CLIAMS:1. A method for estimating a cold-flow property of a refinery product blend for feed oil selection and refinery process optimization, the method comprising:
receiving, by a processor (104), inputs including properties of refinery products to be blended and ratios of the refinery products to be used for producing the refinery product blend;
determining, by the processor (104), whether the refinery products include at least one heavy product based on the received properties of refinery products and refinery product data (116) fetched from database (110);
estimating, by the processor (104), the cold-flow property of the refinery product blend based on a first correlation when the refinery products include the at least one heavy product, wherein the first correlation is fetched from correlation data (118) in the database (110);
estimating, by the processor, the cold-flow property of the refinery product blend based on a second correlation when the refinery products include no heavy product, wherein the second correlation is fetched from the correlation data (118) in the database (110), wherein the first correlation and the second correlation differ in at least a sign of a coefficient; and
providing, by the processor (104), the estimated cold-flow property of the refinery product blend for feed oil selection and refinery process optimization.

2. The method as claimed in claim 1, the cold-flow property is one of pour point and cloud point.

3. The method as claimed in claim 1, wherein, when the cold-flow property is pour point, the first and second correlation provide correlations between a pour point index of the refinery product blend and the pour point of the refinery product blend.

4. The method as claimed in claim 3, comprising determining, by the processor (104) the pour point index of the refinery product blend based on pour point indices of the refinery products and weight fractions of the refinery products in the refinery product blend.

5. The method as claimed in claim 1, wherein when the cold-flow property is pour point, the first correlation has a negative coefficient and the second correlation has a positive coefficient.

6. A system (100) for estimating a cold-flow property of a refinery product blend for feed oil selection and refinery process optimization, the system (100) comprising:
a processor (104);
a database (110) comprising refinery product data (116) and correlation data (118); and
a properties estimation module (112) coupled to the processor (104) and the database (110) to:
receive, as input, properties of refinery products to be blended and ratios of the refinery products to be used for producing the refinery product blend;
determine whether the refinery products include at least one heavy product based on the input and the refinery product data (116);
retrieve a first coefficient from the correlation data (118) when the identified refinery products include the at least one heavy product and retrieve a second coefficient from the correlation data (118) when the identified refinery products include no heavy product; and
estimate the cold-flow property of the refinery product blend based on the retrieved coefficient, a correlation between the cold-flow property and a cold-flow property index that includes the coefficient, and the refinery product data (116).

7. The system (100) as claimed in claim 6, wherein the cold-flow property is one of pour point and cloud point.

8. The system (100) as claimed in claim 6, wherein, when the cold-flow property is pour point, the cold-flow property index is a pour point index of the refinery product blend.

9. The system (100) as claimed in claim 8, comprising determining the pour point index of the refinery product blend based on pour point indices of the refinery products available in the refinery product data and weight fractions of the refinery products in the refinery product blend.

10. The system (100) as claimed in claim 6, wherein when the cold-flow property is pour point, the first coefficient is negative and the second coefficient is positive.
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