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Base oil properties expert system

A technology of crude oil and characteristics, applied in the field of expert systems, can solve problems such as no crude oil model prediction ability reported, no crude oil and lubricant available methods, etc.

Inactive Publication Date: 2010-12-01
CHEVROU USA INC
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Problems solved by technology

However, most of these studies were limited to specific sample groups or specific analytical techniques
Knowledge of the use of various analytical techniques other than NMR to improve the predictive power of crude oil models is not reported
More importantly, there is no method available that would allow the description of crude oils and lubricants with specific properties

Method used

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Embodiment Construction

[0012] Various studies (1-3) reported in said literature recognize that a large number of properties of most crude oils are derived from the hydrocarbon type distribution in the crude oil. During the last 60 years, NMR spectroscopy has become one of the main tools for determining the structure of hydrocarbons. Other techniques used for the characterization of hydrocarbons are MS and HPLC. In the present invention, the structural parameters of crude oil are determined by analytical techniques such as NMR, HPLC-UV and FIMS.

[0013] Crude oil was further characterized by using SIMDIST and VPO to obtain boiling point distribution and molecular weight, respectively. These structural parameters are then modeled in terms of the experimentally observed physical properties of the initial set of crude oils. Artificial neural networks are used to develop such models. Various properties that can be modeled include, but are not limited to: coefficient of kinematic viscosity at 40°C, co...

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Abstract

A method for predicting properties of lubricant base oil blends, comprising the steps of generating an NMR spectrum, HPLC-UV spectrum, and FIMS spectrum of a sample of a blend of at least two lubricant base oils and determining at least one composite structural molecular parameter of the sample from said spectra. SIMDIST and HPO analyses of the sample are then generated in order to determine a composite boiling point distribution and molecular weight of the sample from such analysis. The composite structural molecular parameter, the composite boiling point distribution and the composite molecular weight are applied to a trained neural network trained to correlate with the composite structural molecular parameter, the composite boiling point distribution and the composite molecular weight so as to predict composite properties of the sample. The properties comprise Kinematic Viscosity at 40 C, Kinematic Viscosity at 100 DEG C, Viscosity Index, Cloud Point, and Oxidation Performance.

Description

[0001] Copyright Statement and Authorization [0002] This patent document contains material that is protected by copyright. [0003] Copyright 2007. Chevron USA Inc. All rights reserved. [0004] Chevron Petroleum Corporation, the owner of this copyrighted material, has no objection to the facsimile reproduction of any of the patent disclosures as they appear in the Patent and Trademark Office patent files or records of any country, but otherwise All rights reserved. technical field [0005] The present invention relates to a computer-based expert system for predicting properties of crude oil. Background technique [0006] Currently, there is a need in the lubrication industry for an improved method that allows the prediction of the properties of crude oils, and more specifically, the description of basic components and lubricants with specific properties. Currently, there are no methods available that allow prediction of crude oil properties. Currently, crude oil is ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N24/08G01R33/44G06Q10/00G06F19/00
CPCG01R33/4808G01N24/08G06F19/707G01R33/44G06F19/704G01N33/2888G16C20/30G16C20/70
Inventor A·R·普拉德翰J·M·罗森鲍姆N·J·伯特兰D·C·克雷默A·G·希M·I·常
Owner CHEVROU USA INC
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