In this work, the gravity anomaly signal beneath Mount Amiata and its surroundings have been analysed to reconstruct the subsurface setting. In particular, the work focuses on the investigation of the geological bodies responsible for the Bouguer gravity minimum observed in this area. Different approaches for understanding the Bouguer gravity anomaly source distribution, including the calculation of the first vertical derivative of the gravity signal, the estimation of the depth source using power spectrum analysis and the pseudo-3-D forward modeling, have been considered. The gravity data employed were acquired from different institutions ENI, OGS, USDMA and Servizio Geologico d'Italia and collected in a unique data set kindly made available by ENI. It comes from about 50 000 stations, randomly distributed, which cover Central Italy, with a spacing of less than 1 km. We dedicated an active effort in: (1) Defining the stratigraphic model (i.e. definition of the primary lithomechanical layers within the sedimentary cover and the upper crust). (2) Calculation of a new data set of density data derived from the velocity data collected by active seismic surveys. (3) Integration of stratigraphy, literature and new data in a comprehensive model. The results of this study depict a body, with a density of 2.35 g cm-3, representing the remnant magmatic chamber of Mount Amiata,which is responsible of the observed gravimetric minimum. The top of the magmatic body is upward-convex, dislocated at a depth comprised between 4.5 (beneath the volcano) and 7.5 km (in the peripheral zones) and draped by 2 km thick, highly fractured hard rocks that could represent the fractured aureole of the magmatic body itself. The 3-D modeling also defines the geometry of the Neogene Radicofani basin, close to the eastern flank of the Mount Amiata and is imaged as a bowl-shaped basin with an average depth of about 1500 m, and a maximum depth of about 2000 m reached towards north.
|Titolo:||The gravity anomaly of Mount Amiata; different approaches for understanding anomaly source distribution|
|Data di pubblicazione:||2017|
|Appare nelle tipologie:||1.1 Articolo in rivista|