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

Implementation of an advanced algorithm for enhanced signal analysis in electrical resistance tomography using the EIDORS toolbox

The primary objectives of this research include an implementation of a 3-D algorithm in visualising the movement of solid suspended objects through image reconstruction and assessment of the quality of these images as well as validation of the application of the 3-D algorithm in visualising the movement of conductive solution

High-resolution imaging of transport processes with GPR full-waveform inversion

Imaging subsurface small-scale features and monitoring transport of tracer plumes at a fine resolution is of interest to characterize transport processes in aquifers. Full-waveform inversion (FWI) of crosshole ground penetrating radar (GPR) measurements enables aquifer characterization at decimeter-scale resolution. GPR FWI provides 2D tomograms of the subsurface properties, the dielectric permittivity (ε) and electrical conductivity (σ), which can be correlated with hydrological properties. In the framework of the thesis, we conducted synthetic and experimental tracer tests that were monitored using time-lapse crosshole GPR full-waveform inversion results, to test the potential and limitation to reconstruct the tracer plume. For the synthetic test, we generated a realistic high resolution aquifer model based on previous hydrological and GPR FWI data from the Krauthausen test site in order perform a transport simulation that represents reasonable heterogeneity of the tracer concentration. Using petrophysical relations, we converted the concentration distribution to dielectric properties of specific tracers: saltwater (increase σ only), desalinated water (decrease σ only) and ethanol (decrease in both σ and ε). One important aspect of the GPR FWI is to investigate an optimal way to define adequate starting models especially for the time-lapse data. Therefore, we investigated three different starting model options in the synthetic test, resulting that ε and σ models from the background provide the most accurate FWI of time-lapse data. Hereby, both ε and σ FWI results have shown the potential to derive time-lapse changes. The gained insights of the synthetic optimization tests are applied for an experimental test. To prove the potential of the crosshole GPR FWI also under realistic conditions, we performed an experimental salt tracer experiment at the Krauthausen test site. Thereby, we injected to the sandy aquifer a salt tracer, and monitored the tracer development using crosshole GPR over a timeframe of 14 days within 5 crosshole planes in an area of 11x10 m. These time-lapse data are independently inverted using the background models of each plane as starting models as proposed from the synthetic study to derive the best FWI results. We investigated the consistency of the reconstruction of the plume by temporal and spatial continuity across neighboring planes, by correlating with borehole logging data, and with expectations based on previous tracer experiments from the same site. One challenge arise from the time-lapse GPR data caused by the change of the borehole filling properties over the time and transport of the plume. The salt and freshwater mixture in the tubes couple with the borehole antennae thus influence the GPR data. Fortunately, the processing for the FWI enables accounting this effect by estimating effective source wavelets for each time step and each plane, which compensate for borehole filling effects caused by the salt tracer. If these borehole filling effects would not be considered, errors in the results would occur. Performing the FWI considering the corrected effective source wavelets allows recovery of the aquifer models independently from saltwater-antennae effects. Such effects cannot be incorporated using standard ray-based approaches. In contrast from the synthetic tracer test, investigation of the best starting model for experimental data showed that σ homogenous model rather than from FWI background provides more accurate results for FWI of time-lapse data. This can be explained that possible errors in the FWI background results caused by measurement or starting model uncertainties, are forcing the FWI with these models to be trapped in a local minimum. The time-lapse GPR FWI has shown a reliable manifestation of a tracer of about 0.2 m resolution, which was not observed before from other geophysical monitoring techniques. These improved and higher resolution images of such a tracer transport can help in future to better constraint hydrological properties of interest for hydrological models. In this thesis, we have shown for the first time the potential of the GPR FWI to characterize and monitor tracer experiments using crosshole GPR data. Especially, the application to salt tracers, which traditionally were investigated with ERT, is now also possible with GPR and higher resolution images of the tracer transport are possible to obtain

Smartspectrometer—embedded optical spectroscopy for applications in agriculture and industry

The ongoing digitization of industry and agriculture can benefit significantly from optical spectroscopy. In many cases, optical spectroscopy enables the estimation of properties such as substance concentrations and compositions. Spectral data can be acquired and evaluated in real time, and the results can be integrated directly into process and automation units, saving resources and costs. Multivariate data analysis is needed to integrate optical spectrometers as sensors. Therefore, a spectrometer with integrated artificial intelligence (AI) called SmartSpectrometer and its interface is presented. The advantages of the SmartSpectrometer are exemplified by its integration into a harvesting vehicle, where quality is determined by predicting sugar and acid in grapes in the field

Data Mining

The availability of big data due to computerization and automation has generated an urgent need for new techniques to analyze and convert big data into useful information and knowledge. Data mining is a promising and leading-edge technology for mining large volumes of data, looking for hidden information, and aiding knowledge discovery. It can be used for characterization, classification, discrimination, anomaly detection, association, clustering, trend or evolution prediction, and much more in fields such as science, medicine, economics, engineering, computers, and even business analytics. This book presents basic concepts, ideas, and research in data mining

Selected Papers from the 9th World Congress on Industrial Process Tomography

Industrial process tomography (IPT) is becoming an important tool for Industry 4.0. It consists of multidimensional sensor technologies and methods that aim to provide unparalleled internal information on industrial processes used in many sectors. This book showcases a selection of papers at the forefront of the latest developments in such technologies

Advances in Image Processing, Analysis and Recognition Technology

For many decades, researchers have been trying to make computers’ analysis of images as effective as the system of human vision is. For this purpose, many algorithms and systems have previously been created. The whole process covers various stages, including image processing, representation and recognition. The results of this work can be applied to many computer-assisted areas of everyday life. They improve particular activities and provide handy tools, which are sometimes only for entertainment, but quite often, they significantly increase our safety. In fact, the practical implementation of image processing algorithms is particularly wide. Moreover, the rapid growth of computational complexity and computer efficiency has allowed for the development of more sophisticated and effective algorithms and tools. Although significant progress has been made so far, many issues still remain, resulting in the need for the development of novel approaches

Advanced Sensing, Fault Diagnostics, and Structural Health Management

Advanced sensing, fault diagnosis, and structural health management are important parts of the maintenance strategy of modern industries. With the advancement of science and technology, modern structural and mechanical systems are becoming more and more complex. Due to the continuous nature of operation and utilization, modern systems are heavily susceptible to faults. Hence, the operational reliability and safety of the systems can be greatly enhanced by using the multifaced strategy of designing novel sensing technologies and advanced intelligent algorithms and constructing modern data acquisition systems and structural health monitoring techniques. As a result, this research domain has been receiving a significant amount of attention from researchers in recent years. Furthermore, the research findings have been successfully applied in a wide range of fields such as aerospace, manufacturing, transportation and processes