Gradient-based history matching with a global optimization method

We investigate the application of a global optimization algorithm called th e tunneling method to the problem of history matching of petroleum reservoi rs. Results are presented for two test cases. The first is a small synthetic ca se 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 ea ch tunneling phase is found to be comparable with the cost of each local mi nimization. It is concluded that the tunneling method may have a practical application in history matching as an alternative to immediate reformulation of the pro blem if the first minimum found does not represent an acceptable match.