The presence of an underground air-filled cavity modifies the distribution of the electrical potential. One of the weak points of the resistivity method for the detection of air-filled cavities is the data processing required for quantifying depth and size of an air-filled cavity. One possible way is to use data inversion. At first, numerical computations have been undertaken to look for the major parameters influencing the measurements in an air-filled cavity detection problem with resistivity technique. Then an original inverse approach of resistivity measurements is proposed. In this approach apparent resistivity is a multivariate function, variables being the depth (H), size (X, Y, Z) and surface location (Xa). Thus we have: Pa = f (H, X, Y, Z, Xa). With numerical computations three different data bases are built. Experimental data are compared to theoretical data from the different data bases by using error criteria which allow us to get depth, size and surface location of the cavity. Finally, one example of the results obtained by this inversion approach is gi ven on real field data


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