GNGTS 2015 - Atti del 34° Convegno Nazionale

effect of data errors on the resolution obtained. However, most of the optimization techniques used so far have not sufficiently taken into account the effects of noise on apparent resistivity data. Generally, in ERT the problem due to errors on data caused by improper electrode positioning is not adequately considered. This error may be higher in steep or heavily vegetated areas and it generates an incorrect estimate of the geometric factor. To reduce the effect of this type of error on the resulting electrical tomography it is possible to select datasets that include arrays with relatively low geometric factors and therefore less sensitive to position errors (Wilkinson et al. , 2008). The study of the influence of errors on the resolution of the inverse model and especially on its ability to retrieve correct information of the subsurface is important to understand how the performance vary from a few simple parameters such as the total number of measurements of the data set and the distribution of the geometric factor values. The goal of this work is to study how the reliability of inverse model depends on a few basic parameters, as the combination of potential spacing and dipolar distance and, consequently, the number of measurements and of current dipoles, considering also how error affects inversion. The number of current dipole used is crucial, when using multichannel resistivity-meters, because it determines the overall acquisition time. A systematic comparison is presented between four 2D resistivity models and their images, obtained by the inversion of synthetic datasets relating to four different arrays: dipole-dipole (DD), pole-dipole (PD), Wenner-Schlumberger (WS) and multiple gradient (MG). For DD, PD and WS arrays a progression of eight different datasets are considered, by increasing the number of current dipoles but obtaining approximately the same amount of measures, and so increasing the investigation time. For MG array a progression of six datasets is obtained by increasing the current dipoles and so the lateral coverage. The goal is to study how this affect the resolution and the reliability of the tomographic inversion, particularly in presence of buried structures. Both noise-free and noisy data have been calculated and inverted. The results are compared using quality parameters of the reliability of the inversion. These are calculated for each cell of the first inverse model, and subsequently a mean value is obtained for the entire Tab. 1 - Parameters used for each data set. Array Pattern parameters 1 a max = 1; n max = 35 2 a max = 2; n max = 17 3 a max = 3; n max = 11 DD 4 a max = 4; n max = 8 PD 5 a max = 5; n max = 6 WS 6 a max = 6; n max = 5 7 a max = 7; n max = 4 8 a max = 8; n max = 3 1 e = 1-8; c = 1 2 e = 1-8; c = 2 MG 3 e = 1-8; c = 3 4 e = 1-8; c = 4 5 e = 1-8; c = 5 6 e = 1-8; c = 6 100 GNGTS 2015 S essione 3.2