DocumentCode :
508283
Title :
Application of Genetic Algorithm in Inverse Problem of Welltesting Interpretation of Triple Media Reservoirs
Author :
Zi-sheng, Wang ; Jun, Yao
Author_Institution :
China Univ. of Pet., Dongying, China
Volume :
4
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
589
Lastpage :
593
Abstract :
It is obviously impossible to match test data of triple media reservoirs by hand because of too many parameters to be interpretated. The different parameters of well-testing interpretation have bad relativity and the well-testing interpretation is a non-linear inversion problem with multi-parameters. Genetic algorithms which are developed recently have advantage of global convergence. It is auto-adapted and non-linear optimum algorithm without gradient information which is very fit for the well-testing interpretation of triple media reservoirs. It is very successful for the auto-match of well-testing interpretation of triple media reservoirs by use of genetic algorithms which improves the matching speed and precision between theoretical pressure and the observed pressure.
Keywords :
convergence; genetic algorithms; hydrocarbon reservoirs; testing; auto-adapted optimum algorithm; genetic algorithm; global convergence; inverse problem; nonlinear inversion problem; nonlinear optimum algorithm; triple media reservoirs; well-testing interpretation; Biological cells; Computer applications; Convergence; Genetic algorithms; Inverse problems; Permeability; Petroleum; Random media; Reservoirs; Testing; Genetic Algorithm; Inverser Problem; Triple Media Reservoirs; Well-testing Interpretation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
Type :
conf
DOI :
10.1109/ICNC.2009.325
Filename :
5366454
Link To Document :
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