The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 12, 2024

Filed:

Dec. 13, 2022
Applicant:

Phillips 66 Company, Houston, TX (US);

Inventors:

Ayuba Fasasi, Bartlesville, OK (US);

Alec C. Durrell, Bartlesville, OK (US);

Jinfeng Lai, Bartlesville, OK (US);

David A. Henning, Bartlesville, OK (US);

Franklin Uba, Bartlesville, OK (US);

Assignee:

Phillips 66 Company, Houston, TX (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16B 40/00 (2019.01); C10G 75/00 (2006.01); G01N 21/3577 (2014.01); G01N 21/359 (2014.01); G01N 24/08 (2006.01); G01N 33/28 (2006.01);
U.S. Cl.
CPC ...
G16B 40/00 (2019.02); C10G 75/00 (2013.01); G01N 21/3577 (2013.01); G01N 21/359 (2013.01); G01N 24/081 (2013.01); G01N 24/085 (2013.01); G01N 33/2823 (2013.01); C10G 2300/4075 (2013.01);
Abstract

A process for converting a first hydrocarbon feed stream to one or more liquid transportation fuels in a petroleum refinery where the feed stream is analyzed by at least one analytical method to produce data that is transformed to wavelet coefficients data. A pattern recognition algorithm is trained to recognize subtle features in the wavelet coefficients data that are associated with an attribute of the feed stream. The trained pattern recognition algorithm then rapidly classifies potential hydrocarbon feed streams as a member of either a first group or a second group where the second group comprises hydrocarbon feed streams where the attribute or chemical characteristic at or above a predetermined threshold value. This classification allows rapid decisions to be made regarding utilization of the feedstock in the refinery that may include altering at least one variable in the operation of the refinery.


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