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A New Hybrid Optimization Algorithm for the Estimation of Archie Parameters

In: Optimization Methods, Theory and Applications

Author

Listed:
  • Jianjun Liu

    (China University of Petroleum, College of Science)

  • Honglei Xu

    (Curtin University, Department of Mathematics and Statistics)

  • Guoning Wu

    (China University of Petroleum, College of Science)

  • Kok Lay Teo

    (Curtin University, School of Mathematics and Statistics)

Abstract

Archie formula, which contains three fundamental parameters (a, m, n), is the basic equation to compute the water saturation in a clean or shaly formation. These parameters are known as Archie parameters. To identify accurately the water saturation for a given reservoir condition, it depends critically on the accurate estimates of the values of Archie parameters (a, m, n). These parameters are interdependent and hence it is difficult to identify them accurately. So we present a new hybrid global optimization technique, where a gradient-based method with BFGS update is combined with an intelligent algorithm called Artificial Bee Colony. This new hybrid global optimization technique has both the fast convergence of gradient descent algorithm and the global convergence of swarm algorithm. It is used to identify Archie parameters in carbonate reservoirs. The results obtained are highly satisfactory. To further test the effectiveness of the new hybrid global optimization method, it is applied to ten non-convex benchmark problems. The outcomes are encouraging.

Suggested Citation

  • Jianjun Liu & Honglei Xu & Guoning Wu & Kok Lay Teo, 2015. "A New Hybrid Optimization Algorithm for the Estimation of Archie Parameters," Springer Books, in: Honglei Xu & Song Wang & Soon-Yi Wu (ed.), Optimization Methods, Theory and Applications, edition 127, chapter 0, pages 137-154, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-47044-2_7
    DOI: 10.1007/978-3-662-47044-2_7
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