Aspen Technology, Inc.
Automated Evaluation of Refinery and Petrochemical Feedstocks Using a Combination of Historical Market Prices, Machine Learning, and Algebraic Planning Model Information

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Abstract:

Computer tool determines target feedstock for a refinery, process complex, or plant. The tool receives a dataset of market conditions and preprocesses the data based on properties of the plant. Using the preprocessed data and machine learning, the tool trains predictive models. Each predictive model calculates a breakeven value of a candidate feedstock for the given plant under an individual market condition. Different predictive models optimize for different market conditions. A trained predictive model is selected based on a current market condition. The tool applies the selected predictive model and determines whether a candidate feedstock is a target feedstock for the refinery under the current market condition.

Status:
Application
Type:

Utility

Filling date:

22 Apr 2020

Issue date:

28 Oct 2021