependent attribute versus time is studied for the first time. The result of the numerical simulation reveals that: (1) caused by CO₂ injection, there is significant dispersion and attenuation within the seismic band; (2) the level of dispersion reflects the migration of CO₂ plume; (3) dispersion anomalies are well quantified by the inverted FDAVO attributes, which can be utilized to characterize the vertical distribution of the CO₂ plume.

Least-squares reverse time migration (LSRTM) is a linearized inversion technique used for estimating high-wavenumber reflectivity. However, due to the redundant overlay of the band-limited source wavelet, the gradient based on the cross-correlated imaging principle suffers from a loss of wavenumber information. We first prepare the residuals between observed and demigrated data by deconvolving with the amplitude spectrum of the source wavelet, and then migrate the preprocessed residuals by using the cross-correlation imaging principle. In this way, a gradient that preserves the spectral signature of data residuals is obtained. The computational cost of source-wavelet removal is negligible compared to that of wavefield simulation. The two-dimensional Marmousi model containing complex geology structures is considered to test our scheme. Numerical examples show that our improved gradient in LSRTM has a better convergence behavior and promises inverted results of higher resolution. Finally, we attempt to update the background velocity with our inverted velocity perturbations to approach the true velocity.

In order to understand the permeability evolution law of the gob by mining disturbances and obtain the permeability distribution of the fully compacted gob, comprehensive methods including theoretical analyses of monitoring data and numerical simulation are used to determine the permeability of gobs in the mining process.

Based on current research, three zones of the vertical stress and permeability in the gob are introduced in this article, which are the caving rock mass accumulation zone, the gradually compacted zone and the fully compacted zone. A simple algorithm is written by using FISH language to be imported into the reservoir model. FISH language is an internal programming language in FLAC3D. It is possible to calculate the permeability at each zone with this algorithm in the mining process. Besides, we analyze the gas flow rates from seven gob gas ventholes (GGV) located on a longwall face operated in a mine of a Huainan coalfield in Huainan City, China. Combined with Darcy's law, a calculation model of permeability around GGV in the gob is proposed. Using this model, the evolution law of permeability in the gob is deduced; the phases of permeability evolution are the decline stage and the stable stage. The result of the vertical stress monitoring data and good fitting effect of the permeability to the experimental data show that the permeability decline caused by the compaction of the gob is the principal reason for the decline stage. The stable stage indicates that the gob has been fully compacted, and the average period of full gob compaction is 47.75 d. The permeability in the middle of the compacted gob is much smaller than the permeability on the edge of the gob which presents an O shape trend. Besides, the little difference among the results of the numerical simulation, the permeability calculation model and other commonly used calculation models validate the correctness of the permeability calculation model and numerical simulation results.

Amplitude variation with offset (AVO) inversion is widely utilized in exploration geophysics, especially for reservoir prediction and fluid identification. Inverse operator estimation in the trust region algorithm is applied for solving AVO inversion problems in which optimization and inversion directly are integrated. The L1 norm constraint is considered on the basis of reasonable initial model in order to improve effciency and stability during the AVO inversion process. In this study, high-order Zoeppritz approximation is utilized to establish the inversion objective function in which variation of ${{v}_{\text{p}}}/{{v}_{\text{s}}}$ with time is taken into consideration. A model test indicates that the algorithm has a relatively higher stability and accuracy than the damp least-squares algorithm. Seismic data inversion is feasible and inversion values of three parameters (${{v}_{\text{p}}},{{v}_{\text{s}}},\rho$) maintain good consistency with logging curves.