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dc.contributor.advisorAamo, Ole Morten
dc.contributor.advisorHauge, Espen
dc.contributor.authorHaukanes, Simon
dc.date.created2015-06-09
dc.date.issued2015
dc.identifierntnudaim:12685
dc.identifier.urihttp://hdl.handle.net/11250/2352439
dc.description.abstractThere is a continuous search for new reserves in the oil and gas industry. Most of the larger fields that are accessible with conventional drilling technology have been drilled. The remaining fields typically contain less oil and gas, are harder to drill and located at significant depths. The costs of drilling wells have increased while the oil price has dropped. It is therefore a strong demand for drilling technologies able to drill where conventional drilling cannot be used, while still being cost and time efficient. In addition, after the blowout in the Gulf of Mexico, the industry has been challenged to develop new solutions improving safety. As a response to increased demands, solutions with a higher degree of automation, improving pressure control have been developed, and are referred to as Managed Pressure Drilling. A sub technology in this category is Dual Gradient Drilling. Statoil ASA uses this technology at one of their offshore installations, and after gaining operational experience, field data has become available. This field data gives the opportunity to validate mathematical models and estimate unknown parameters. Once a verified model has been established, it can be used to experiment with controller design and tuning. This will ease controller tuning offshore, which in turn saves valuable rig time. In this thesis, a fit-for-purpose mathematical model for a Dual Gradient Drilling system with partially filled riser is derived. Using the available field data, unknown parameters related to the mud circulation part of the system is identified. The model is also augmented to account for the presence of the U-tubing effect. A steady state friction model was found sufficient to describe the frictional losses, and a subsea pump model was obtained by optimization. The presence of U-tubing was found when ramping down the booster pump. Due to the lack of measurements and in-depth system knowledge, a complicated model was discarded in favor of adding simplified dynamics to the booster pump. The simple model successfully compensated for U-tubing. Through simulation the derived model, with identified parameters, was found to be able to reproduce the field data in a satisfactory manner with only small deviations during U-tubing.
dc.languageeng
dc.publisherNTNU
dc.subjectKybernetikk og robotikk
dc.titleState and Parameter Identification Applied to Dual Gradient Drilling with Water Based Mud
dc.typeMaster thesis
dc.source.pagenumber92


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