Abstract
Geoinversion takes off different forms to assess the subsurface formations more noticeably. The evolution of soft computing inversion technique makes the geoinversion to the next level of modelling parameters. In this research work, the novel neuro fuzzy pattern recognition approach was introduced to solve the non-linearity involved in geoelectrical resistivity data for appraising the subsurface parameters. The novelty encompasses in generating the patterns using Artificial Neural Networks (ANN) for the geoelectrical resistivity data obtained from the Vertical Electrical Sounding (VES) data as well as the pattern recognition done by the Adaptive Neuro Fuzzy Inference System (ANFIS) algorithm is predominant in mitigating the near world truth information that is available. Moreover, the ambiguities of the principle of equivalence have been reduced further by incorporating the Dar-Zarrouk parameter evaluation of longitudinal conductance and transverse resistivity. Thus, this tool could be a good alternate for any conventional algorithm for unravelling such complex problems.
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