1,720,983 research outputs found
Deep geothermal exploration by means of electromagnetic methods: New insights from the Larderello geothermal field (Italy)
Full text linkThe main target of this research is the improvement of the knowledge on the deep structures of the Larderello-Travale geothermal field (Tuscany, Italy), with a focus on the Lago Boracifero sector, particularly on the heat source of the system, the tectonics and its relation with the hydrothermal circulation.
In the frame of the PhD program and of the IMAGE project (Integrated Methods for Advanced Geothermal Exploration; EU FP7), we acquired new magnetotelluric (MT) and Time Domain EM (TDEM) data in a key sector of the field (Lago Boracifero). These data integrate the MT datasets previously acquired in the frame of exploration and scientific projects.
This study is based also on a integrated modelling, which included and organized in Petrel (Schlumberger) environment, a large quantity of geological and geophysical data.
We also propose an integrated approach to improve the reliability of the 2D MT inversion models, by using external information from the integrated model of the field as well as an innovative probabilistic analysis of the MT data.
We present our attempt to treat the 1D magnetotelluric inverse problem with a probabilistic approach, by adopting the Particle Swarm Optimization (PSO), a heuristic method based on the concept of the adaptive behaviour to solve complex problems. The user-friendly software “GlobalEM” was implemented for the analysis and probabilistic optimization of MT data. The results from theoretical and measured MT data are promising, also for the possibility to implement different schemes of constrained optimization as well as joint optimization (e.g. MT and TDEM). The analysis of the a-posteriori distribution of the results can be of help to understand the reliability of the model.
The 2D MT inversion models and the integrated study of the Larderello-Travale geothermal field improved the knowledge about the deep structures of the system, with a relevant impact on the conceptual geothermal model.
In Micaschist and Gneiss complexes we observed a generally high electrical resistivity response locally interrupted by low resistivity anomalies that are well correlated with the most productive sectors of the field. A still partial melted igneous intrusion beneath the Lago Boracifero sector was detected based on the interpretation of the low resistivity anomalies located at a mid-crustal level (> 6 km).
New insights on the tectonics are proposed in this research. The fundamental role of a large tectonic structure, i.e. the Cornia Fault, located along the homonymous river, was highlighted. In our opinion, this fault played an important role in the geothermal evolution of the Lago Boracifero sector, favouring both the hydrothermal circulation and the emplacement of magma bodies.
In our opinion, the system can be ascribed to a “young convective and intrusive” field feed by a complex composite batholite
Joint optimization of geophysical data using multi-objective swarm intelligence
Full text linkThe joint inversion of multiple data sets encompasses the advantages of different geophysical
methods but may yield to conflicting solutions. Global search methods have been recently
developed to address the issue of local minima found by derivative-based methods, to analyse
the data compatibility and to find the set of trade-off solutions, since they are not unique. In
this paper, we examine two evolutionary algorithms to solve the joint inversion of electrical
and electromagnetic data. These nature-inspired metaheuristics also adopt the principle of
Pareto optimality in order to identify the result among the feasible solutions and then infer the
data compatibility. Since the joint inversion is characterized by more than one objective, we
implemented the algorithm multi-objective particle swarm optimization (MOPSO) to jointly
interpret time-domain electromagnetic data and vertical electrical sounding. We first tested
MOPSO on a synthetic model. The performance of MOPSO was directly compared with that
of a multi-objective genetic algorithm, the non-dominated sorting genetic algorithm (NSGAIII),
which has often been adopted in geophysics. The adoption of MOPSO and NSGA-III
enabled avoiding both simplification into a single-objective problem and the use of a weighting
factor between the objectives. We tested the two methods on real data sets collected in the
northwest of Italy. The results obtained from MOPSO and NSGA-III were highly comparable
to each other and largely consistent with literature findings. The MOPSO performed a rigorous
selection of the best trade-off solutions and its convergence was faster than NSGA-III. The
analysis of the Pareto Front reported data incompatibility, which is very common for real data
due to different resolutions, sensitivities and depth of investigations. Notwithstanding this,
the multi-objective optimizers provided a complementary interpretation of the data, ensuring
significant advantages with respect to the separate optimizations we carried out using the
single-objective particle swarm optimization algorithm
Particle Swarm Optimisation of Electromagnetic Soundings
No full textWe discuss through synthetic and real data some the application of PSO in electromagnetic soundings. The suggested approach can be easily adapted to resistivity soundings (RS), time domain soundings (TDEM) , magneto-telluric (MT) and audio-magneto-telluric survey (AMT). We propose an overview on the PSO for solving 1D problems with a priori information and/or lateral constraints. The application of PSO on AMT data is suggested by the high speed of convergence to a problem's solution respect other evolutionary methods. Application on the synthetic dataset allow us to analyze the relevance of the setting parameters, and to select the optimal solutions when a priori information or additional constraints are introduced. We demonstrate how PSO could be an effective approach in AMT data processing (1D). The results can be selected as starting model for a subsequent gradient-based inversion
Particle swarm optimization for simultaneous analysis of Magnetotelluric (MT) and Time Domain EM (TDEM) data
Full text linkWe present an innovative, simultaneous 1D optimization of electromagnetic data. The proposed scheme is suitable for the simultaneous analysis of magnetotelluric (MT) and time-domain EM (TDEM) data based on the probabilistic and evolutionary particle swarm optimization (PSO) algorithm. The simultaneous optimization also identifies and removes the static shift from the MT data. In the proposed scheme, the static shift of the MT apparent resistivity curve is considered an additional parameter S to be optimized. We tested the suggested method on synthetic data and then applied it to the data from an electromagnetic geophysical study carried out in the geothermal area of Larderello-Travale (Tuscany, Italy). Apart from the novelty of using the PSO algorithm to estimate the model parameters by joint analysis, the simultaneous optimization of the static shift parameter addresses a major problem in MT: i.e., how to define and remove the galvanic effects on MT curves according to independent information, such as that provided by TDEM data. The procedure is expected to strongly influence the application of MT, particularly in geothermal exploration, which commonly relies extensively on EM methods
Electrical Resistivity Structures and their Relation to Geological Features at the Larderello Geothermal Field (Italy)
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A new repository of electrical resistivity tomography and ground penetrating radar data from summer 2022 near Ny-Ålesund, Svalbard.
No full textWe present the geophysical data set acquired in summer 2022 close to Ny-Ålesund (Western Svalbard, Brøggerhalvøya peninsula, Norway) as part of the project ICEtoFLUX (MUR/PRA2021 project-0027). The data set is composed of Electrical Resistivity Tomography (ERT) and GroundPenetrating Radar (GPR) surveys, which are well-known geophysical techniques for the characterization of glacial and hydrological processes and features. 18 ERT profiles and 10 GPR lines were acquired, for a total surveyed length of 9.3 km. The data have been organized in a consistent repository that includes both raw and processed (filtered) data. Some representative examples of 2D models of the subsurface are provided, that is, 2D sections of electrical resistivity (from ERT) and 2D radargrams (from GPR). These examples can support the identification of the active layer and the occurrence of spatial variation of soil conditions at depth. The aim of the investigation is to characterize the role of groundwater flow in correspondence of the active layer as well as through and/or below the permafrost. The data set is of major relevance because scant attention has been paid to the publication of geophysical data from the Ny-Ålesund area so far. Moreover, these geophysical data can foster multidisciplinary scientific collaborations in the fields of hydrology, glaciology, climate, geology, geomorphology, etc. To a large extent, the data set can provide new insight into the hydrological dynamics and polar and climate changes studies on the Ny-Ålesund are
Imaging the deep structures of the Larderello geothermal field (Italy) by electrical resistivity measurements: the IMAGE experiment
No full textElectromagnetic and DC methods for geothermal exploration in Italy - case studies and future developments
No full textGeothermal energy is a renewable and eco-compatible resource suitable for base-load power and thermal production, which means a daily continuous energy production. In the past few years this source has been of interest for governments, companies and research institutes worldwide that are working for the increase of geothermal exploitation with the aim of reducing greenhouse gas emissions and fossil fuels consumption. Italy was the first country (in 1913) where geothermal energy was exploited for industrial power production and is now the sixth-largest geothermal electricity producer in the world (Bertani, 2015). The geothermal potential of Italy, both for power production and direct uses, is really huge due to particular geological conditions; elsewhere it is mostly underexploited for non-technical barriers. In Italy, many industrial and scientific exploration pro¬jects have been carried out in the last few years for assessing shallow and deep geothermal resources. ElectroMagnetic (EM) methods play a fundamental role in the geothermal exploration due to particular sensitivity of the subsurface electrical resistivity (hereby resistivity) to hydro¬thermal circulation, thermal regime and rocks alteration. Many papers have been published on the study of geothermal areas by EM methods worldwide (Meju, 2002; Spichak and Manzella, 2009; Muñoz, 2014 and references therein). In this paper, we propose an updated state-of-the-art of the main electromagnetic and direct current methods for geother¬mal exploration in Italy, describing innovative case studies and including a discussion about the direction of new researches. The Magnetotellurics (MT) represents the most common and effective method for investigating deep geothermal res¬ervoirs. A case study in southern Tuscany is herein described. We will also focus the attention on the resistivity measure¬ments for shallow geothermal exploration by means of Airborne EM (AEM), Transient or Time Domain EM (TEM or TDEM) and Electrical Resistivity Tomography (ERT). Among the various scientific projects for geothermal exploration that the Italian National Research Council (CNR) carried out, the VIGOR project (evaluation of the geothermal potential of Regions of Convergence) for Southern Italy provided the occasion of detailed geoelectro¬magnetic studies for assessing shallow and deep geothermal resources (Manzella et al. 2013a, VIGOR website). Some cases study of the VIGOR project are briefly described as: i) the innovative application of Airborne EM data acquired over large areas in Sicily and applied to the assessment of shallow geothermal potential and ii) a Deep Electrical Resistivity Tomography (DERT) acquired on a thermal area in Calabria regio
Data integration and favourability maps for exploring geothermal systems in Sicily, southern Italy
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