About the Webinar
Fuel blending is a vital process in the downstream refining industry, as 80-85% of end-user refinery products are made by blending processes in offsite operations. Refineries lose 25 to 40 Million dollars annually due to inefficient and non-optimized blend recipes and poor blend quality control.
Refineries employ planning and real-time control systems to improve the marginality of the blending process. These systems are supposed to keep the blend qualities on spec while minimizing the quality giveaways and utilizing the available components to produce the desired quantity of the end product at the lowest cost. Both planning and control systems rely on the blend models.
These models predict the blend's properties based on the blended components' properties and their ratios in the blend. Two methods are adopted to model the blend.
The first predominant method uses the first principles of mathematical equations to model the blending process. This method requires initial customization of model parameters and continuously updating biases to correct the quality predictions online or offline by an experienced blend control engineer and must use historical data. Invariably, if not exercised diligently, this method results in a loss of tangible benefits for the refinery and blend quality error control.
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