公开(公告)号：US20220028495A1

公开(公告)日：2022-01-27

申请号：US17443648

申请日：2021-07-27

Applicant: PHILLIPS 66 COMPANY

Inventor： Ayuba Fasasi ,  Jinfeng Lai ,  David A. Henning

IPC: G16B40/00 ,  G01N33/28 ,  G01N21/359 ,  G01N24/08 ,  G01N21/3577 ,  C10G75/00

Abstract: A process for producing liquid transportation fuels in a petroleum refinery while avoiding the usage of crude oil feed stock that characterized by a fouling thermal resistance having the potential to foul refinery processes and equipment. Spectral data selected from NIR, NMR or both is obtained and converted to wavelets coefficients data. A genetic algorithm (or support vector machines) is then trained to recognize subtle features in the wavelet coefficients data to allow classification of crude samples into one of two groups based on fouling potential. Rapid classification of a potential crude oil feed stock according to its fouling potential prevents the utilization of feed stocks characterized by increased fouling potential in a petroleum refinery to produce liquid transportation fuels.

公开(公告)号：US12116537B2

公开(公告)日：2024-10-15

申请号：US18065057

申请日：2022-12-13

Applicant: PHILLIPS 66 COMPANY

Inventor： Ayuba Fasasi ,  Alec C. Durrell ,  Jinfeng Lai ,  David A. Henning ,  Franklin Uba

IPC: C10G75/00 ,  G01R33/46 ,  G06N3/126

CPC classification number: C10G75/00 ,  G01R33/4625 ,  G06N3/126 ,  C10G2300/1059 ,  C10G2300/30

Abstract: A process for producing liquid transportation fuels in a petroleum refinery while preventing or minimizing corrosion of refinery process equipment. Spectral data selected from mid-infrared spectrometry, nuclear magnetic resonance spectrometry, or both is obtained and converted to wavelets coefficients data. A pattern recognition genetic algorithm is then trained to recognize subtle features in the wavelet coefficients data to allow classification of crude samples into one of two groups based on corrosion propensity. One of several actions is taken depending upon the measured corrosion propensity of the potential feed stock in order to prevent or minimize corrosion while producing one or more liquid hydrocarbon fuels.

公开(公告)号：US11929153B2

公开(公告)日：2024-03-12

申请号：US18065140

申请日：2022-12-13

Applicant: PHILLIPS 66 COMPANY

Inventor： Ayuba Fasasi ,  Alec C. Durrell ,  Jinfeng Lai ,  David A. Henning ,  Franklin Uba

IPC: G16B40/00 ,  C10G75/00 ,  G01N21/3577 ,  G01N21/359 ,  G01N24/08 ,  G01N33/28

CPC classification number: G16B40/00 ,  C10G75/00 ,  G01N21/3577 ,  G01N21/359 ,  G01N24/081 ,  G01N24/085 ,  G01N33/2823 ,  C10G2300/4075

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.

公开(公告)号：US20230115815A1

公开(公告)日：2023-04-13

申请号：US18065140

申请日：2022-12-13

Applicant: PHILLIPS 66 COMPANY

Inventor： Ayuba Fasasi ,  Alec C. Durrell ,  Jinfeng Lai ,  David A. Henning ,  Franklin Uba

IPC: G16B40/00 ,  G01N33/28 ,  G01N21/359 ,  G01N21/3577 ,  G01N24/08 ,  C10G75/00

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.

公开(公告)号：US20230113986A1

公开(公告)日：2023-04-13

申请号：US18065057

申请日：2022-12-13

Applicant: PHILLIPS 66 COMPANY

Inventor： Ayuba Fasasi ,  Alec C. Durrell ,  Jinfeng Lai ,  David A. Henning ,  Franklin Uba

IPC: C10G75/00 ,  G06N3/126 ,  G01R33/46

Abstract: A process for producing liquid transportation fuels in a petroleum refinery while preventing or minimizing corrosion of refinery process equipment. Spectral data selected from mid-infrared spectrometry, nuclear magnetic resonance spectrometry, or both is obtained and converted to wavelets coefficients data. A pattern recognition genetic algorithm is then trained to recognize subtle features in the wavelet coefficients data to allow classification of crude samples into one of two groups based on corrosion propensity. One of several actions is taken depending upon the measured corrosion propensity of the potential feed stock in order to prevent or minimize corrosion while producing one or more liquid hydrocarbon fuels.

公开(公告)号：US11557376B2

公开(公告)日：2023-01-17

申请号：US17443648

申请日：2021-07-27

Applicant: PHILLIPS 66 COMPANY

Inventor： Ayuba Fasasi ,  Jinfeng Lai ,  David A. Henning ,  Franklin Uba

IPC: G16B40/00 ,  C10G75/00 ,  G01N21/359 ,  G01N24/08 ,  G01N33/28 ,  G01N21/3577

Abstract: A process for producing liquid transportation fuels in a petroleum refinery while avoiding the usage of crude oil feed stock that characterized by a fouling thermal resistance having the potential to foul refinery processes and equipment. Spectral data selected from NIR, NMR or both is obtained and converted to wavelets coefficients data. A genetic algorithm (or support vector machines) is then trained to recognize subtle features in the wavelet coefficients data to allow classification of crude samples into one of two groups based on fouling potential. Rapid classification of a potential crude oil feed stock according to its fouling potential prevents the utilization of feed stocks characterized by increased fouling potential in a petroleum refinery to produce liquid transportation fuels.