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Marceau GRESSE


Localisation : Chambéry
Email : marceau.gresse@gmail.com


3-D Electrical Resistivity Image of Solfatara volcano (South Italy)

Electrical Resistivity Tomography : acquisition processing and inversion
In order to characterize the subsurface electrical conductivity of the Solfatara volcano, 73,987 transfer resistances were collected along 63 ERT profiles between 2008 and 2016.

An unstructured mesh of the Solfatara volcano was constructed with 902,919 tetrahedral elements and 180,211 finite-element nodes using TetGen algorithm (Si, 2006). The mesh was delimited by electrical resistivity surveys and covers a 0.68 km² ovoid area. The surface topography was integrated using the 1-m-accuracy DEM. Mesh refinement was achieved near the electrodes location to improve the numerical accuracy (Johnson et al., 2010).

Each transfer resistance value was obtained by stacking 3 to 7 individual measurements. Only measurements with a standard deviation below 5 % were retained for the inversion. At the end of the filtering process, only 43,432 transfer resistance were kept for the inversion.The latter was performed with E4D code (Johnson et al., 2010), with L2-norm.

The electrical conductivity inversion is a non-unique problem (Loke and Barker, 1996). Hence, to improve the inversion of subsurface conductivity, additional constraints and a priori information can be used (Doetsch et al., 2012 ; Johnson et al., 2012 ; Zhou et al., 2014). A prior conductivity distribution was used as a starting model. It was obtained by interpolation of the 3-D resistivity model of Audio-Magnetotellurics (AMT) data inversion with a spatial resolution of 50 m . As a result, the computation time was reduced and the model accuracy improved. Moreover, we applied specific inversion constraints on some selected areas, such as Fangaia mud pool, whose conductivity was fixed at the measured water conductivity, i.e. 1 S/m.

Preliminary results
The resistivity model highlights the main geological units : Monte Olibano lava dome and Solfatara crypto-dome that appear as two resistive bodies (50-100 Ω.m). At the top of the rim, the last eruptive deposits are clearly delineated with medium resistivity values (20-60 Ω.m). These results are consistent with the geological map performed by Isaia et al., (2015).

Secondly, the resistivity model clearly revealed the contrasting geometry of hydrothermal fluids flow in the Solfatara crater. A channel-like conductive structure was interpreted as the condensate flowing from the main fumarolic area down to the liquid-dominated area of Fangaia mud pool. This interpretation of fluid circulation is consistent with the negative Self-Potential anomaly and with surface observations.

- Paper submitted to JGR S-L.-

clip of the 3-D electrical resistivity model of the Solfatara crater (Ω m), draped with a surface temperature (°C). The video slices the volcano from W to E and reveals the Fangaia liquid-dominated plume, Mt Olibano, Solfatara crypto-dome, eruptive deposits at the top of the rim, and the resistive gas-dominated reservoir feeding the BG fumarole thought a 10-m tick resistive channel.

Physical model of a fumarolic system inferred from a high-resolution 3-D resistivity image of Solfatara volcano)

The geophysical images combined with the geochemical data allowed us to build up a multiphase fluid flow model of the Bocca Grande and and Bocca Nuova fumaroles using the TOUGH 2 code. Our results show that the distinct resistivity structure, temperature, and water content of the both fumaroles are due to the particular geometry of the condensate flow that intersects and contaminates the Bocca Nuova but not the Bocca Grande fumarole.

- Paper in prep-


Loke, M. H., and R. D. Barker (1996), Rapid least-squares inversion of apparent resistivity pseudosections by a quasi-Newton method1, Geophysical Prospecting, 44(1), 131-152.

Si, H. T. (2006), A quality tetrahedral mesh generator and three-dimensional delaunay triangulator.

Johnson, T. C., R. J. Versteeg, A. Ward, F. D. Day-Lewis, and A. Revil (2010), Improved hydrogeophysical characterization and monitoring through parallel modeling and inversion of time-domain resistivity and induced-polarization, Geophysics, 75(4), doi:10.1190/1.347551.

Doetsch, J., N. Linde, M. Pessognelli, A. G. Green, and T. Günther (2012), Constraining 3-D electrical resistance tomography with GPR reflection data for improved aquifer characterization, Journal of Applied Geophysics, 78, 68-76, doi:10.1016/j.jappgeo.2011.04.008.

Zhou, J., A. Revil, M. Karaoulis, D. Hale, J. Doetsch, and S. Cuttler (2014), Image-guided inversion of electrical resistivity data, Geophysical Journal International, 197(1), 292-309, doi:10.1093/gji/ggu001.

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