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dc.contributor.advisorFoss, Bjarne Antonnb_NO
dc.contributor.advisorGrimstad, Bjarnenb_NO
dc.contributor.authorAusen, Håvardnb_NO
dc.date.accessioned2014-12-19T14:05:45Z
dc.date.available2014-12-19T14:05:45Z
dc.date.created2012-11-08nb_NO
dc.date.issued2012nb_NO
dc.identifier565928nb_NO
dc.identifierntnudaim:7059nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/260617
dc.description.abstractTo aid in faster and better decision making it is interesting to couple advanced simulators with optimization tools.Most simulators however does not offer gradients, therefore derivative-free methods must be used. In this thesis optimization of and oil and gas field with free routing is considered. By embedding the structural information in the optimization problem and approximating the simulators by polynomials a MINLP problem is formed which can be solved by gradient based solvers. This approach requires that the polynomial models are updated frequently to fit the simulators. Each update requires several simulations and creates a trade-off between robustness and computation time. Different updating strategies for the models are considered in this thesis. By solving a separate optimization problem to update the models the MINLP problem can be formulated as a convex problem which is solved in a branch and bound framework and with an interior-point. Two approaches to updating the models in respect to the branch and bound method are explored, and it is found to be more robust to update the models for each node of the branch and bound tree, ensuring a local fit before branching.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for teknisk kybernetikknb_NO
dc.subjectntnudaim:7059no_NO
dc.subjectMTTK teknisk kybernetikkno_NO
dc.titleA Study in MINLP-class Optimization Problems for Simulated Petroleum Productionnb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber84nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for teknisk kybernetikknb_NO


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