Title:

Deep Fluid Circulation in the Travale Geothermal Area and Its Relation with Tectonic Structure Investigated by a Magnetotelluric Survey

Authors:

A. Manzella, V. Spichak, P. Pushkarev, D. Sileva, B. Oskooi, G. Ruggieri, Yu. Sizov

Key Words:

magnetotelluric, fluid circulation, modeling, electrical resistivity

Geo Location:

Travale, Italy

Conference:

Stanford Geothermal Workshop

Year:

2006

Session:

Geophysics

Language:

English

Paper Number:

Manzella

File Size:

908KB

View File:

Abstract:

The high enthalpy Italian geothermal fields are located in southern Tuscany and are characterized by shallow and deep reservoirs defined by fractures within sedimentary or metamorphic rocks, showing an apparent heterogeneously distributed permeability. The structure of the Travale geothermal area is characterized by NW-trending and NE-dipping normal faults. Heat flow maxima and vertical displacement of isotherms associated with recent normal fault were recognized, and suggested that fluid circulation is not randomly distributed, but correlated to the tectonic setting of the area. In order to get an idea about the geoelectrical structure of the studied area MagnetoTelluric data were collected at 59 sites in the frequency range between 360 and 0.001 Hz. Moreover, a remote system was operated simultaneously with the main survey on Sardinia Island, about 500 km off the survey area, in order to face the low frequency electromagnetic noise affecting the Italian peninsula due to direct current electrified railways.

MT data were processed either as single site or by means of robust routines for remote reference processing, using data from Sardinia or from another local site a few km apart depending on the availability and quality of the synchronized data. Time domain electromagnetic data and geological information provided a base for static shift corrections. Processed data were decomposed, and showed a main NW-SE strike, in accordance to the main tectonic direction of the area.

2D inversion results produced models of resistivity distribution that were related to main lithological changes and the geothermal system. The models provide also a correlation with the main active faults and the seismic features of the area, most probably linked to the geothermal fluid circulation. A preliminary 3D inversion has been carried out using artificial neural network approach.


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