DocumentCode :
2757773
Title :
Quantitative Evaluation of Oil and Gas Resources: A Geological Analogy Model Based on Delphi Method
Author :
Liu, Gang ; Wang, Yanni ; Wang, Xianyong ; Pan, Yuandun
Author_Institution :
Fac. of Earth Resources, China Univ. of Geosci., Wuhan, China
Volume :
2
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
603
Lastpage :
607
Abstract :
One trend of oil and gas prediction and evaluation is computer-aided quantitative approach. Aiming at complicated factors and numerous parameters of oil and gas resources estimation, the method with combination of geological analogy model and probabilistic model and corresponding flowcharts were introduced. The quantitative estimation process was performed by using Delphi method and Monte Carlo calculation method to give a curve of inverse cumulative probability to support decision-making. Geological analogy method based on probabilistic model has better adaptability than the traditional analogy method. The final comprehensive probability curve of quantitative estimation of oil and gas resources can be obtained, which has a good practical significance.
Keywords :
Monte Carlo methods; decision making; decision support systems; environmental science computing; geology; hydrocarbon reservoirs; oils; probability; Delphi method; Monte Carlo calculation method; computer-aided quantitative approach; decision-making; flowcharts; gas resources estimation; geological analogy model; inverse cumulative probability curve; oil resources estimation; probabilistic model; quantitative estimation process; quantitative evaluation; Computer science education; Decision making; Earth; Feedback; Fuzzy systems; Geology; Laboratories; Monte Carlo methods; Petroleum; Probability; Delphi method; Monte Carlo calculation method; geological analogy model; oil and gas resources; quantitative evaluation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
Type :
conf
DOI :
10.1109/FSKD.2009.725
Filename :
5359524
Link To Document :
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