Estimation of subsurface strata of earth using Adaptive Neuro-Fuzzy Inference System (ANFIS)

Abstract

Soft computing techniques are widely used for the applications on most of the nonlinear problems related to the real world. Earth’s most of the nonlinear characteristics exhibit the uncertainty problem that has to be interpreted with most of the advanced soft computing tools. Here the three layer electrical resistivity data has taken for interpreting the subsurface parameters of the earth using Adaptive Neuro-Fuzzy inference (ANFIS) technique. ANFIS can be predictably used for most of the nonlinear problems. Its membership functions and rules with adjustable parameters will help the interpretation technique with less error percentage results. In the present study, the program is specially designed for the interpretation of three layer electrical resistivity data. The network model is successful in training with large number of data sets available. Interpretation using ANFIS technique will give the promising results with good accuracy. With much less error percentage, the program supports all types of three layer electrical resistivity data more than a conventional method can do. Typical problems with parameter estimation can be done more efficiently with this ANFIS program.