Geothermal model calibration using a global minimization algorithm based on finding saddle points and minima of the objective function

Manuel Plasencia*, Andreas Pedersen, Andri Arnaldsson, Jean Claude Berthet, Hannes Jónsson

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)

Abstract

The objective function used when determining parameters in models for multiphase flow in porous media can have multiple local minima. The challenge is then to find the global minimum and also to determine the uniqueness of the optimized parameter values. A method for mapping out local minima to search for the global minimum by traversing regions of first order saddle points on the objective function surface is presented. This approach has been implemented with the iTOUGH2 software for estimation of models parameters. The methods applicability is illustrated here with two examples: a test problem mimicking a steady-state Darcy experiment and a simplified model of the Laugarnes geothermal area in Reykjavík, Iceland. A brief comparison with other global optimization techniques, in particular simulated annealing, differential evolution and harmony search algorithms is presented.

Original languageEnglish
Pages (from-to)110-117
Number of pages8
JournalComputers and Geosciences
Volume65
DOIs
Publication statusPublished - Apr 2014

Bibliographical note

Funding Information:
This work was supported by a Grant from GEORG (Geothermal Research Group) and the Icelandic Research Fund (RANNIS). We would like to thank Stefan Finsterle for useful discussions as well as providing us access to the latest iTOUGH2 code.

Other keywords

  • Global optimization
  • Inverse modeling
  • Reservoir modeling

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