Deep geothermal exploration by means of electromagnetic methods: New insights from the Larderello geothermal field (Italy)

The 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

Rilevamento geologico ed informatizzazione della cartografia geologica, in zona Catabbio - San Martino sul Fiora (sud ovest Monte Amiata), finalizzati all'esplorazione geotermica dell'area

Il presente lavoro di tesi è stato svolto con l’obiettivo di esplorare ai fini geotermici un’area posta a sud del Monte Amiata. L’area in esame, ricade nel foglio 129 della topografia 1:100000 dell’IGM, si estende per circa 35 km2 tra le valli del Fiume Albegna e del Fiume Fiora in prossimità dei centri abitati di Catabbio e San Martino sul Fiora (Provincia di Grosseto). L’obiettivo è la raccolta dei dati di base per la valutazione del potenziale geotermico di un’area attraverso l’attività esplorativa geologica di campagna. Il rilevamento geologico finalizzato alla definizione dell’assetto stratigrafico – strutturale rappresenta l’attività di base dalla quale non possono prescindere tutte le tecniche esplorative geofisiche ed idrogeochimiche necessarie per la ricostruzione di un modello concettuale di un campo geotermico. Il risultato è una carta geologica alla scala 1:10000 corredata dalle relative sezioni geologiche. È stata, inoltre, focalizzata l’attenzione sulle manifestazioni geotermiche e sulle mineralizzazioni idrotermali espressione diretta rispettivamente dei sistemi idrotermali attivi e fossili. Al fine ultimo di delineare un modello concettuale geotermico, la carta geologica è stata confrontata con i dati geofisici disponibili

A Review of Geophysical Modeling Based on Particle Swarm Optimization

This paper reviews the application of the algorithm particle swarm optimization (PSO) to perform stochastic inverse modeling of geophysical data. The main features of PSO are summarized, and the most important contributions in several geophysical felds are analyzed. The aim is to indicate the fundamental steps of the evolution of PSO methodologies that have been adopted to model the Earth’s subsurface and then to undertake a critical evaluation of their benefts and limitations. Original works have been selected from the existing geophysical literature to illustrate successful PSO applied to the interpretation of electromagnetic (magnetotelluric and time-domain) data, gravimetric and magnetic data, self-potential, direct current and seismic data. These case studies are critically described and compared. In addition, joint optimization of multiple geophysical data sets by means of multi-objective PSO is presented to highlight the advantage of using a single solver that deploys Pareto optimality to handle diferent data sets without conficting solutions. Finally, we propose best practices for the implementation of a customized algorithm from scratch to perform stochastic inverse modeling of any kind of geophysical data sets for the beneft of PSO practitioners or inexperienced researchers

Particle swarm optimization for simultaneous analysis of Magnetotelluric (MT) and Time Domain EM (TDEM) data

We 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

Joint optimization of geophysical data using multi-objective swarm intelligence

The 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

Geothermal resources within carbonate reservoirs in western Sicily (Italy): A review

Abstract Low-to-medium temperature fluid reservoirs hosted in carbonate rocks are some of the most promising and unknown geothermal systems. Western Sicily is considered a key exploration area. This paper illustrate a multidisciplinary and integrated review of the existing geological, geochemical and geophysical data, mainly acquired during oil and gas explorations since the 1950s, specifically re-analyzed for geothermal purposes, has led to understanding the western Sicily geothermal system as a whole, and to reconstructing the modalities and particular features of the deep fluid circulation within the regional reservoir. The data review suggests the presence of wide groundwater flow systems in the reservoir beneath impervious cap rocks. We identified the main recharge areas, reconstructed the temperature distribution at depth, recognized zones of convective geothermal flow, and depicted the main geothermal fluid flow paths within the reservoir. We believe that our reconstruction of geothermal fluid circulation is an example of the general behavior of low-to-medium enthalpy geothermal systems hosted in carbonate units on a regional scale. Due to the recent technological developments of binary plants, these systems have become more profitable, not only for geothermal direct uses but also for power production

Three-Dimensional Magnetotelluric Characterization of the Travale Geothermal Field (Italy) Remote Sens. 2022, 14, 542.

The geoelectrical features of the Travale geothermal field (Italy), one of the most productive geothermal fields in the world, have been investigated by means of three-dimensional (3D) magnetotelluric (MT) data inversion. This study presents the first resistivity model of the Travale geothermal field derived from derivative-based 3D MT inversion. We analyzed MT data that have been acquired in Travale over the past decades in order to determine its geoelectrical dimensionality, directionality, and phase tensor properties. We selected data from 51 MT sites for 3D inversion. We carried out a number of 3D MT inversion tests by changing the type of data to be inverted, the inclusion of static-shift correction at some sites where new time-domain electromagnetic soundings (TDEM) were acquired, the grid rotation, as well as the starting model in order to assess the connection between the inversion model and the geology. The final 3D model herein presents deep elongated resistive bodies between the depths of 1.5 and 8 km. They are transverse to the Apennine structures and suggest a correlation with the strike-slip tectonics. Comparison with a seismic velocity model and well log data suggests a highly-fractured volume of rocks with vapor-dominated circulation. The outcome of this study provides new insights into the complex geothermal system of Travale

Data integration and conceptual modelling of the Larderello geothermal area, Italy

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Particle Swarm Optimisation of Electromagnetic Soundings

We 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 of Electromagnetic Data with Parallel Computing in the 2D Case

This work presents the application to electromagnetic data processing of the particle swarm optimization (PSO) algorithm, with the advantage of its high speed of convergence to the problem solution compared with other evolutionary methods. We focus on the inversion of MT synthetic data in the two-dimensional case. The PSO problem is solved complying with upper and lower bounds and a priori information, which is initially given only to a small amount of particles of the swarm. The fitness function is properly defined including smoothing parameter (Occam's razor). Since it is a computationally demanding problem, a practical tool of parallel computing is tested and validated, thus allowing large computation time savings. Results show encouraging outcomes in terms of minimization of fitness function and data fitting. This approach represents the starting point for the 2D PSO application to MT data, Audio Magneto Telluric data and other near surface applications implying two-dimensional interpretation