Phillips 66 Company

Ayuba Fasasi

Franklin Uba

Paul Rady

Marisa Purificato

David Aaron Henning

Jinfeng Lai

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

In one embodiment, a pipeline interchange is described where a first product flows through a first pipeline and a second product flows through a second pipeline. A pipeline interchange is connected downstream to both the first pipeline and the second pipeline, wherein the pipeline interchange blends the first product flowing through the first pipeline with the second product flowing through the second pipeline. A third pipeline is connected downstream to the pipeline interchange, wherein the third pipeline flows a blended product created from the blending of the first product and the second product in the pipeline interchange. An automated analyzer can be situated downstream of the pipeline interchange capable of physical and/or chemically analyzing the blended product and generating blended data. A data analyzer is also positioned to interpret the blended data and communicate adjustments to the flow of both the first product and the second product to achieve desired physical and/or chemical characteristics in the blended product.

Pipeline interchange/transmix

In one embodiment, a pipeline interchange flows a product through an upstream pipeline. An automated analyzer is connected to the upstream pipeline to analyze different physical and/or chemically properties in the product and generate data from the product without extracting a sample from the upstream pipeline. An automatic splitter is placed downstream of the automated analyzer, capable of receiving and interpreting the data from the automated analyzer and directing the refined petroleum product into at least three different downstream pipelines, wherein at least one of the downstream pipelines is a transmix pipeline.

In one embodiment, a pipeline interchange is described where a first product flows through a first pipeline and a second product flows through a second pipeline. In this embodiment, a first product automated analyzer is situated near the first pipeline to physical and/or chemically analyze the first product and generate first product data. Additionally, in this embodiment, a second product automated analyzer is situated near the second pipeline to physical and/or chemically analyze the second product and generate second product data. A pipeline interchange is connected downstream to both the first pipeline and the second pipeline, wherein the pipeline interchange blends the first product flowing through the first pipeline with the second product flowing through the second pipeline. A third pipeline is connected downstream to the pipeline interchange, wherein the third pipeline flows a blended product created from the blending of the first product and the second product in the pipeline interchange. A data analyzer is also positioned to interpret the first product data and the second product data and communicate adjustments to the flow of both the first product and the second product to achieve desired physical and/or chemical characteristics in the blended product.

In one embodiment, a process is taught where the process begins by flowing a first product through a first pipeline and flowing a second product through a second pipeline. The process then produces a blended product by mixing both the first product and the second product within a pipeline interchange which is connected downstream to both the first pipeline and the second pipeline. The blended product then flows from the pipeline interchange to a third pipeline that is connected downstream of pipeline interchange. The blended product is analyzed in the third pipeline with an automated analyzer that is capable of physical and/or chemically analyzing the blended product in the third pipeline and generating blended data. The blended data is then interpreted in a data analyzer by comparing the physical and/or chemical characteristics of the blended data to an optimal blended data and determining the adjustments in the flow of the first product and the flow of the second product to achieve optimal blended data from the blended product. The adjustments are then communicated to adjust the flow of the first product in the first pipeline and the flow of the second product in the second pipeline.

In one embodiment, a process is taught where the process begins by flowing a first product through a first pipeline and flowing a second product through a second pipeline. In this embodiment, the first product in the first pipeline is analyzed with a first product automated analyzer that is capable of physical and/or chemically analyzing the first product in the first pipeline and generating a first product data. Additionally, in this embodiment, the second product in the second pipeline is analyzed with a second product automated analyzer that is capable of physical and/or chemically analyzing the second product in the second pipeline and generating a second product data. The process then produces a blended product by mixing both the first product and the second product within a pipeline interchange which is connected downstream to both the first pipeline and the second pipeline. The blended product then flows from the pipeline interchange to a third pipeline that is connected downstream of pipeline interchange. The first product data and the second product data is then interpreted in a data analyzer by comparing the physical and/or chemical characteristics of the physical and/or chemical characteristics of the first data to an optimal first data and the physical and/or chemical characteristics of the second data to an optimal second data. The data analyzer then determines the adjustments in the flow of the first product and the flow of the second product to achieve optimal blended data from the blended product. The adjustments are then communicated to adjust the flow of the first product in the first pipeline and the flow of the second product in the second pipeline.

In one embodiment, a pipeline interchange flows a product through an upstream pipeline. An automated analyzer is connected to the upstream pipeline, wherein the automated analyzer analyzes a sample of the product, and wherein the analyzer is capable of analyzing different physical and/or chemical characteristics of the product and generating a data sample. An automatic splitter is then placed downstream of the automated slipstream analyzer. In this embodiment, the automatic splitter is capable of receiving and interpreting the data sample from the automated analyzer and directing the product into at least three different downstream pipelines, wherein at least one of the downstream pipelines is a transmix pipeline and wherein at least one of the downstream pipelines returns the product upstream of the automated analyzer.

In one embodiment, the method begins by flowing a product stream through an upstream pipeline comprising a first product stream. The product stream is then continuously analyzed with an automated analyze to produce data. The first product stream downstream is then directed downstream of the automated analyzer to a downstream first product stream pipeline. The method then changes the product stream flowing through the upstream pipeline from the first product stream to a second product stream without purging the first product stream from the upstream pipeline, thereby creating a transmix product stream within the upstream pipeline wherein the transmix product stream comprises a mixture of the first product stream and the second product stream. The data from the automated analyzer is then analyzed with an automatic splitter, wherein the product stream flowing through the upstream pipeline no longer matches the physical and/or chemical characteristics of the first product stream. The automatic splitter then directs the transmix product stream downstream of the automatic splitter to a downstream transmix pipeline. As the data from the automated analyzer is still analyzed by the automatic splitter the product stream flowing through the upstream pipeline matches the physical and/or chemical characteristics of the second product stream. The automatic splitter then directs the second product stream downstream of the automatic splitter to a downstream second product stream pipeline.

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Bartlesville, OK, United States of America

Ayuba Fasasi