The exploration of hydrocarbon resources as a process is very complex and costly. In this process multiple factors of geology, geochemistry and geophysics are considered and combined together. Designing the best route to take seismic data and determine the best location for drilling exploration wells is extremely important. Since improper or careless determine the selection of location is time consuming and expensive during the operation. The aim of this study was to identify possible areas for oil and gas in the map of 1: 250,000 Ahvaz with 20 oil fields using adaptive inference systems neuro - fuzzy (ANFIS) and geographic information systems (GIS). For this purpose, 17 maps of factors including: the lowest and highest value (total organic carbon (TOC), potential for the production of hydrocarbons (PP), peak Tmax, the production index (PI), oxygen index (OI), hydrogen index (HI)) and the proximity to areas of high bouguer gravity anomaly, anticline axis and faults, map the topography and curvature of the yield curve Asmari subsurface were created by GIS functions. For combined factor map, the adaptive inference systems neuro - fuzzy (ANFIS) that is data-driven methods were used. The results of test data showed that the model with a R = 0.839 ,RMSE=0.0339 and the Kappa=0.859 was able to accurately predict the oil fields, but fields such as Shaver and Sepehr have not been identified and Also some areas were mistakenly classified oil fields.