Ex-situ Observation and Characterization of Mild Hydrotreated Liquid Products

• Author / Creator

  Palys, Daniel

• On-line analytical tools are needed to optimize the upgrading process. This technology could reduce environmental impacts, reduce costs, and enhance quality control of heavy oil feeds. Ultraviolet and visible spectroscopy, a well established ex-situ technique, is one example that could potentially be developed. The current challenge of this technology is heavy oil chemical complexity and its dynamic compositional transformations in upgrading.
  The current study focuses on enhancing knowledge of hydrotreating reactions of an intermediate Heavy Vacuum Gas Oil (HVGO) feed derived from Athabasca Bitumen. A batch microreactor with sulfided Ni-Mo/γ-Al2O3 catalyst pellets and <45μm solids were used. A range of reaction temperatures, 290-390°C, and times, 0.25-2h, were tested. To assess product quality, ex-situ observation and characterization of the hydrotreated liquid products were completed. Carbon, hydrogen, sulfur, nitrogen, density, boiling point distribution, and hydrogen nuclear magnetic resonance were completed to characterize the liquid products. A visible spectroscope was developed to observe and measure the hypsochromic color changes of the liquid products.
  Chemometric analysis with four modeling methods were completed to calibrate the visible adsorption spectra to the physicochemical properties obtained from characterization. Multiple linear regression and partial least squares regression were found as optimal modeling methods. Depending on the data set used, sulfur, nitrogen, initial boiling point to 300°C fraction, 400 to 500°C fraction, density, total aromatic hydrogen and its conversion, were found as the best properties calibrated. The 57, 81, and 77wt.% fractions off from the boiling point distribution curve using multiple linear regression were found to be the best models overall.

• Subjects / Keywords

  • Chemometrics
  • Visible Spectroscopy
  • HVGO
  • Hydrotreating

• Graduation date

  Fall 2019

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-06p6-dp56

• License

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