1. PC-SAFT Crude Oil Characterization for Modeling of Phase Behavior and Compositional Grading of Asphaltene Sai R Panuganti, Anju S Kurup, Francisco M Vargas, Walter G Chapman 1

2. Outline Asphaltene introduction Background of asphaltene thermodynamic analysis Comparison of Cubic and PC-SAFT EoS Robustness of PC-SAFT characterization methodology Asphaltene compositional grading Future Work Conclusion 2

3. Introduction Modified Yen Model Mullins OC. Energy & Fuels 2010; 24(4):2179-2207 3 Operational Definition 1.Soluble in aromatic solvents 2.Insoluble in light paraffinic solvents Asphaltene 1.Polarizable 2.Polydisperse 3.Heavy fraction in crude oil

4. Modeling Asphaltene Stability Limitations of Colloidal Model: Negative Hydropilic-Lipophilic Balance for asphaltene [Czarnecki J-2009] Impedence Analysis – Resins are unlikely to coat asphaltene [Goual-2009] Diffusion coefficient of asphaltene is same in the presence and absence of resin Nellensteyn FJ. Journal of the Institute of Petroleum Technologist 1928; 14:134-138 Colloidal Model (~1930) Stability based on polar-polar interactions. Micelle formation Asphaltene particles kept in solution by resins adsorbed on them Solubility Model (~1980) Asphaltene solubilized by the oil. London dispersion dominate phase behavior. Approaches: (Less parameters) Flory-Huggins-regular solution theory EoS 4

5. Solubility Model Approaches Flory-Huggins type models Limitation: 1.Effective molar volume significantly lower than actual molar volume. 2.Cannot account for compressibility Equations of State 1. Cubic-EoS 2. SAFT based models Hirshberg A. Journal of Petroleum Technology 1988; 40(1):89-94 5

6. Modeling using Cubic EoS (Crude A) Crude A Characterized the crude oil system using PVT-Sim of Calsep The Cubic EoS employed was SRK-P 6

7. Modeling using Cubic EoS (Crude A) The optimized Cubic EoS parameters from 5% were used to predict the phase behavior for 30% injected gas Limitations of cubic equation of state: Asphaltene critical properties are not well known Results are very sensitive to parameters Larry GC et al. Advances in Thermodynamics (Volume 1): C7+ Fraction Characterization. Taylor & Francis; 1989 7

8. Introduction to SAFT 8 Parameters represent the physical system directly PC-SAFT EOS is be used Parameters for most compounds are known Chapman WG et al. Industrial Engineering and Chemistry Research 1990; 29(8):1709-1721. Gonzalez DL et al. Energy & Fuels 2005; 19(4):1230-1234.

9. PC-SAFT Characterization Developed a standardized characterization procedure based on: Methodology: Composition data up to C9+ is sufficient. Few parameters were needed Temperature independent binary interaction parameters for all compounds are very small Panuganti SR et al. “PC-SAFT Characterization of Crude Oils and Modeling of Asphaltene Phase Behavior” Fuel - Submitted SARA analysis Flashed Liquid and Gas compositions (C9+) Molecular Weights Liquid Density Bubble Pressure AOP Stable Unstable VLE 9

10. Comparison of PC-SAFT and Cubic EoS (Crude A) Characterized using PC-SAFT and SRK-P EoS Will PC-SAFT work better than Cubic EOS? Will a specific set of PC-SAFT parameters be sufficient to capture the phase behavior of the system at a different condition? SRK-P PC-SAFT 10

11. Comparison of PC-SAFT and Cubic EoS Crude B Better performance of PC-SAFT is visible Will PC-SAFT with proposed characterization procedure be able to predict phase behavior for higher amounts of gas injected? SRK-P PC-SAFT 11

12. Comparison of PC-SAFT and Cubic EoS Crude B PC-SAFT holds upper hand over C EoS What about for even higher gas injection? SRK-P PC-SAFT 12

13. PC-SAFT vs. Optimized Cubic EOS Crude B SRK-P PC-SAFT 13

14. Prediction of Effect of Gas Injection Crude C A different crude, exhibiting different physical properties. Characterized using standardized methodology 14

15. Robust Methodology Crude C 1. Robust Methodology 2. Good parameter estimation Any property of the precipitate phase can be calculated 15

16. Compositional Grading Introduction Used for: 1. To predict oil properties with depth 2. Find out gas-oil contact How is asphaltene compositional grading useful? Reservoir connectivity A M Schulte. SPE Conference; September 21-25, 1980 Høier L, Whitson CH. SPE 74714; 2001; 4(6)525-535 16

17. Compositional Grading Algorithm Whitson C H & Belery P; SPE 28000 1994 443-459

18. Reservoir Compartmentalization All zones belong to the same reservoir as the gradient slopes are nearly the same. The curves do not overlap meaning each of them belong to different zone. 18

19. Approximate Analytical Solution ρ= Molar density; h=Depth; = Partial Molar Volume M i =Mol wt Assumptions: 1.Changes in density of oil with depth can be neglected 2.At infinite dilution partial molar volume is independent of composition 3.System is far away from critical point such that partial molar volume is independent of pressure changes Sage BH, Lacey WN. Los Angeles Meeting, AIME; October 1938 Morris Muskat. Physical Review 1930; 35(1):1384-1392 19

20. We have Partial molar volume of asphaltene = 1934 cm 3 /mol. It corresponds to a particle size of 1.83 nm Analytical solution can be used for sensitivity analysis and approximate estimate. 20 Approximate Analytical Solution

21. Future Work Tar mat occurrence due to compositional grading of asphaltene. QCM-D experiments for determination of asphaltene deposition rates and aging effects. Micro fluidic studies to understand the asphaltene deposition mechanism. 21

22. Conclusion Solubility model using PC-SAFT EoS PC-SAFT characterization methodology proposed Robustness of PC-SAFT characterization methodology Evaluate reservoir compartmentalization through asphaltene compositional grading. 22

23. Acknowledgement Walter G Chapman Francisco Vargas Anju S Kurup Jeff Creek 23

24. 24

25. Characterization of T Oil 25

26. Derivation of Thermodynamic Model 26

27. Algorithm 27