Comparison between genetic algorithms and differential evolution for solving the history matching problem

Authors:
Elisa P. dos Santos Amorim;Carolina R. Xavier;Ricardo Silva Campos;Rodrigo W. dos Santos
Affiliations:
Dept. of Computer Science, University of Calgary, Canada;Departamento de Ciência da Computação, UFSJ, Brazil,COPPE, UFRJ, Brazil;Programa de Pós Graduação em Modelagem Computacional, UFJF, Juiz de Fora, MG, Brazil;Programa de Pós Graduação em Modelagem Computacional, UFJF, Juiz de Fora, MG, Brazil
Venue:
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part I
Year:
2012

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Abstract

This work presents a performance comparison between Differential Evolution (DE) and Genetic Algorithms (GA), for the automatic history matching problem of reservoir simulations. The history matching process is an inverse problem that searches a set of parameters that minimizes the difference between the model performance and the historical performance of the field. This model validation process is essential and gives credibility to the predictions of the reservoir model. Four case studies were analyzed each of them differing on the number of parameters to be estimated: 2, 4, 9 and 16. Several tests are performed and the preliminary results are presented and discussed.