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Exploration of hydrocarbon resources is a highly complicated and expensiveprocess where various geological, geochemical and geophysical factors aredeveloped then combined together. It is highly significant how to design theseismic data acquisition survey and locate the exploratory wells sinceincorrect or imprecise locations lead to waste of time and money during theoperation. The objective of this study is to locate high-potential oil and gasfield in 1: 250,000 sheet of Ahwaz including 20 oil fields to reduce both timeand costs in exploration and production processes. In this regard, 17 maps weredeveloped using GIS functions for factors including: minimum and maximum oftotal organic carbon (TOC), yield potential for hydrocarbons production (PP),Tmax peak, production index (PI), oxygen index (OI), hydrogen index (HI) aswell as presence or proximity to high residual Bouguer gravity anomalies,proximity to anticline axis and faults, topography and curvature maps obtainedfrom Asmari Formation subsurface contours. To model and to integrate maps, thisstudy employed artificial neural network and adaptive neuro-fuzzy inferencesystem (ANFIS) methods. The results obtained from model validation demonstratedthat the 17x10x5 neural network with R=0.8948, RMS=0.0267, and kappa=0.9079 canbe trained better than other models such as ANFIS and predicts the potentialareas more accurately. However, this method failed to predict some oil fieldsand wrongly predict some areas as potential zones.

Spatial Modeling of Oil Exploration Areas Using Neural Networks and ANFIS in GIS