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IUGG XXIV General Assembly July 2-13, 2007 Perugia, Italy<br />

(S) - <strong>IASPEI</strong> - International Association of Seismology and Physics of the Earth's<br />

Interior<br />

JSS007 Oral Presentation 1952<br />

Three - Dimensional resistivity model of the Volcano Elbrus (Northern<br />

Caucasus) revealed from MT and satellite data<br />

Prof. Viacheslav Spichak<br />

EM data interpretation methodology Geoelectromagnetic Research Center IPE RAS IAVCEI<br />

Borisova Valeriya, Fainberg Edward, Khalezov Alex, Goidina Aleksandra<br />

Construction of the 3D resistivity model of the volcano requires array EM survey provided over the<br />

whole surface, which is often difficult due to its relief surface and inaccessibility of some zones<br />

surrounding the summit. This problem could be overcome by using a new approach, which combines<br />

analysis of both ground and satellite data. It is based on the method of the correlation similitude, which<br />

enables to fill the gaps in the EM data using other geological and/or geophysical data, correlating with<br />

the resistivity values. In particular, the latter ones could consist from the tectonic fragmentation of the<br />

rocks obtained by analysis of the satellite photographs of the surface using the method developed in<br />

(Nechaev, 1999). In turn, it is based on the estimation of the coefficient of the tectonic fragmentation<br />

(CTF) from the specific lineaments' lengths determined by the photographs of the studied area. The<br />

approach mentioned above was used in order to construct a 3D resistivity model of the Elbrus volcano<br />

(northern Caucasus) by MT data measured along one longitudinal profile crossing its summit. Twodimensional<br />

inversion of the MT data resulted in a resistivity values in the same nodes of the grid,<br />

where the CTF was determined. A special neural network based technique was used in order to extract<br />

the subset of these nodes, which supports the biggest correlation ratio between these two parameters.<br />

At the next step an artificial neural network was taught to correspondence of these parameters<br />

determined only in the selected nodes followed by reconstruction of the resistivity distribution in the<br />

whole area from the CTF values. The analysis of the constructed resistivity model resulted in detection<br />

of the relatively conductive body at the depth 40 km (conductivity - 0.04 S/m, dimensions in vertical<br />

axis, latitude and longitude being equal to 20 km, 35km and 15km, accordingly), which can be treated<br />

as a magma chamber. The model of the Elbrus volcano can be used for solution of two important tasks<br />

related to the monitoring of its activity: optimization of the EM survey network and determination of the<br />

background level for detection of the time and spatial variations of the manifestations of the tectonic<br />

activity leading to the eruptions.<br />

Keywords: magnetotelluric, volcano, three dimensional

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