This work presents the two-dimensional stochastic inverse modelling of a magnetotelluric profile from the Larderello geothermal area (Italy). For the first time, the algorithm Particle Swarm Optimization was applied to this kind of field data to investigate a complex electrical structure without the initial assumption given by an external starting model driving the inversion. The outcome was in good agreement with results of previous research with the advantage of a lower data misfit as well as the contribution that the modelling was not initially constrained by a priori information (e.g., from well-log or other geophysical methods) that, in geothermal areas, can be unavailable or even misleading.

STOCHASTIC INVERSE MODELING OF MAGNETOTELLURIC DATA FROM THE LARDERELLO-TRAVALE GEOTHERMAL AREA (ITALY) / Pace, F.; Santilano, A.; Godio, A.; Manzella, A.. - ELETTRONICO. - (2019), pp. 1-5. ((Intervento presentato al convegno 1st Conference on Geophysics for Geothermal and Renewable Energy Storage tenutosi a L'Aia, Paesi Bassi nel 8-12 September 2019 [DOI: 10.3997/2214-4609.201902507].

STOCHASTIC INVERSE MODELING OF MAGNETOTELLURIC DATA FROM THE LARDERELLO-TRAVALE GEOTHERMAL AREA (ITALY)

Pace F.;Santilano A.;Godio A.;
2019

Abstract

This work presents the two-dimensional stochastic inverse modelling of a magnetotelluric profile from the Larderello geothermal area (Italy). For the first time, the algorithm Particle Swarm Optimization was applied to this kind of field data to investigate a complex electrical structure without the initial assumption given by an external starting model driving the inversion. The outcome was in good agreement with results of previous research with the advantage of a lower data misfit as well as the contribution that the modelling was not initially constrained by a priori information (e.g., from well-log or other geophysical methods) that, in geothermal areas, can be unavailable or even misleading.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2752252
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