Theoretical Developments in Electromagnetic Induction Geophysics with Selected Applications in the Near Surface

Near-surface applied electromagnetic geophysics is experiencing an explosive period of growth with many innovative techniques and applications presently emergent and others certain to be forthcoming. An attempt is made here to bring together and describe some of the most notable advances. This is a difficult task since papers describing electromagnetic induction methods are widely dispersed throughout the scientific literature. The traditional topics discussed herein include modeling, inversion, heterogeneity, anisotropy, target recognition, logging, and airborne electromagnetics (EM). Several new or emerging techniques are introduced including landmine detection, biogeophysics, interferometry, shallow-water electromagnetics, radiomagnetotellurics, and airborne unexploded ordnance (UXO) discrimination. Representative case histories that illustrate the range of exciting new geoscience that has been enabled by the developing techniques are presented from important application areas such as hydrogeology, contamination, UXO and landmines, soils and agriculture, archeology, and hazards and climat

Novel AI-assisted computational solutions for GPR data interpretation and electromagnetic data fusion to detect buried utilities

This research presents a number of novel computational solutions using artificial intelligence (AI) to interpret ground penetrating radar (GPR) data as well as fusing GPR data with data from other sensing modalities, including electromagnetic conductivity (EMC) and electromagnetic locating (EML). The application of the proposed computational solution is predominantly for detecting and locating buried utilities (e.g. pipes and cables) and ground anomalies (e.g. ground disturbances) in the shallow subsurface environment although the work can be extended to detect other buried anomalies. Processing GPR data is usually a subjective and time-consuming practise which involves expert intervention. Thus, the quality of the interpretation of such data depends on user experience and knowledge. Whilst several numerical approaches are available in the literature for post-processing GPR data, they all suffer from various shortcomings including lack of accuracy and/or excessive computational time. The issue is similar (or often worse) for data fusion between GPR and other sensors e.g. EMC and EML. To tackle some of these issues, in this research, four new computational procedures were developed. Three of these computational procedures are based on Kalman Filtering (KF), a less-studied approach to process GPR radargrams despite its great potential in efficient data analysis, and genetic algorithm (GA) as a machine learning based global optimisation tool. The final computational procedure combines finite element modelling and genetic algorithm to infer fused EML-GPR data. For the first two numerical methods, new algorithms were developed to optimise KF parameters using GA to remove noises from GPR radargrams and detect targets. The proposed procedures were validated against data from field and their performance was assessed against additional unseen dataset different to that of the validation to identify their potential limitations. Furthermore, their performances were compared against existing GPR data processing methods and differences were highlighted. The other two computational packages focused on data fusion from GPR and EMC/EML. The first of these two, extended the above KF algorithm to fuse data from GPR and EML as well as GPR and EMC. The results showed that the proposed data fusion algorithm significantly enhanced the quality of locating conductors and conductive regions in the subsurface compared to the individual techniques which were either incapable of defining the material of the buried target or the geometry of conductive anomalies. Finally, a novel inversion algorithm was developed by integrating finite element modelling of a coupled magnetic field and GA for detecting and locating buried live cables using GPR and EML. It was demonstrated that the proposed inversion can successfully detect the location of the buried cables as well as their intensity

Time Series Analysis of Surface Deformation Associated With Fluid Injection and Induced Seismicity in Timpson, Texas Using DInSAR Methods

In recent years, a rise in unconventional oil and gas production in North America has been linked to an increase in seismicity rate in these regions (Ellsworth, 2013). As fluid is pumped into deep formations, the state of stress within the subsurface changes, potentially reactivating pre-existing faults and/or causing subsidence or uplift of the surface. Therefore, hydraulic fracturing and/or fluid disposal injection can significantly increase the seismic hazard to communities and structures surrounding the injection sites (Barnhart et al., 2014). On 17th May 2012 an Mw4.8 earthquake occurred near Timpson, TX and has been linked with wastewater injection operations in the area (Shirzaei et al., 2016). This study aims to spatiotemporally relate, wastewater injection operations to seismicity near Timpson using differential interferometric synthetic aperture radar (DInSAR) analysis. Results are presented as a set of time series, produced using the Multidimensional Small Baseline Subset (MSBAS) InSAR technique, revealing two-dimensional surface deformation

Inversion strategies for seismic surface waves and time-domain electromagnetic data with application to geotechnical characterization examples.

Geophysical methods are broadly used to map the subsurface. Their ability to investigate large areas in a short time and to reach significant depths with good resolution makes them suitable for a wide range of applications: from hydrological studies, mineral exploration, archaeological investigations to geotechnical characterization. Unfortunately, most of the geophysical methods are ill-posed. Thus, to be able to effectively invert the geophysical data and get meaningful models of the subsurface a priori information needs to be included in the process. This is the basic idea behind the inversion theory. This thesis deals with the inversion of two types of geophysical measurements: the Seismic Surface Waves (SSW) data and the Time Domain Electromagnetic (TDEM) observations. The present work consists of two parts: (1) The first one is about possible implementations of the minimum gradient support stabilizer into a SSW inversion routine and its extension to the laterally constrained case. By means of this novel approach, it is possible to tune the level of sparsity of the reconstructed velocity model, providing a solution with the desirable characteristics (smooth or sharp) in both directions (vertically and laterally). The capabilities of the proposed approach have been tested via applications on synthetic and measured data. (2) The second part of the thesis is about the joint interpretation of SSW and TDEM measurements for an improved geotechnical characterization of an area intended for construction. In this case, the SSW results, together with other ancillary data, are used as prior information for the subsequent inversion of TDEM measurements. In this respect, the SSW results have been translated into pieces of information to be used in the TDEM inversion via a petrophysical relationship. This work is coherent with one of the goals of the United Nations Agenda 2030 for sustainable development, specifically, the item 11b, as geotechnical characterization is one of the essential components for the design of civil engineering works, ensuring the necessary safety and resilience to natural disasters and climate change. However, the field of application of the proposed approaches is very broad as they can also be used, e.g., for groundwater mapping, as well as for the evaluation of aquifer contamination. In this respect, the present work is also in line with items 6.1, 6.3 and 6.4 of the 2030 UN Agenda

Exploration of radiation damage mechanism in mems devices.

We explored UV, X-ray and proton radiation damage mechanisms in MEMS resonators. T-shaped MEMS resonators of different dimensions were used to investigate the effect of radiation. Radiation damage is observed in the form of resistance and resonance frequency shift of the device. The resistance change indicates a change in free carrier concentration and mobility, while the resonance frequency change indicates a change in mass and/or elastic constant. For 255nm UV radiation, we observed a persistent photoconductivity that lasts for about 60 hours after radiation is turned off. The resonance frequency also decreases 40-90 ppm during irradiation and slowly recovers at about the same time scale as the resistance during annealing. For X-ray radiation, the resonance frequency decreases with radiation, but the resistance increases. To investigate X-ray dose-rate dependence, we irradiated the resonators at three different dose rates of X-ray: 5.4, 10.9 and 30.3 krad(SiO2)/min. The change in resonance frequency and resistance both showed a dose rate dependence where a lower dose-rate X-ray caused a larger shift in resonance frequency than the higher dose-rate. We attributed the observed shift in resonance frequency to the change in carrier concentration—using Keyes’ theory of electronic contribution to elastic constant—for both X-ray and UV radiation. The resistance change is explained by the net effect of the carrier concentration and mobility change. We proposed that the carrier concentration changes through two differing mechanisms for X-ray and UV radiation. For X-ray, dopant depassivation is primarily responsible for the carrier concentration change since an X-ray is known to dissociate the hydrogen-boron complex and it penetrates through the 15μm thick Si resonator affecting the whole bulk of Si. On the contrary, the 255nm UV gets absorbed near the surface (within 10nm) and charges the native oxide. The mirror charge on adjacent silicon is responsible for the carrier concentration change. The mirror charges drive the silicon surface to accumulation, depletion or strong inversion depending on the type and amount of charge trapped in the oxide. Since the carrier concentration only changes near the surface, it was predicted that higher surface-to-volume ratio devices will show a greater shift in resonance frequency. This was proven by radiating three devices with differing widths (1, 2 and 8μm), and therefore differing surface-to-volume ratios. This experiment verified that the UV light effect is surface dominated. The dimensional dependence is also observed for X-ray radiation damage. We found that a reduction in the surface-to-volume ratio enhances the X-ray radiation damage and we proposed a hydrogen diffusion-based model that fits the observed dimensional dependence of X-ray radiation damage. For proton radiation, the direction of resonance frequency change depended on the energy of radiated proton. Two proton energies were tested: 0.8MeV and 2MeV. The proton with 0.8MeV energy stops inside the resonator, causing greater displacement damage than the proton with 2MeV energy, which readily passes through the resonator. The 2MeV proton causes more ionization damage than the 0.8MeV protons. So, the observed energy dependence of resonance frequency shift comes from the competing effects of displacement damage and ionization damage since resonance frequency decreases due to ionization damage but increases due to displacement damage. The result agrees with our theory since the 0.8MeV proton radiation showed net resonance frequency increase during radiation and more permanent damage after annealing compared to the 2MeV proton radiation

Applications of SAR Interferometry in Earth and Environmental Science Research

This paper provides a review of the progress in regard to the InSAR remote sensing technique and its applications in earth and environmental sciences, especially in the past decade. Basic principles, factors, limits, InSAR sensors, available software packages for the generation of InSAR interferograms were summarized to support future applications. Emphasis was placed on the applications of InSAR in seismology, volcanology, land subsidence/uplift, landslide, glaciology, hydrology, and forestry sciences. It ends with a discussion of future research directions

Advanced Techniques for Ground Penetrating Radar Imaging

Ground penetrating radar (GPR) has become one of the key technologies in subsurface sensing and, in general, in non-destructive testing (NDT), since it is able to detect both metallic and nonmetallic targets. GPR for NDT has been successfully introduced in a wide range of sectors, such as mining and geology, glaciology, civil engineering and civil works, archaeology, and security and defense. In recent decades, improvements in georeferencing and positioning systems have enabled the introduction of synthetic aperture radar (SAR) techniques in GPR systems, yielding GPR–SAR systems capable of providing high-resolution microwave images. In parallel, the radiofrequency front-end of GPR systems has been optimized in terms of compactness (e.g., smaller Tx/Rx antennas) and cost. These advances, combined with improvements in autonomous platforms, such as unmanned terrestrial and aerial vehicles, have fostered new fields of application for GPR, where fast and reliable detection capabilities are demanded. In addition, processing techniques have been improved, taking advantage of the research conducted in related fields like inverse scattering and imaging. As a result, novel and robust algorithms have been developed for clutter reduction, automatic target recognition, and efficient processing of large sets of measurements to enable real-time imaging, among others. This Special Issue provides an overview of the state of the art in GPR imaging, focusing on the latest advances from both hardware and software perspectives