GNGTS 2015 - Atti del 34° Convegno Nazionale

Forte E., Dossi M., Pipan M., and Colucci R.R., 2014a, “Velocity analysis from common offset GPR data inversion: theory and application to synthetic and real data”, Geophysical Journal International, vol. 197, pp. 1471-1483 Forte E., Dossi M., Colle Fontana M., and Colucci R.R., 2014b, “4-D quantitative GPR analyses to study the summer mass balance of a glacier: a case history”, Proceedings of the 15th International Conference on Ground Penetrating Radar, Brussels, Belgium, pp. 352-356, ISBN 978-1-4799-6789-6 Forte E., Dossi M., Pipan M., and Del Ben A., 2015, “Automated phase attribute-based picking applied to reflection seismics”, Geophysics, submitted Geletti, R., Zgur F., Del Ben A., Buriola F., Fais S., Fedi M., Forte E., Mocnik A., Paoletti V., Pipan M., Ramella R., Romeo R., and Romi A., 2014, “The Messinian Salinity Crisis: new seismic evidence in the West-Sardinian Margin and Eastern Sardo-Provençal basin (West Mediterranean Sea)”, Marine Geology, vol. 351, pp. 76-90 Hoyes J., and Cheret T., 2011, “A review of ‘global’ interpretation methods for automated 3D horizon picking”, The Leading Edge, vol. 30, pp. 38-47 Saarenketo T., and Scullion T., 2000, “Road evaluation with ground penetrating radar”, Journal ofApplied Geophysics, vol. 43, no. 2-4, pp. 119-138 Sabbione J.I., and Velis D., 2010, “Automatic first-breaks picking: New strategies and algorithms”, Geophysics, vol. 75, no. 4, pp. V67-V76 Taner M.T., Koehler F., and Sheriff R.E., 1979, “Complex seismic trace analysis”, Geophysics, vol. 44, no. 6, pp. 1041-1063 GNGTS 2015 S essione 3.3 147 3D MAGNETOTELLURIC RESPONSE IN PRESENCE OF RESISTIVITY DISPERSION: SNAKE RIVER PLAIN (IDAHO) EXAMPLE R. Esposito 1 , A. Troiano 2 , M.G. Di Giuseppe 2 , D. Patella 3 , C. Troise 2 , G. De Natale 2 , R.M. Castelo Branco 1 1 Federal University of Ceará, Fortaleza, Brazil 2 Istituto Nazionale di Geofisica e Vulcanologia - Osservatorio Vesuviano, Naples, Italy 3 Department of Physical Sciences, University Federico II, Naples, Italy Introduction. Resistivity dispersion is a known phenomenology, which in geophysics constitutes the basis of the Induced Polarization (IP) prospecting method (Seigel, 1959; Wait, 1959; Bertin and Loeb, 1976; Sumner, 1976; Fink et al. , 1990). In the frequency domain (FD), the dispersion consists in a variation of the resistivity parameter as the frequency of the exciting current is changed. The dispersive resistivity, called impedivity (Patella, 1993), is a complex function of frequency. At vanishing frequency, however, the impedivity is real and coincides with the classical resistivity parameter used in DC geoelectrical methods. A real asymptote is also approached by the impedivity as frequency tends to infinity. It has been shown that the electrical dispersion phenomenology can influence the magnetotelluric (MT) response (Stoyer, 1976; Patella, 1987). The detection and spatial definition of impedivity effects by MT can give a notable contribution to the understanding of the rock physical properties, well beyond the limited exploration depths of some tens m, reachable by the standard Induced Polarization (IP) equipments. Hydrocarbon and geothermal exploration are application fields, where MT is an ideal approach to detect dispersion-affected zones. These zones are fractured portions of rock, which have undergone diffuse alterations due to chemical interaction with uprising light hydrocarbons and hot fluids. These altered zones are considered reliable markers of the presence of exploitable reservoirs underneath. Dispersion effects in MT were experimentally recognized and modeled by 1D and 2D tools in volcanic and geothermal areas (Coppola et al ., 1993; Patella et al. , 1991; Giammetti et al ., 1996; Di Maio et al. , 1997, 2000; Mauriello et al. , 2000, 2004), and in hydrocarbon exploration (e.g., He et al. , 2010). The paper analyses the 3Dmagnetotelluric (MT) response in presence of resistivity frequency dispersion. The aim of this paper is to further study the influence of the electric dispersion on MT, by analyzing the synthetic responses generated by a 3D body. 3D IP effects have