Characterization of crude oil by near infrared spectroscopy

1. A system for assigning an indicative property to a gas oil fraction of an oil sample, wherein the oil sample is selected from a group consisting of crude oils, bitumens, heavy oils and shale oils, the system comprising:

a near infrared (NIR) spectrometer that outputs near infrared spectroscopy data;

a non-volatile memory device that stores calculation modules and data, the data including the NIR spectroscopy data indicative of absorbance values of the oil sample for peaks detected in a predetermined wavenumber range for the oil sample;

a processor coupled to the non-volatile memory device;

a first calculation module that calculates a near infrared absorbance index of the oil sample from the NIR spectroscopy data; and

a second calculation module that calculates the indicative property of the gas oil fraction of the oil sample as a function of the near infrared absorbance index and a density of the oil sample, and that stores the indicative property into the non-volatile memory device, wherein the indicative property is used to determine one or more of engine/fuel performance, usability, flow characteristic, or composition of the gas oil fraction of the oil sample.

2. The system of claim 1 , wherein the first calculation module calculates the near infrared absorbance index from a summation of the absorbance values for the peaks detected by the near infrared spectrometer in the predetermined wavenumber range.

3. The system of claim 1 , wherein the second calculation module calculates the indicative property with a multi-variable polynomial equation with a set of predetermined constant coefficients developed using linear regression wherein corresponding variables are the near infrared absorbance index and the density of the oil sample.

4. A method for assigning an indicative property to a gas oil fraction of an oil sample, wherein the oil sample is selected from a group consisting of crude oils, bitumens, heavy oils and shale oils, the method comprising:

obtaining near infrared spectroscopy data indicative of absorbance values of the oil sample for peaks detected in a predetermined wavenumber range for the oil sample and entering the near infrared spectroscopy data of the oil sample into a non-volatile memory of a computer;

using a processor of the computer to calculate a near infrared absorbance index of the oil sample from the near infrared spectroscopy data; and

using the processor of the computer to calculate and record the indicative property of the gas oil fraction of the oil sample as a function of the near infrared absorbance index and a density of the oil sample, wherein the indicative property is used to determine one or more of the engine/fuel performance, usability, flow characteristic, or composition of the gas oil fraction of the oil sample.

5. The method of claim 4 wherein the oil sample is crude oil.

6. The method of claim 4 wherein the oil sample is obtained from an oil well, stabilizer, extractor, or distillation tower.

7. The method of claim 4 wherein the indicative property is a cetane number.

8. The method of claim 4 wherein the indicative property is a pour point.

9. The method of claim 4 wherein the indicative property is a cloud point.

10. The method of claim 4 wherein the indicative property is an aniline point.

11. The method of claim 4 wherein plural indicative properties are calculated including at least two indicative properties selected from a group consisting of cetane number, pour point, cloud point and aniline point.

12. The method of claim 4 wherein the indicative property is of the gas oil fraction boiling in a nominal range 180-370° C.

13. The method of claim 4 , wherein the predetermined wavenumber range is 4,000-12,821 cm −1 .

14. The method of claim 4 , wherein the near infrared absorbance index is calculated from a summation of the absorbance values for the peaks detected by the near infrared spectrometer in the predetermined wavenumber range.

15. The method of claim 4 , wherein the indicative property is calculated with a multi-variable polynomial equation with a set of predetermined constant coefficients developed using linear regression wherein corresponding variables are the near infrared absorbance index and the density of the oil sample.