Automated evaluation of refinery and petrochemical feedstocks using a combination of historical market prices, machine learning, and algebraic planning model information
US11663546B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 22, 2020 |
| Grant date | May 30, 2023 |
| Priority date | — |
| Expiry date | Apr 22, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q50/06
- WIPO fieldIT methods for management
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.