Optimal Design, Operation and Development of Oil Sands Upgrading Plants

  • Author / Creator
    Shahandeh, Hossein
  • Canada has the third largest oil reserves in the world where 97% of these reserves are located in the oil sands, Alberta province. The product resulted from the extraction of oil sands reserves is called bitumen which can be diluted and shipped to the market or it can be proceeded and upgraded into a value-added product. The upgrading facilities mainly improve the quality of bitumen by rejecting carbon from it or adding hydrogen to it using operating units such as thermocracking or hydrocracking, respectively. Moreover, the upgrading process can be carried out through full or partial upgrading technologies. Note that the partial upgrading technology has not been commercialized yet. There is no doubt that upgrading bitumen would bring more social and economic benefits to the province; however, decision making at different levels of upgrading processes is a challenging task.In this thesis, we attempt to address how to reach the optimal point of upgrading process at three different levels. The first level is the design problem in which the objective is selecting the most efficient units out of all possible options and finding the best arrangement among them for the full upgrading process. The second level is the operation problem, where there exists a hydrocracking-based full upgrading plant with determined operating units, and the goal is achieving the optimal operating conditions such as pressure and temperature. The third level is the development of upgrading plants in the future. In one study, the expansion planning of an existing thermocracking-based full upgrading plant is addressed. In a later study, the optimal planning of initial capacity and expansion of partial upgrading technologies is presented. It should be highlighted here that the objective functions of these works are economic terms such as net present value or profit, and the environmental impact is one of the constraints in our optimization problems. Furthermore, while the design and operation problems are modeled deterministically, different uncertainties are incorporated and stochastic models are considered for the development problems.The major novelties and contributions of this thesis are threefold. Firstly, Augmented Lagrangian decomposition method is implemented to solve the design problem. The final optimization model of the design problem is a large–scale non–convex mixed integer nonlinear programming problem which commercial solvers are not able to find the optimal solution directly. Secondly, a multistage stochastic programming model is proposed for the development problem of full upgrading plant. An uncertainty set is defined for the synthetic crude oil price and carbon tax, and linear decision rule approximation is applied for the robust optimization of the developed mixed integer linear programming problem. Thirdly, a multistage stochastic programming model is proposed for the development problem of partial upgrading technologies. The developed model cannot be handled with classical approaches (such as robust optimization or stochastic programming), and hence, two novel hybrid methods are introduced (to the best of our knowledge, one of them has not been studied in literature before). The hybrid methods are a combination of scenario–based and uncertainty set definitions for uncertainty.

  • Subjects / Keywords
  • Graduation date
    Fall 2018
  • Type of Item
  • Degree
    Doctor of Philosophy
  • DOI
  • License
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