Phillips 66 Company

Exxonmobil Chemical Patents Inc.

David Aaron Henning

Franklin Uba

Ayuba Fasasi

Jinfeng Lai

Patrick Brant

Peijun Jiang

Charles Lewis Sims

David Raymond Johnsrud

Alec C Durrell

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.

Rapid measurement of hydrocarbon corrosion propensity

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.

Chemometric characterization of refinery hydrocarbon streams

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.

Rapid assessment of crude oil fouling propensity to prevent refinery fouling

Disclosed herein is an in-reactor produced multi-component copolymer comprises a semi-crystalline component having a crystallinity of 20% or more, and an amorphous component having a crystallinity of 5% or less. The copolymer comprises at least 80 wt % of units derived from propylene and from about 1 to about 20 wt % of units derived from at least one Cto Calpha-olefin. The copolymer has a viscosity at 190&#xb0; C. of at least 530 mPa sec and a heat of fusion between about 10 and about 70 J/g. An adhesive containing the copolymer exhibits a good balance of adhesive properties and mechanical strength.

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Bartlesville, OK, United States of America

David Aaron Henning