State and parameter identification applied to dual gradient drilling with oil based mud
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Dual gradient drilling (DGD) is a modern technology that allows for drilling wells for oiland gas in a more precise and efficient manner. Many of the future oil and gas prospectsare highly complex and challenging with narrow geo-pressure margins and little room forhuman errors. Such projects are simply only feasible if they are founded on robust andefficient automated drilling solutions that allow for accurate pressure control. This studyfocuses on investigation of a real DGD system in the Gulf of Mexico through modelingand application of field data in order to estimate unknown parameters.First an introduction to the basics of drilling is given, explaining the advantages of thedual gradient drilling technology in terms of efficiency as well as safety. Then a hydraulicmodel for the complete system is developed. The available field measurements delimit asubsystem of the complete system where all parameters are identifiable. This shifts thefocus of this thesis solely to the dynamics of the mud return line (MRL), which is the mostvital section of the DGD system to know prior to control design.Following the development of the model for the MRL dynamics, field data are appliedto estimate the unknown parameters. Obvious discrepancies between observed field dataand the outputs of the identified model expressions encourage slight modifications of themodel structures until the observed outcomes are replicated by the model expressions to asatisfactory degree of accuracy. Finally, the dynamics of the identified system are simulated.The produced outputs are compared to field data, and the consistency between thesimulation results and the field measurements works as a natural measure of the validityof the identified model.