A realistic inversion algorithm for magnetic anomaly data: the Mt. Amiata volcano test

The aim of this work is the formulation of a 3D model of the Mt. Amiata volcanic complex (Southern Tuscany)
 by means of geomagnetic data. This work is shown not only as a real test to check the validity of the inversion
 algorithm, but also to add information about the structure of...

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Bibliographic Details
Main Authors: C. Carmisciano, F. Caratori Tontini, N. Beverini, O. Faggioni, I. Nicolosi
Format: Article
Language:English
Published: Istituto Nazionale di Geofisica e Vulcanologia (INGV) 2003-06-01
Series:Annals of Geophysics
Subjects:
Online Access:http://www.annalsofgeophysics.eu/index.php/annals/article/view/3425
Description
Summary:The aim of this work is the formulation of a 3D model of the Mt. Amiata volcanic complex (Southern Tuscany)
 by means of geomagnetic data. This work is shown not only as a real test to check the validity of the inversion
 algorithm, but also to add information about the structure of the volcanic complex. First, we outline briefly the
 theory of geomagnetic data inversion and we introduce the approach adopted. Then we show the 3D model of the
 Amiata volcano built from the inversion, and we compare it with the available geological information. The most
 important consideration regards the surface distribution of the magnetization that is in good agreement with rock
 samples from this area. Moreover, the recovered model orientation recall the extension of the lava flows, and as a
 last proof of validity, the source appears to be contained inside of the topographic contour level. The credibility of
 the inversion procedure drives the interpretation even for the deepest part of the volcano. The geomagnetic signal
 appears suppressed at a depth of about 2 km, but the most striking consequence is that sub-vertical structures are
 found even in different positions from the conduits shown in the geologic sections. The results are thus in good
 agreement with the information obtained from other data, but showing features that had not been identified, stressing
 the informative power of the geomagnetic signal when a meaningful inversion algorithm is used.
ISSN:1593-5213
2037-416X