Chemical Product and Process Modeling
Ed. by Sotudeh-Gharebagh, Rhamat / Mostoufi, Navid / Chaouki, Jamal
4 Issues per year
CiteScore 2017: 0.96
SCImago Journal Rank (SJR) 2017: 0.295
Source Normalized Impact per Paper (SNIP) 2017: 0.347
Pseudo-Dynamic Modeling to Evaluate a Remote Gas-to-Liquids Process
A project team was given the task of evaluating various technology options for design of a small-scale gas-to-liquids (GTL) process operated remotely at or near an individual gas source. For this study, small-scale plants were considered those producing between 100 and 500 barrels per day of liquid fuels. In addition, being remote enforced limitations on utility sources available to the plant site such as water and grid power. A secondary goal was development of a dynamic model of the plant to use in operator training. To accomplish these objectives, the authors investigated the suitability of a process-simulation application. The conceptual design of the GTL unit included many different possibilities, such as front-end design, back-end design, heat integration, and recycling of materials. Complications associated with plant start-up and shutdown, utilities, process reliability, and economics were included in the decision-making process. The authors present selective results from a steady-state model and sensitivity studies. Considerations for the development of the dynamic model included both a fully rigorous dynamic model and a pseudo-dynamic steady-state-based model; results of the latter model are provided. The study concluded that an industrial steady-state simulation tool provided sufficient flexibility to complete the material and energy-balance calculations, sensitivity analyses, and pseudo-dynamic modeling. This study yielded significant insights into the importance of model assumptions and their impact on the overall process viability. The pseudo-dynamic model also provided insight for improving the process control design. During the work completed the authors determined that the object-oriented structure adopted for the model enabled an efficient, rapid model development.