Abstract:
This paper results the research carried on the 2D resistivity inversion problem, where resistivity distribution is
determined from the apparent resistivity measurements using the Artificial Neural Networks. Neural Network (NN) is
trained with the synthetic data generated using a 56 multi electrode Wenner array with 1 m electrode spacing. The
geoelectrical model studied show encouraging results for the applicability of the well trained NN 's as a fast 2D
resistivity inversion tool for field resistivity measurements
