How New Modeling Capabilities Enable Digital Transformation to Improve Refinery Performance

This paper will address refinery modeling problems that have presented difficult challenges to simulators, including properly characterizing assays, estimating properties, predicting behavior, and improving planning. This paper focuses on advances in modeling such as molecular modeling-based properties estimation that allow for quicker and more accurate refinery models. These models can evolve into digital twins of the refinery asset, leading to improved safety, operability, and revenue. Examples of successful applications outlining the technical challenge and how it was overcome will be shared along with the estimated economic impact that these improved models have delivered.