We investigate the application of a global optimization algorithm called the Tunneling Method to the problem of history-matching of petroleum reservoirs.

Results are presented for two test cases. The first is a small synthetic case in which the global minimum is known. The second is a real field example. In both cases, a series of minima was found. The computational cost of each tunneling phase is found to be comparable with the cost of each local minimization.

It is concluded that the Tunneling Method may have a practical application in history-matching as an alternative to immediate reformulation of the problem if the first minimum found does not represent an acceptable match.

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