1,720,972 research outputs found
Monitoring of levee breaching through remote sensing and artificial intelligence
No full textThe study of flooding events resulting from bank over-flooding and levee breaching is of large interest for both society and environment, because flood waves, resulting from levee failure, might cause loss of lives and destruction of properties and ecosystems. Understanding the subsoil mechanics and the fluid-solid interplay allows the stability condition estimate of dams, embankments and slopes and the development of early warning alarm systems. Changes in soil and hydraulic parameters are usually monitored by geotechnical and geophysical investigations that also provide the basic assumptions for developing hydraulic models. Nowadays, remote sensing approaches, including satellite techniques, are mainly used for flooding simulation studies. Indeed, remote sensing observations, such as discharge, flood area extent and water stage, have been used for retrieving flood hydrology information and modeling, calibrating and validating hydrodynamic models, improving model structures and developing data assimilation models. Although all these studies have contributed significantly to the recent advances, uncertainty in observations, as well as in model parameters and prediction, represents a critical aspect for using remote sensing data in the flooding defence. Compared to past and current methods for monitoring the fluvial levee failure, we propose a new procedure that provides a wide and fast alert system. The proposed methodological path is based on presumed relationships between ground level deformation and hydrological and surface soil properties, due to physical mechanisms and exhibited by geodetic and hydrological time series. The procedure is accomplished first through multi-methodological comparative analyses applied to geodetic, hydrological and soil-properties patterns, then through the mapping of the river zones prone to failure. Since the input consists of time series satellite-derived data, the geospatial Artificial Intelligence is applied for extracting knowledge from spatial big data and for increasing the performance of data computing
Estimation of Carbon Dioxide emissions along an active fault by using geoelectrical measurements
No full textIn the last twenty years, a growing interest is noticed in quantifying non-volcanic degassing, which could represent a significant input of CO2 into the atmosphere. Large emissions of non-volcanic carbon dioxide usually take place in seismically active zones, where the existence of a positive spatial correlation between gas discharges and extensional tectonic regimes has been confirmed by seismic data. Extensional stress plays a key role in creating pathways for the rising of gases at micro- and macro-scales, increasing the rock permeability and connecting the deep crust to the earth surface. Geoelectrical investigations, which are very sensitive to permeability changes, provide accurate volumetric reconstructions of the physical properties of the rocks and, therefore, are fundamental not only for the definition of the seismic-active zone geometry, but also for understanding the processes that govern the flow of fluids along the damage zone. In this framework, we present the results of an integrated approach where geoelectrical and passive seismic data are used to construct a 3D geological model, whose simulated temporal evolution allowed the estimation of CO2 flux along an active fault in the area of Matese Ridge (Southern Apennines, Italy). By varying the geometry of the source system and the permeability values of the damage zone, characteristic times for the upward migration of CO2 through a thick layer of silts and clays have been estimated and CO2 fluxes comparable with the observed values in the investigated area have been predicted. These findings are promising for gas hazard, as they suggest that numerical simulations of different CO2 degassing scenarios could forecast possible critical variations in the amount of CO2 emitted near the fault
Predicting electrical resistivity in hydrothermal and natural degassing geological systems through petrophysical and thermodynamic data: a machine learning approach
No full textHydrothermal and natural degassing geological systems present various hazards. Monitoring them is crucial to understanding their behavior, assessing risks comprehensively, and mitigating potential impacts on both the environment and human safety. Electrical resistivity, which is closely
related to water content, gas content, and fluid temperature, is a key parameter for studying these systems. However, existing mathematical relationships, such as Archie's law, have limitations, particularly in their applicability to a wide range of petrophysical and thermodynamic properties. Linking the observed variations in measured resistivity to variations in the dynamics of the hydrothermal or natural degassing system under investigation is not straightforward. The aim of this study is to establish a numerical relationship between petrophysical and thermodynamic input variables and resistivity data obtained from geoelectrical field surveys. This numerical relationship could predict changes in the electrical resistivity distribution based on variations in simulated petrophysical and thermodynamic values over time. Comparison between predicted and field resistivity data would ultimately validate the current dynamic state of the system, providing a powerful monitoring tool. To this end, two 3D petrophysical and thermodynamic numerical models for two natural degassing systems were constructed by 3D electrical resistivity tomography surveys using constraints derived from different types of data (e.g., geological, geochemical and/or hydrogeological data). The models were validated through the comparison of predicted temperature, pressure, and gas flow distributions with field survey data. We then trained a
Random Forest algorithm to predict the resistivity values for each cell of the models using the petrophysical and thermodynamic parameters of each cell as input and the field resistivity values as the target variable
Understanding the effects of leaking gas in geological carbon sequestration through geophysical characterization of natural CO2 gas emission systems
No full textGas leakage from deep geologic storage formations to the Earth’s surface is one of the main hazards in geological carbon sequestration and storage. Permeable sediment covers or natural and artificial pathways, such as faults and well structures, are the main factors controlling surface leakages. Therefore, the characterization of natural systems, where large amounts of CO2 are released, can be helpful for understanding the effects of potential gas leaks from storage carbon systems. In this framework, we propose a combined use of geoelectrical investigations (i.e., resistivity tomography and self-potential surveys) for characterizing natural CO2 leakage areas, as well as gas storage sites. Such methodologies appear to be among the most suitable for revealing spatial distributions of carbon dioxide and monitoring subsurface fluid migration processes, because of the strong dependence of the electrical properties of water-bearing permeable rock, or unconsolidated materials, on many factors relevant to CO2 storage (i.e., porosity, fracturing, water saturation, etc.). Indeed, the electric resistivity of porous water-bearing sediments decreases significantly when CO2 dissolves in pore-water, in contrast to the effect in the gas phase and supercritical CO2, while the anomalous concentrations of natural electric charge are directly related to carbon dioxide migration along porous and fractured rock systems. The effectiveness of the suggested multi-methodological geoelectrical approach is tested in some areas of natural CO2 degassing located in the Southern Apennines (Italy), which could represent natural analogues of gas storage sites. Specifically, electrical resistivity and self-potential surveys are targeted at reconstructing shallow buried fracture networks in the cap-rock and detecting preferential CO2 migration pathways. Our findings are promising for imaging the CO2 plume within a carbon storage reservoir and for identifying possible CO2 leakages through the cap-rock formation, suggesting that the proposed approach can be very helpful also for the monitoring of carbon sequestration systems
Modeling of non-volcanic CO2 earth degassing. Application to a case study from Ciorlano area (southern Apennines, Italy)
No full textIn the last twenty years a growing interest is noticed in studying the process of carbon dioxide degassing from the geosphere in various field of Earth Sciences, with the aim of defining relationship between gas flux on the ground and tectonic structures, quantifying deeply derived CO2 released into the atmosphere and studying volcanic and non-volcanic degassing processes (Frondini et al., 2018). While it is already recognized that volcanic degassing can introduce huge quantities of carbon dioxide into the atmosphere, only recent studies (Kerrick and Seward, 1996; Chiodini et al., 2000) have shown that non-volcanic degassing may be a globally significant input of CO2 into the atmosphere and that many areas where large emissions of non-volcanic carbon dioxide take place are also characterized by a some degree of permeability of the crust that often coincides with seismically active zones. Indeed, seismic data demonstrate the existence of a positive spatial correlation between gas discharges and extensional tectonic regimes and confirms that such processes would play a key role in creating pathways for the rising gases at micro- and macro-scales, increasing the rock permeability and connecting the deep crust to the earth surface. Therefore, the identification and the geometric characterization of the CO2-permeable active faults is fundamental, not only for the definition of the seismic-active zone geometry, but also for the understanding of the processes that govern the flow of fluids along the damage zone that convey the gases towards the surface. In this framework, numerical simulations of fluid flow in three-dimensional faulted models can help to identify the primary control parameters of fault-related fluid flow, their interactions, and to model the temporal evolution of the investigated system. In this work, we present the results of a numerical simulation of CO2 flow along an active fault in the Ciorlano area of Matese Ridge (Southern Apennines, Italy), which recent accurate geological and geochemical analyses classify as the area with the highest non-volcanic natural emissions of CO2 ever measured on Earth (Ascione et al., 2018)
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
High-resolution ERT imaging of CO2 degassing along active faults on the south-west flank of the Matese Mts. (Southern Apennines)
No full textThe emission of gas along active faults represents the shallow manifestation of a gases migration path from a deep natural source, and it indicates that the fault zones are characterized by high permeability, acting as drains in the crust . When these gases reach the surface, they are usually discharged into the atmosphere from small areas known as gas vents. Understanding gas migration along faults is a key scientific problem in many geoscience researches, such as geothermal exploration and geohazard assessment. The growing attention to this issue is related to the potential impact of the natural CO2 release on human health and ecosystems, groundwater quality, soil mineralogy and CO2 concentrations in the
atmosphere. In this framework, for the purposes of the gas hazard assessment, the geophysical prospecting methods are successfully and increasingly applied for the identification of active faults and for the detection and monitoring of CO2 degassing along them. In particular, over the last decade, geoelectrical surveys performed by electrical resistivity tomography (ERT) technique have proven to be among the most appropriate prospecting methods to detect spatial distributions of carbon dioxide, whose emission in non-volcanic areas is essentially controlled by fractures, faults and fault damage zones. Indeed, the ERT technique is able to identify the areas of influence of the gas vent as either conductive and resistive anomalies, depending on the geological environment and the physical, chemical and biological conditions of the investigated risk areas. In this work, we present the results of a high-resolution electrical resistivity tomography survey aimed to identify the active fault zones that control the release of significant CO2 flows in the Ailano area (Matese Mts., Southern Italy)
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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