Regularized solution of a nonlinear problem in electromagnetic sounding

We propose a regularization method to solve a nonlinear ill-posed problem connected to inversion of data gathered by a ground conductivity meter

Common-Reflection-Surface Stack with Global Simultaneous Multi-Parameter Velocity Analysis—A Fit for Shallow Seismics

In many regions, particularly coastal areas, population growth, overuse of water, and climate change have put quality and availability of water under threat. While accurate, predictive groundwater flow models are essential for effective water resource management, the precision of these models relies on the ability to determine the geometries of geological structures and hydrogeologic systems accurately. In complex geological settings or with deep aquifers, the drilling of observation wells becomes too costly and shallow seismic surveys become the method of choice. Common-Reflection-Surface stacking is being used by major oil companies for hydrocarbon exploration but can serve also as an advanced imaging method for near-surface seismic data. Its spatial stacking aperture covers a whole group of neighboring common midpoint gathers and, as such, a multitude of traces contribute to every single stacking process. Since the level of noise suppression is proportional to the number of contributing traces, Common-Reflection-Surface stacking generates a large increase in signal-to-noise ratio. In addition, the data-driven velocity analysis is a statistical process and is, as such, the more stable the more input traces it has. At the beginning, however, the spatial operator was only used for stacking, not for velocity analysis, since limiting computational demand was mandatory to obtain results within a reasonable time frame. Today’s computing facilities are thousands of times faster and even large efficiency gains do not justify the loss of effectiveness anymore that comes with a truncated velocity analysis. We show that this is particularly true for near-surface data with low signal-to-noise ratio and modest common midpoint fold. For the spatial velocity analysis, we present two options: (1) as reference, a global search of all three parameters of the Common-Reflection-Surface operator, and (2) as a quicker solution, a strategy that uses the two-parameter Common-Diffraction-Surface operator to obtain initial values for a local three-parameter optimization. For shallow P-wave data from a hydrogeological survey, we show that the computational cost of option (2) is one order of magnitude smaller than the cost of option (1), while the stack and corresponding normal-moveout velocities are very similar. Comparing the results of the spatial velocity analysis to those of preceding, computationally lighter, strategies, we find a significant improvement, both in stack section resolution and stacking parameter accuracy

Inversion of electrical conductivity data with Tikhonov regularization approach: some considerations

Electromagnetic induction measurements, which are generally used to determine lateral variations of apparent electrical conductivity, can provide quantitative estimates of the subsurface conductivity at different depths. Quantitative inference about the Earth’s interior from experimental data is, however, an ill-posed problem. Using the generalised McNeill’s theory for the EM38 ground conductivity meter, we generated synthetic apparent conductivity curves (input data vector) simulating measurements at different heights above the soil surface. The electrical conductivity profile (the Earth model) was then estimated solving a least squares problem with Tikhonov regularization optimised with a projected conjugate gradient algorithm. Although the Tikhonov approach improves the conditioning of the resulting linear system, profile reconstruction can be surprisingly far from the desired true one. On the contrary, the projected conjugate gradient provided the best solution without any explicit regularization (a = 0) of the objective function of the least squares problem. Also, if the initial guess belongs to the image of the system matrix, Im(A), we found that it provides a unique solution in the same subspace Im(A)

Inversion of multiconfiguration complex EMI data with minimum gradient support regularization: A case study

Frequency-domain electromagnetic instruments allow the collection of data in different configurations, that is, varying the intercoil spacing, the frequency, and the height above the ground. Their handy size makes these tools very practical for near-surface characterization in many fields of applications, for example, precision agriculture, pollution assessments, and shallow geological investigations. To this end, the inversion of either the real (in-phase) or the imaginary (quadrature) component of the signal has already been studied. Furthermore, in many situations, a regularization scheme retrieving smooth solutions is blindly applied, without taking into account the prior available knowledge. The present work discusses an algorithm for the inversion of the complex signal in its entirety, as well as a regularization method that promotes the sparsity of the reconstructed electrical conductivity distribution. This regularization strategy incorporates a minimum gradient support stabilizer into a truncated generalized singular value decomposition scheme. The results of the implementation of this sparsity-enhancing regularization at each step of a damped Gauss-Newton inversion algorithm (based on a nonlinear forward model) are compared with the solutions obtained via a standard smooth stabilizer. An approach for estimating the depth of investigation, that is, the maximum depth that can be investigated by a chosen instrument configuration in a particular experimental setting is also discussed. The effectiveness and limitations of the whole inversion algorithm are demonstrated on synthetic and real data sets

OR5: Imaging Geofisico

2006-11-28Sardegna Ricerche, Edificio 2, Località Piscinamanna 09010 Pula (CA) - ItaliaKick-off Meeting del Progetto GRIDA

Inversion of EM38 electrical conductivity data

In geophysical prospecting and environmental monitoring, the frequency domain electromagnetic induction technique has been developed for measuring the apparent soil electrical conductivity. A linear model can be formulated to described the response of the EM38, a ground conductivity meter. To image the subsurface conductivity profile from recorded data, the model has been inverted defining a Least Squares problem with Tikhonov approach improves the conditioning of the resulting linear systems, profile reconstruction can be surprisingly far from the expected conductivity behaviour

FDEM and ERT measurements for archaeological prospections at Nuraghe S'Urachi (West‐Central Sardinia)

Nuraghe S’Urachi is a monumental architectural complex in West Central Sardinia that was probably first built in the Bronze Age and remained occupied continuously into the early Roman Imperial period. It has been the object of systematic and largescale archaeological investigations in three different phases since 1948 when the first excavations revealed a complex building within a massive defensive wall and multiple towers. Intermittent fieldwork between the 1980s and 2005 subsequently showed that the central nuraghe might comprise up to five principal towers. In 2013, a new collaborative research project, sponsored by Brown University and the Municipality of San Vero Milis, brought together a multidisciplinary research project to investigate this important archaeological site. In this framework, multi-frequency and multi-coil electromagnetic measurements (FDEM) and Electrical resistivity tomography (ERT) were carried out in 2018, 2019, and 2020, over and close to the nuraghe towers, to gain a better understanding of the inner part of the main structure and to investigate the surrounding area that was intensively settled in Phoenician and Punic times. The preliminary results of the geophysical measurements provide new and interesting evidence that supports new hypotheses and suggests possible future archaeological and geophysical strategies to investigate the unexcavated part of the archaeological site of S’Urachi

Characterization of Dismissed Landfills Via Geophysical Techniques

In the context of waste landfill management, geophysical methods are a powerful tool for evaluating their impact on public health and environment. Noninvasive and cost-effective geophysical techniques rapidly investigate large areas with no impact on the system. This is essential for the characterization of the waste body and the evaluation of the liner integrity at the bottom of the landfill and leakage localization. Three case studies are described with the purpose of highlighting the potentiality of such techniques in landfill studies. The case studies show different site conditions (capped landfills, controlled closed systems, and unconfined systems) that limit the applicability of any other kind of investigation and, at the same time, highlight the versatility of the geophysical techniques to adapt to several field situations. Electrical and electromagnetic techniques proved to be the most efficient geophysical techniques for providing useful information to develop an accurate site conceptual model

A field-scale remediation of residual light non-aqueous phase liquid (LNAPL): chemical enhancers for pump and treat

The remediation of petroleum-contaminated soil and groundwater is a challenging task. The petroleum hydrocarbons have a long persistence in both the vadose zone and in the aquifer and potentially represent secondary and residual sources of contamination. This is particularly evident in the presence of residual free-phase. Pump-and-treat is the most common hydrocarbon decontamination strategy. Besides, it acts primarily on the water dissolved phase and reduces concentrations of contaminants to an asymptotic trend. This study presents a case of enhanced light non-aqueous phase liquid (LNAPL) remediation monitored using noninvasive techniques. A pilot-scale field experiment was conducted through the injection of reagents into the subsoil to stimulate the desorption and the oxidation of residual hydrocarbons. Geophysical and groundwater monitoring during pilot testing controlled the effectiveness of the intervention, both in terms of product diffusion capacity and in terms of effective reduction of pollutant concentrations. In particular, non-invasive monitoring of the reagent migration and its capability to reach the target areas is a major add-on to the remediation technique. Most of the organic contaminants were decomposed, mobilized, and subsequently removed using physical recovery techniques. A considerable mass of contaminant was recovered resulting in the reduction of concentrations in the intervention areas

Non-Invasive Survey Techniques to Study Nuragic Archaeological Sites: The Nanni Arrù Case Study (Sardinia, Italy)

The Italian territory of Sardinia Island has an enormous cultural and identity heritage from the Pre-Nuragic and Nuragic periods, with archaeological evidence of more than 7000 sites. However, many other undiscovered remnants of these ancient times are believed to be present. In this context, it can be helpful to analyze data from different types of sensors on a single information technology platform, to better identify and perimeter hidden archaeological structures. The main objective of the study is to define a methodology that through the processing, analysis, and comparison of data obtained using different non-invasive survey techniques could help to identify and document archaeological sites not yet or only partially investigated. The non-invasive techniques include satellite, unmanned aerial vehicle, and geophysical surveys that have been applied at the nuraghe Nanni Arrù, one of the most important finds in recent times. The complexity of this ancient megalithic edifice and its surroundings represents an ideal use case. The surveys showed some anomalies in the areas south–east and north–east of the excavated portion of the Nanni Arrù site. The comparison between data obtained with the different survey techniques used in the study suggests that in areas where anomalies have been confirmed by multiple data types, buried structures may be present. To confirm this hypothesis, further studies are believed necessary, for example, additional geophysical surveys in the excavated part of the site