Wednesday 12 December 2018, 13.00 – 16.00, The Technical University of Denmark, Building 303A, room 49\n

\n**Principal supervisor**:\nAssociate Professor John Bagterp Jørgensen, DTU Compute.

\n**Co-Supervisors**:\nAssociate Professor Niels Kjølstad Poulsen, DTU Compute\nand Freelance computational scientist Andrea Capolei.\n

**Examiners**:\nAssociate Professor Mirza Karamehmedovic, DTU Compute.

\nAssociate Professor John Hedengren, Brigham Young University, United States of America.

\nAssociate Professor Jiri Mikyška, Czech Technical University in Prague, Czech Republic.\n

Moderator:\nAssistant Professor Dimitri Boiroux, DTU Compute\n

\n**Summary:**\n

\nOil remains the world’s leading fuel, and it is expected to account for a significant part of the\nworld’s energy consumption for several decades. However, current recovery techniques do\nnot recover all of the oil that is present in the oil reservoirs.\nFurthermore, the production of oil\nfrom a given reservoir may be uneconomical depending on the oil price\nwhich is very volatile.\n

\nIn this PhD project, we consider nonlinear model predictive control (NMPC) for improving the\neconomics of oil recovery processes. The objective of NMPC for oil reservoirs management is\nto compute a field-\nwide\nclosed-loop feedback control strategy which optimizes a long-term\nfinancial measure of the recovery process, e.g. the total amount of recovered oil or the net\npresent value over the life-time of the reservoir.\nWhenever new measurements become available, the NMPC algorithm uses 1) state\nestimation to estimate the state of the reservoir (as well as parameters in the model) and 2)\ndynamic optimization to compute a new updated field-wide production strategy. Reservoir flow\nmodels are used in both the state estimation and the dynamic optimization. Accurate reservoir\nflow models are therefore key to the effectiveness of the NMPC algorithm.\n

\nIn this work, we present thermodynamically rigorous models of thermal (varying temperature)\nand isothermal (constant temperature) compositional reservoir flow processes. Models of such\nprocesses are based on two main principles: 1) conservation of mass and energy, and 2)\nphase equilibrium. The conservation of energy is related to the first law of thermodynamics,\nand phase equilibrium is related to the second law of thermodynamics. The phase equilibrium\nproblems that are relevant to the thermal and the isothermal models are the UV flash and the\nVT flash, respectively. We formulate these phase equilibrium problems as equality cons\ntrained\noptimization problems and the phase equilibrium conditions as the first order optimality\nconditions. Furthermore, we demonstrate that the thermal and the isothermal models are in a\nsemi-explicit differential-algebraic form, and we formulate algorithms for state estimation,\ndynamic optimization, and NMPC of systems in this form.\nThese algorithms are relevant to other phase equilibrium processes as well because it is\nnatural to model such processes using differential-algebraic equations in the same semi-explicit form.\n

A copy of the PhD thesis is available for reading at the department\n

\nAll are welcome

X-ALT-DESC;FMTTYPE=text/html:Wednesday 12 December 2018, 13.00 – 16.00, The Technical University of Denmark, Building 303A, room 49\n

\n**Principal supervisor**:\nAssociate Professor John Bagterp Jørgensen, DTU Compute.

\n**Co-Supervisors**:\nAssociate Professor Niels Kjølstad Poulsen, DTU Compute\nand Freelance computational scientist Andrea Capolei.\n

**Examiners**:\nAssociate Professor Mirza Karamehmedovic, DTU Compute.

\nAssociate Professor John Hedengren, Brigham Young University, United States of America.

\nAssociate Professor Jiri Mikyška, Czech Technical University in Prague, Czech Republic.\n

Moderator:\nAssistant Professor Dimitri Boiroux, DTU Compute\n

\n**Summary:**\n

\nOil remains the world’s leading fuel, and it is expected to account for a significant part of the\nworld’s energy consumption for several decades. However, current recovery techniques do\nnot recover all of the oil that is present in the oil reservoirs.\nFurthermore, the production of oil\nfrom a given reservoir may be uneconomical depending on the oil price\nwhich is very volatile.\n

\nIn this PhD project, we consider nonlinear model predictive control (NMPC) for improving the\neconomics of oil recovery processes. The objective of NMPC for oil reservoirs management is\nto compute a field-\nwide\nclosed-loop feedback control strategy which optimizes a long-term\nfinancial measure of the recovery process, e.g. the total amount of recovered oil or the net\npresent value over the life-time of the reservoir.\nWhenever new measurements become available, the NMPC algorithm uses 1) state\nestimation to estimate the state of the reservoir (as well as parameters in the model) and 2)\ndynamic optimization to compute a new updated field-wide production strategy. Reservoir flow\nmodels are used in both the state estimation and the dynamic optimization. Accurate reservoir\nflow models are therefore key to the effectiveness of the NMPC algorithm.\n

\nIn this work, we present thermodynamically rigorous models of thermal (varying temperature)\nand isothermal (constant temperature) compositional reservoir flow processes. Models of such\nprocesses are based on two main principles: 1) conservation of mass and energy, and 2)\nphase equilibrium. The conservation of energy is related to the first law of thermodynamics,\nand phase equilibrium is related to the second law of thermodynamics. The phase equilibrium\nproblems that are relevant to the thermal and the isothermal models are the UV flash and the\nVT flash, respectively. We formulate these phase equilibrium problems as equality cons\ntrained\noptimization problems and the phase equilibrium conditions as the first order optimality\nconditions. Furthermore, we demonstrate that the thermal and the isothermal models are in a\nsemi-explicit differential-algebraic form, and we formulate algorithms for state estimation,\ndynamic optimization, and NMPC of systems in this form.\nThese algorithms are relevant to other phase equilibrium processes as well because it is\nnatural to model such processes using differential-algebraic equations in the same semi-explicit form.\n

A copy of the PhD thesis is available for reading at the department\n

\nAll are welcome

URL:https://www.compute.dtu.dk/english/kalender/2018/12/phd-defense-by-tobias-kasper-skovborg-ritschel DTSTAMP:20221129T134800Z UID:{04148F08-8FE3-4F7C-860C-3EDF17B28A42}-20181212T120000Z-20181212T120000Z LOCATION: DTU, Building 303A, room 49 END:VEVENT END:VCALENDAR