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.
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dos Santos Amorim, E.P., Xavier, C.R., Campos, R.S., dos Santos, R.W. (2012). Comparison between Genetic Algorithms and Differential Evolution for Solving the History Matching Problem. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2012. ICCSA 2012. Lecture Notes in Computer Science, vol 7333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31125-3_48
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DOI: https://doi.org/10.1007/978-3-642-31125-3_48
Publisher Name: Springer, Berlin, Heidelberg
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