GNGTS 2019 - Atti del 38° Convegno Nazionale

GNGTS 2019 S essione 3.2 663 Fiorucci M., Marmoni G.M., Martino S. and Mazzanti P.; 2018: Thermal response of jointed rock masses inferred from infrared thermographic surveying (Acuto test-site, Italy). Sensors, 18 (7), 2221. Doi: 10.3390/s18072221. Macciotta R., Martin C.D., Cruden D.M., Hendry M. and Edwards T.; 2017: Rock fall hazard control along a section of railway based on quantified risk. Georisk, 11 , 272–284, Taylor & Francis. doi:10.1080/17499518.2017.1293 273 Provost F., Malet J.P., Hibert C., Helmstetter A., Radiguet M., Amitrano D., Langet N., Larose E., Abancò C., Hürlimann M., Lebourg T., Levy C., Le Roy G., Ulrich P., Vidal M. and Vial B.; 2018: Towards a standard typology of endogenous landslide seismic sources. Earth Surf. Dyn., 6 , 1059–1088. doi:10.5194/esurf-6-1059-2018 Spillmann T., Maurer H., Green A.G., Heincke B., Willenberg H. and Husen S.; 2007: Microseismic investigation of an unstable mountain slope in the Swiss Alps. Journal of Geophysical Research, 112 . Zhuang D., Ma K., Tang C., Cui X. and Yang G.; 2019: Study on crack formation and propagation in the galleries of the Dagangshan high arch dam in Southwest China based on microseismic monitoring and numerical simulation. Int. J. Rock Mech. Min. Sci., 115 , 157–172. doi:10.1016/j.ijrmms.2018.11.016 GLOBAL INVERSION OF ELECTRICAL RESISTIVITY TOMOGRAPHY DATA G. De Donno, M. Cercato “Sapienza” Università di Roma – DICEA, Area Geofisica, Italy Introduction. The ERT (Electrical Resistivity Tomography) technique has been applied to numerous problems for decades, involving both the geological field - i.e. aquifer characterization, cavities detection, landslide modelling, soils layering (e.g. Storz et al. 2000) and the anthropogenic environment - i.e. archaeological prospection, building characterization, landfills, contaminated sites (e.g. Chambers et al. , 2006). The effectiveness of an ERT investigation mainly depends on the electrode spacing, the array configuration, the signal-to- noise ratio and the type of algorithm used for inversion (Cardarelli and De Donno 2019). In the last decades, in almost all research works concerning ERT applications, a local procedure (e.g. Occam’s inversion) has been used for inverting for resistivity, even though the solution could be trapped into local minima of the misfit function. The few attempts of applying global inversion algorithms to ERT data (Chunduru et al. 1996, Sen and Stoffa 2013) were restricted to very simple case studies (few electrodes and few pixels) due to the huge computational effort needed for solving the non-linear forward problem for a significant number of random steps (often > 10 4 ) required to explore the model space. In addition, although using a fine mesh for the forward solution, the above mentioned authors employed only spline functions on few selected nodes for inversion. The aim of this work is to apply the VSFA (very Fast Simulated Annealing) algorithm for inversion of ERT data using the VEMI software (De Donno and Cardarelli 2017) developed in Matlab within the EIDORS environment (Adler and Lionheart 2006). The global inversion algorithmdeveloped is potentially capable to deal with 2D and 3Dmulti-electrode configurations and complex geometries often encountered in geological and engineering applications. Forward modelling. The resistive response of a subsoil is generally described by the Poisson’s equation, under the hypothesis of an external point source (e.g. Dey and Morrison, 1979): (1) where σ is the electrical conductivity, φ the electric potential, r ≡ r ( x, y, z ) the position vector, I the injected current, δ the Dirac’s function, r s ≡ r s ( x s , y s , z s ) the position vector of the source and D the domain.The point-source hypothesis holds where the electrode spacing is large against electrode size and penetration depth, which is the case of common ERT studies.