PhD defence by Mads Valentin Bram on Grey-box Modeling and Validation of Deoiling Hydrocyclones


27.11.2020 kl. 13.00 - 16.00


Mads Valentin Bram, Department of Energy Technology, will defend the thesis "Grey-box Modeling and Validation of Deoiling Hydrocyclones"


Grey-box Modeling and Validation of Deoiling Hydrocyclones


Mads Valentin Bram


Associate Professor Zhenyu Yang


Associate Professor Simon Pedersen


Associate Professor Ben-Guang Rong, Dep. of Chemistry and Bioscience, Aalborg University (Chairman)
Professor John Bagterp Jørgensen, Technical University of Denmark
Associate Professor Christian Holden, Norwegian University of Science and Technology


The produced oil and gas from offshore installations are transported to onshore facilities for further processing, while the produced water (PW), which commonly is more than 90% of the produced mixture by volume, has to be cleaned before it is discharged to the surrounding sea. Danish regulations require the discharged oil-in-water (OiW) concentration to be less than 30ppm on a weekly average, and less than 222t total oil discharge annually. However, these restrictions are very likely to become stricter due to governmental trends toward zero harmful discharge. Current control solutions for produced water treatment (PWT) suffer from a set of problems associated with the produced water treatment processes
being interdependent, and sometimes contradictory. The challenges call for solutions based on plant-wide control, which benefits from accurate and reliable  control-oriented models of the processes, such as models of the deoiling hydrocyclones. The field of research of computational fluid dynamics and data-driven black-box hydrocyclone models are relatively mature and provide a good background for understanding the separation principles of a hydrocyclone. However, the model must be relatively simple for control design purposes. Additionally, the model will likely perform better in a broader range of operating conditions if it is derived from first principles. A grey-box model structure is proposed that uses hydrocyclone valves and existing measurements as input to predict various separation performance metrics, such as grade efficiency, also called mitigation probability, and separation efficiency. The model structure is composed of valve dynamics from electrical input to actual valve opening, virtual flow resistance (VFR) to estimate flow rates and pressures, and oil droplet trajectory (ODT) to classify oil droplets. Each main part of the model was experimentally validated on a modified PWT pilot plant, including OiW measurements obtained from real-time fluorescence-based monitors, and showed good accuracy and reliability. In this thesis, a versatile control-oriented grey-box model structure of a deoiling hydrocyclone with emphasis on practical implementation is defined, analyzed, and validated. An approach to obtain or identify all parameters of the model is proposed and validated. A proposed pin-cart model was formulated and identified to describe the dynamics of the valves located at the hydrocyclone outlets. The pin-cart model was validated using actual valve data, and was able to reasonably describe the longer perceived delay when changing valve direction. A VFR model was proposed and identified using measurements obtained from the PWT pilot plant. The VFR model was able to predict the flow rates and pressures of the hydrocyclone with good accuracy. The ODT model was validated using real-time fluorescence-based OiW monitors, while addressing the challenges associated with using the OiW monitors for validation. However, it is acknowledged that the proposed model structure can always benefit from further validation, such as by droplet size measurements. Additionally, the modular model structure allows future works to incorporate effects, such as droplet coalescence and breakup. The model is deemed valuable for control design and other observer-related pur-


THE DEFENCE will be IN ENGLISH - all are welcome.

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Department of Energy Technology - Campus Esbjerg

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