Analyzers have been crucial parts of the industry, providing accurate properties of the products and confirming product’s conformity with specification and regulation. In the oil & gas industry, one of the best practices of checking the final product properties is to use an analyzer on-line during the in-line blending process in real-time and within the laboratory.
The advent of microcomputer revolution made it possible to economically code large scientific programs in personal computers, such as linear program refinery simulator and embedding AI into well-known mathematical algorithms to predict properties from the spectral fingerprints. The decision on what to use to determine predicted properties depends on cost.
Use of artificial intelligence (AI) has revolutionized this expensive and time-consuming step, bringing it close to a “plug-and-play” system. This presentation will compare two approaches, classical chemometrics and AI, highlighting the superiority and practicality of using AI.
Scheduled Speaker:
Daniel BC Son, Project Engineer - Refinery Automation Institute, Blending Division
Daniel BC Son holds a degree in Chemical Engineering from the New Jersey Institute of Technology and currently serves as a Project Engineer at Refinery Automation Institute.
Daniel has experience in several gasoline and bunker blending projects, including project feasibility studies, giveaway analysis, in-line blender modernization projects, and analyzer modernization projects.
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