Abstarct: Shale gases are the types of unconventional reservoirs which are distributed vastly around the world. Due to the increasing price of hydrocarbon and decreasing trend of exploration of conventional reservoirs in most countries, the tendency to the production of these types of reservoirs has increased. Distribution of these reservoirs makes it economically essential to investigate the highly potential areas of production. In this thesis, it has been tried to estimate the total organic carbon (TOC) from the conventional logs with the help of intelligent methods. Two methods have been used for TOC estimation in six wells of Kockatea shale gas in Perth basin of Western Australia. 1- Multi laxyer percptron neural network 2- Wavelet neural network (combination of MLP and wavelet theory) Finally the areas of higher potentiality have been determined in these six wells by using the TOC output of estimator model and also the investigation of cut-off baxse methods in shale gases for the determination of high production potential areas.