Review of Soft Computing Methods in Geophysical Applications: A comprehensive analysis of soft computing methods in geophysical prospecting

Abstract

Geophysics as its name indicates it has to do with Physics of the Earth. Geophysical prospecting methods involves exploration of interior of the Earth or the subsurface of the Earth. There are various Geophysical prospecting methods like Gravity prospecting, Magnetic prospecting, seismic prospecting, Electrical and Electromagnetic prospecting methods. Data obtained through these Geophysical prospecting methods are only indirectly related to the physical properties of the Earth, so an inverse problem must be solved to obtain estimates of the physical properties within the Earth. As the field data acquired is more non-linear it is necessary to invert the data using smart tools. Soft computing methods are more prominent in handling such data and researchers found it more successful in their applications (Srinivas et al., 2012, Stanley Raj et al., 2014, 2016). Soft computing based geophysical inversion differs from conventional computing in fixing uncertainty problems. Several Soft computing methods viz., Neural Networks, Fuzzy Logic, Neuro Fuzzy, Wavelet analysis, Cellular Automata, Nature inspired artificial optimization algorithms are applied to inverting most of the Geophysical methods. A complete overview of the soft computing methods applied in the field of Geophysics is presented in this paper. Research works based on these methods are studied, analyzed and discussed.