WE CLAIM:
1. A method of determining and mitigating wax risk of a hydrocarbon
composition comprising:
obtaining a sample of the hydrocarbon composition;
analyzing the sample of the hydrocarbon composition to determine one or more attributes of the sample of the hydrocarbon composition;
developing one or more predictive models of a hydrocarbon production, transportation , refming, refined hydrocarbon production, processing and use process for the hydrocarbon composition entering the hydrocarbon production, transportation, refming, refined hydrocarbon production, processing and use process based on the analysis of the sample of the hydrocarbon composition;
determining wax risks based on the developed one or more predictive models; and
mitigating one or more of the determined wax risks.
2. The method of claim 1, further comprising developing a pipe flow model for a pipeline and determining wax risks in the pipeline based on the pipe flow model and the determined wax risks.
3. The method of any of claims 1-2, further comprising determining chemical additives to mitigate one or more of the determined wax risks.
4. The method of claim 3, wherein determining chemical additives to mitigate one or more of the determined wax risks comprises selecting one or more chemical additives based on matching precipitation characteristics between the one or more chemical additives and wax in the hydrocarbon composition, and/or the attributes related to composition of the hydrocarbon
5. The method of any of claims 1-4, wherein analyzing the sample of the hydrocarbon composition to determine one or more attributes of the sample of the hydrocarbon composition comprises performing one or more of fingerprint analysis of the sample, high temperature gas chromatography (HTGC) analysis of the sample, differential

scanning calorimetry analysis, inductively coupled plasma mass spectrum analysis or combination of the variable analysis of the sample to determine one or more attributes of the sample.
6. The method of any of claims 1-5, wherein the one or more attributes include Total Acid Number (TAN), American Petroleum Institute gravity (API gravity), specific gravity (SG), SARA (saturates, aromatics, resins, asphaltenes), Colloid Instability Index (CII), viscosity, rheology, wax content, heavy wax content, Wax Appearance Temperature (WAT), and Pour Point (PP).
7. The method of any one of claims 1-6, wherein the one or more predictive models of the hydrocarbon production, transportation, refming, refined hydrocarbon production, processing, handling, storage, and use are developed using one or more machine learning algorithms.
8. The method of claim 7, wherein the one or more machine learning algorithms include principal component analysis (PCA), linear regression and logistic regression.
9. The method of any of claims 1-8, wherein the determined wax risks include one or more of wax content, heavy wax content, Wax Appearance Temperature (WAT), Pour Point (PP), and wax deposition potential.
10. The method of any of claims 1-9, wherein mitigating one or more of the determined wax risks comprises modifying the production, transportation, storage, processing, and/or distribution of the hydrocarbon composition to reduce the determined wax risks.
11. A method of reducing wax risks in a hydrocarbon composition comprising:
obtaining a sample of the hydrocarbon composition;
determining one or more wax risks by:
analyzing the sample of the hydrocarbon composition to determine one or more attributes of the sample of the hydrocarbon composition;
developing one or more predictive models for the hydrocarbon composition based on the analysis of the sample of the hydrocarbon composition; and
determining the one or more wax risks based on the developed one or more predictive models; and

modifying the production, transportation, storage, processing, and/or distribution of the hydrocarbon composition to reduce the wax risks.
12. The method of claim 11, further comprising developing a pipe flow model for a pipeline and determining wax risks in the pipeline based on the determined wax risks.
13. The method of any of claims 11-12, wherein the modification of the production, transportation, storage, processing, and/or distribution of the hydrocarbon composition comprises determining one or more chemical additives to combine with the hydrocarbon composition to mitigate one or more of the determined wax risks.
14. The method of claims 13, wherein determining chemical additives to mitigate one or more of the determined wax risks comprises selecting one or more chemical additives based on matching precipitation characteristics between the one or more chemical additives and wax in the hydrocarbon composition.
15. The method of any of claims 10-14, wherein analyzing the sample of the hydrocarbon composition to determine one or more attributes of the sample of the hydrocarbon composition comprises performing one or more of fingerprint analysis of the sample, high temperature gas chromatography (HTGC) analysis of the sample, differential scanning calorimetry analysis, inductively coupled plasma mass spectrum analysis or combination of the variable analysis of the sample to determine one or more attributes of the sample.
16. The method of any one of claims 10-15, wherein the one or more predictive models of the hydrocarbon refining are developed using one or more machine learning algorithms.
17. The method of claim 16, wherein the one or more machine learning algorithms include principal component analysis (PCA), linear regression and logistic regression.
18. The method of any of claims 10-17, wherein the determined wax risks include one or more of Wax Appearance Temperature (WAT), Pour Point (PP), wax content, heavy wax content, and wax deposition potential.
19. A system for using predictive analytics in management of a hydrocarbon process, said system comprising:

a memory, wherein the memory stores computer-readable instructions; and
a processor communicatively coupled with the memory, wherein the processor executes the computer-readable instructions stored on the memory, the computer-readable instructions causing the processor to:
receive an analysis of a hydrocarbon sample,
develop one or more predictive models for a hydrocarbon based on one or more attributes of the sample of the hydrocarbon composition determined in the analysis of the hydrocarbon sample;
determine wax risks based on the developed one or more predictive models; and
control aspects of the hydrocarbon process based on the determined wax risks to mitigate one or more of the determined wax risks,
wherein the analysis is obtained by the following steps:
obtaining a sample of the hydrocarbon composition; and
analyzing the sample of the hydrocarbon composition to determine the one or more attributes of the sample of the hydrocarbon composition.
20. The system of claim 19, further comprising causing the processor to execute instructions to develop a pipe flow model for a pipeline and determine wax risks in the pipeline based on the determined wax risks.
21. The system of any of claims 19-20, wherein controlling aspects of the hydrocarbon process comprises causing the processor to execute instructions to determine one or more chemical additives to combine with the hydrocarbon composition to mitigate the determined wax risks.
22. The system of claim 21, wherein the processor determining chemical additives to mitigate the determined wax risks comprises causing the processor to execute instructions to select one or more chemical additives based on matching precipitation characteristics between the one or more chemical additives and wax in the hydrocarbon composition.
23. The system of any of claims 19-22, wherein analyzing the sample of the hydrocarbon composition to determine one or more attributes of the sample of the

hydrocarbon composition comprises performing one or more of fingerprint analysis of the sample, high temperature gas chromatography (HTGC) analysis of the sample, differential scanning calorimetryanalysis, inductively coupled plasma mass spectrum analysis or combination of the variable analysis of the sample to determine one or more attributes of the sample.
24. The system of any of claims 19-23, wherein the one or more attributes include Total Acid Number (TAN), American Petroleum Institute gravity (API gravity), specific gravity (SG), SARA (saturates, aromatics, resins, asphaltenes), Colloid Instability Index (CII), viscosity, rheology, wax content, heavy wax content, Wax Appearance Temperature (WAT), and Pour Point (PP).
25. The system of any one of claims 19-24, wherein the one or more predictive models of the hydrocarbon refining are developed by the processor executing instructions that comprise one or more machine learning algorithms.
26. The system of claim 25, wherein the one or more machine learning algorithms include principal component analysis (PCA), linear regression and logistic regression.
27. The system of any of claims 19-26, wherein the causing the processor to execute instructions to determine wax risks comprises determining one or more of Wax Appearance Temperature (WAT), Pour Point (PP), wax content, heavy wax content and wax deposition potential.
28. The system of any one of claims 19-27, wherein controlling aspects of the hydrocarbon process based on the determined wax risks to mitigate one or more of the determined wax risks comprises controlling one or more of hydrocarbon production, transportation, refining, refined hydrocarbon production, processing, handling, storage, and use as the hydrocarbon composition enters the production, transportation, refining, refined hydrocarbon production, processing, handling, storage, and use or moves through the production, transportation, refining, refined hydrocarbon production, processing, handling, storage, and use.