Enhancing the Efficiency of Refining Processes: A Desktop Solution for Predicting FCC Yield Profiles

Abstract The current state of FCC technology has the potential to dictate the overall profitability of any complex oil refinery worldwide, where the catalyst plays a central role in maximizing fuel and olefin yields. Innovations in FCC catalysis have led to higher conversion rates, improved selectivity, and better tolerance to contaminants. Consequently, every FCC catalyst changeover presents an opportunity to enhance the refinery’s profit margin. However, this potential increment in margin necessitates thorough testing and selection of candidate optimum catalysts which is often a time-consuming process. While various computational models based on first principles, databases, linear programming, or artificial intelligence exist to expedite this process, they typically serve as intermediaries between laboratory experiments and commercial yield predictions. To streamline this process, the R&D team at Bharat Petroleum Corporation Limited (BPCL) has developed a proprietary Yield Prediction (Y-P) model. This model is designed to eliminate the need for experimental catalyst testing by estimating potential yield, selectivity, and conversion based on FCC feed and catalyst characteristics. The Y-P model employs a mathematical kinetic model using the tenlump scheme, integrating feed and catalyst properties into the prediction algorithm. By leveraging multivariate regression, lumped reaction mechanisms, and artificial neural networks, the model utilizes feedstock properties such as con-carbon, density, distillation, sulfur/nitrogen content, and catalyst properties like surface area, unit cell size, and acidity to predict commercial plant yields. The trial results of the Y-P model have shown strong alignment with conventional in-house catalyst evaluation methods, demonstrating its reliability and accuracy. This model not only facilitates the selection of FCC catalysts but also enables their reformulation to meet changing market demands. By bringing catalyst selection to the operator’s fingertips, the Y-P model significantly enhances the efficiency and profitability of refinery operations.