Near Surface Geophysics - Volume 22, Issue 4, 2024

Currently, the horizontal resolution of Rayleigh wave exploration is low. In this study, we propose the Born–Jordan time‐frequency distribution to analyse Rayleigh waves. The seismic signal was filtered with a wavelet transform for denoising, and the Rayleigh wave was separated in the time domain. Using the Born–Jordan time‐frequency distribution, the time waveform of each frequency comprising the Rayleigh wave from every seismic channel was obtained, and the time difference of the Rayleigh wave with the same frequency was calculated, based on which the dispersion curve between the two channels was obtained. Combined with the multichannel Rayleigh wave dispersion curve, phase velocity and frequency imaging under the seismic arrangement were obtained. Applying this method to detect abnormal geological bodies in engineering investigations showed that hard geologic bodies, such as comcrete rocks, have high velocity and frequency, whereas weak ones have low velocity and frequency. This strategy facilitated the detection of fractured zones, underground goafs and obstacles during pipe‐jacking construction near the surface.

Waveform inversion is theoretically a powerful tool to reconstruct subsurface structures, but a usually encountered problem is that accurate sources are very rare, causing the computation to be unstable or divergent. This challenging practical problem, although sometimes ignored and even imperceptible, can easily create discrepancies in calculated shot gathers, which will then lead to wrong residuals that will be smeared back to the gradients, hence jeopardizing the inverted tomograms. For any real dataset, every shot gather corresponds to its unique source even if some gathers can be transformed alike after data processing. To resolve this problem, we propose a collocated inversion of sources and early arrival waveforms with the two submodules executing successively. Not only can this method reconstruct a decent source wavelet that approaches the ground truth, but also it can produce credible background tomograms with optimized sources. Part of the cycle skipping problems can also be mitigated because it avoids the trial and error experiments on various sources. Numerical tests on a synthetic and a land dataset validate the effectiveness of this method. Restrictions on initial sources or starting velocity models will be relaxed, and this method can be extended to any other applications for engineering or exploration purposes.

The recent developments of electromagnetic induction and electrostatic prospection devices dedicated to critical zone surveys in both rural and urban contexts necessitate improving the interpretation of electrical properties through complementary laboratory studies. In a first interpretation step, the various experimental results obtained in the 100 Hz–10 MHz frequency range can be empirically fitted by a simple six‐term formula. It allows the reproduction of the logarithmic decrease of the real component of the effective relative permittivity and its corresponding imaginary component, the part associated with the direct current conductivity, one Cole–Cole relaxation and the real and imaginary components of the high‐frequency relative permittivity. For elucidating physical phenomena contributing to both the logarithmic decrease and the observed Cole–Cole relaxation, we first consider the Maxwell–Wagner–Sillars polarization. Using the method of moments, we establish that this continuous medium approach can reproduce a large range of relaxation characteristics. At the microscopic scale, the possible role of the rotation of the water molecules bound to solid grains is then investigated. In this case, contrary to the Maxwell–Wagner–Sillars approach, the relaxation parameters do not depend on the external medium properties.

Borehole ground‐penetrating radar (BGPR) measurements allow for the detection of objects and structures in the subsurface and are often applied to the detection of unexploded ordnance (UXO). If omnidirectional borehole antennas in reflection mode are used for the measurement, the localization of UXO is only possible if the data from a multitude of boreholes are analysed. Data analysis is usually still done by manual picking of reflections. We propose novel approaches to process and visualize data from BGPR measurements in a more advanced and appealing manner. Therein, the reflected energy recorded in the radargrams is projected back to all potential reflection points in the three‐dimensional space around the boreholes. If the projection direction is considered, we obtain a vectorized energy projection image. Superposition of projected energy yields an easy‐to‐grasp indicator of possible locations of UXO and of regions of interest that ought to be investigated in more detail. These approaches have been applied to synthetic data and to data measured on a test site with buried UXO. The results show that energy projection is a useful tool for BGPR data visualization, although the result is dependent on data pre‐processing. The proposed methods provide novel representations of BGPR data based on an objective algorithm which will at least complement the conventional methods.

Quantification of non‐uniqueness and uncertainty is important for transient electromagnetism (TEM). To address this issue, we develop a trans‐dimensional Bayesian inversion schema for TEM data interpretation. The trans‐dimensional posterior probability density (PPD) offers a solution to model selection and quantifies parameter uncertainty resulting from the model selection from all possible models rather than determining a single model. We use the reversible‐jump Markov chain Monte Carlo sampler to draw ensembles of models to approximate PPD. In addition to providing reasonable model selection, we address the reliability of the inversion results for uncertainty analysis. This strategy offers reasonable guidance when interpreting the inversion results. We make the following improvements in this paper. First, in terms of algorithmic acceleration, we use the nonlinear optimization inversion results as the initial model and implement the multi‐chain parallel method. Second, we develop double factors to control the sampling step size of the proposed distribution, so that the sampling models cover the high‐probability region of the parameter space as much as possible. Finally, we provide the potential scale reduction factor‐η convergence criteria to assess the convergence of the samples and ensure the rationality of the output models. The proposed methodology is first tested on synthetic data and subsequently applied to a field dataset. The TEM inversion results show that probability inversion can provide reliable references for data interpretation through uncertainty analysis.