Title :
Lithofacies recognition hybrid bench
Author :
Ferraz, Inhauma Neves ; Garcia, Ana Cristina Bicharra
Author_Institution :
Univ. Fed. Fluminense, Brazil
Abstract :
Well offshore petroleum exploration is a risky, but very profitable task. Determining the rock formation of each layer of a given reservoir diminishes the risks of expending a great deal of money drilling dry wells. Since collecting offshore rock samples is difficult and expensive, geologists must decide upon drilling based on indirect measures called well log. Traditional statistical methods have been used to assist this task. Neural networks have also been successfully used. As an alternative fuzzy logic based systems have an extra appeal of intuitive comprehension of some uncertainties. This paper presents a hybrid tool that combines neural networks, fuzzy logic and neuro-fuzzy logic to improve human intuition when analyzing the potential of oil fields.
Keywords :
fuzzy logic; fuzzy neural nets; oil technology; petroleum industry; petrology; uncertainty handling; well logging; fuzzy logic based systems; intuitive uncertainty comprehension; lithofacies recognition hybrid bench; neural networks; neuro-fuzzy logic; well log; well offshore petroleum exploration; Drilling; Fuzzy logic; Fuzzy systems; Geology; Hydrocarbon reservoirs; Neural networks; Permeability; Petroleum; Production; Statistical analysis;
Conference_Titel :
Hybrid Intelligent Systems, 2005. HIS '05. Fifth International Conference on
Print_ISBN :
0-7695-2457-5
DOI :
10.1109/ICHIS.2005.70