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Journal V.24.No.3.2022
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A step-by-step approach to creating and tuning PVT-models of reservoir hydrocarbon systems based on the state equation

T.S. Yushchenko, A.I. Brusilovsky

Original article

DOI https://doi.org/10.18599/grs.2022.3.14

164-181
rus.

open access

Under a Creative Commons license
The article is considering a new effective step-by-step approach to creating and tuning PVT-models of reservoir oil and reservoir gas condensate mixtures. The method is based on the reproducing of the results of field measurements and basic laboratory studies of representative samples in thermodynamic modeling using cubic three parameters equation of state. Tuning PVT-model is used for reliable modeling of PVT properties of reservoir fluids (reservoir oil and reservoir gas) in the design and monitoring of field development, calculation of multiphase flow in wells and field pipelines, as well as in basin modeling. 

Proposed approach makes possible to tune the PVT model with high accuracy of both reservoir oil and reservoir gas condensate system to experimental data using a step-by-step procedure, where at each step, by changing one of the parameters of the equation of state, one of the PVT properties of the hydrocarbon system is tuned. Algorithmization and automated application of this approach in specialized software products is possible.

Proposed approach allows tune reservoir oil PVT-models on the main PVT-properties such as saturation pressure, FVF, STO density, gas-oil ratio of reservoir oil and dependencies of dynamic viscosity and compressibility on pressure at reservoir temperature as well as STO density. The tuned gas-condensate PVT-model precisely reproduces the key properties such as dew point pressure, initial condensate content in the reservoir gas, z-factor of the reservoir gas, gas-oil ratio, stable condensate density, drop down curve by the result of CVD-test. 

PVT-models created on the base of the proposed method, provide reliable information on the properties of a reservoir fluid in development of flow simulation both using a reservoir simulation compositional models and using pseudo models “black oil”.
The method is illustrated by the example of creation of the adequate PVT-models of various regions of Russia reservoir oil and reservoir gas condensate mixtures.
 
PVT-model, phase equilibria, reservoir fluid, tuning approach, PVT-properties, mathematical modeling
 
  • Ahmed T. (2007). Equations of State and PVT Analysis: Applications for Improved Reservoir Modeling. Gulf Publishing Company, 557 p.
  • Al-Meshari A.A., McCain W.D. (2005). New Strategic Method to Tune Equation-of-State for Compositional Simulation. SPE-106332, 13 p. https://doi.org/10.2118/106332-MS
  • API (2003). Sampling Petroleu-m Reservoir Fluids. Washington: API Recommended Practice 44, Second Edition, 49 p.
  • Brusilovsky A.I. (1992). Mathematical Simulation of Phase Behavior of Natural Multicomponent Systems at High Pressures with an Equation of State. SPE-20180-PA, 7(01), pp. 117–122. https://doi.org/10.2118/20180-PA
  • Brusilovsky A.I. (2002). Phase Transformations in the development of oil and gas fields. Moscow: Graal, 575 p. (In Russ.)
  • Brusilovsky A.I. (2011). Methodology and results of using cubic descriptions for modeling the thermodynamic properties of natural hydrocarbon systems. Vesti gazovoy nauki, Part II, pp. 150-165. (In Russ.)
  • Brusilovsky A.I., Nugaeva A.N. (2008). New Method of Systemic Substantination of Reservoir Crude Oil properties in Calculation of reserves and field development design. SPE-117391-MS, 11 p, https://doi.org/10.2118/117391-MS
  • Cavett R.H. (1962) Physical Data for Distillation Calculations-Vapor-Liquid Equilibria. Proc. 27th API Meeting, San Francisco, p. 351.
  • Christensen P.L. (1999). Regression to Experimental PVT Data. Journal of Canadian Petroleum Technology, 38, p. 1. https://doi.org/10.2118/99-13-52
  • Coats K.H., Thomas L.K., Pierson R.G (1995). Compositional and Black oil Reservoir Simulation. SPE Res Eval & Eng, 1(04), pp. 372-379. http://dx.doi.org/10.2118/50990-PA
  • Coats K.H., Smart G.T. (1986). Application of a Regression-Based EOS PVT Program to Laboratory Data. SPERE, 5, p. 277. https://doi.org/10.2118/11197-PA
  • Dodson C.R., Goodwill D., Mayer E.H. (1953). Application of Laboratory PVT Data to Reservoir Engineering Problems. Transactions of AIME, 198, pp. 287-298. https://doi.org/10.2118/953287-G
  • Efimov A.D., Tokarev D.K., Fateev D.G., Kozubovsky A.G. (2012). Adaptation scheme for creating adequate models of gas condensate systems (on the example of the Achimov deposits of the Urengoyskoye oil and gas condensate field). Territoriya Neftegaz, 12. (In Russ.)
  • Fahim F.A., Al-Sahhaf T.A. (2009). Fundamentals of Petroleum Refining. Oxford, UK: Elsevier, 516 p.
  • Fateev D.G., Nesterenko A.N. (2014). Unification of Approaches in the Study of the Characteristics of Gas-Condensate Systems. SPE-171249-MS, https://doi.org/10.2118/171249-MS 
  • Hosein R., Dawe R.A. (2014). A Parametric Methodology in tuning the Peng-Robinson (PR) Equation of State for Gas Condensate Systems. Petroleum Science and Technology, 32, pp. 662-672. https://doi.org/10.1080/10916466.2011.603011
  • Ibeh S.U., Chubueze S.E. (2016). PVT Analysis: Validity Checks and EOS Tuning Techniques for Retrograde Gas Condensate Reservoirs. SPE-184314-MS. https://doi.org/10.2118/184314-MS
  • Jhavery B.S., Youngren G.K. (1988). Three-parameter modification of the Peng – Robinson equation of state to improve volumetric predictions. SPE Reservoir Engineering, 3, p. 1033. https://doi.org/10.2118/13118-PA
  • Joergensen M., Stenby E.H. (1995). Optimization of pseudo-component selection for compositional studies of reservoir fluids. SPE- 30789, 11 p. https://doi.org/10.2118/30789-MS
  • Katz D.L., Firoozabadi A. (1978) Predicting Phase Behavior of Condensate/Crude-Oil Systems Using Methane Interaction Coefficients. JPT, 11, p. 1649. https://doi.org/10.2118/6721-PA
  • Kesler M.G., Lee B.I. (1976). Improve Predictions of Enthalpy of Fractions. Hydro. Proc, 55, p. 153.
  • Kurosh A.G. (1972). Higher algebra. Trans. from the Russ. Moscow: Mir, 430 p.
  • Lee B.I., Kesler M.G. (1975). A Generalized Thermodynamic Correlation Based on Three-Parameter Corresponding States. AlCh J, 1, p. 510. https://doi.org/10.1002/aic.690210313
  • Lobanova O.A., Indrupskiy I.M., Yushchenko T.S. (2016). Modeling Non-Equilibrium Dynamics of Condensate Recovery for Mature Gas-Condensate Fields. SPE-181977, 14 p. https://doi.org/10.2118/181977-MS
  • Lohrenz J., Bray B.G., Clark C.R. (1964). Calculating Viscosities of Reservoir Fluids from Their Compositions. JPT, October, pp. 1171-1176. https://doi.org/10.2118/915-PA
  • Majidi M., Azari V., Karimi F. (2021). Tuning of Peng-Robinson Equation of State for Simulation of Oil Compositional Change During EOR Processes. 82nd EAGE Annual Conference & Exhibition, 2021, p.p 1-5. https://doi.org/10.3997/2214-4609.202011960
  • Mashayekhi L., Assareh M., Kasiri N. (2019). An Effective EOS Based Modeling Procedure for Minimum Miscibility Pressure in Miscible Gas Injection. Journal of Petroleum Science and Technology, 9(2), pp. 70-88.
  • Merrill R.C., Hartman K.J. (1994). A comparison of equation of state Tuning Methods. SPE-28589-MS. https://doi.org/10.2118/28589-MS
  • McCain W.D. (2017). The properties of petroleum fluids. PennWell, 576 p.
  • Michelsen M.L., Mollerup J. (2007). Thermodynamic Models: Fundamentals and Computational Aspects. Denmark: Tie-Line Publications, 382 p.
  • Naji H.S. (2010). Characterizing Pure and Undefined Petroleum Components. International Journal of Engineering & Technology, 10(2), pp. 39-68.
  • Pedersen K.S., Cristensen P.L. (2007). Phase Behavior of Petroleum Reservoir Fluids. N.Y.: CRC Press, 407 p. https://doi.org/10.1201/9781420018257
  • Pedersen K.S., Fredenslund А., Thomassen P. (1989). Properties of Oils and Natural Gases. Denmark: Petroleum Geology and Engineering, 252 p.
  • Pedersen K.S., Fredenslund A. (1987). An Improved Corresponding states model for the Prediction of Oil and Gas Viscosities and Thermal Conductivities. Chem. Eng. Sci, 42, p. 182. https://doi.org/10.1016/0009-2509(87)80225-7
  • Peng D.Y., Robinson D.B. (1976). A new Two-Constant Equation of state. Ind. Eng. Chem. Fundam, 15, p. 59. https://doi.org/10.1021/i160057a011
  • Peneloux A., Rauzy E., Freze R. (1982). A consistent volume correction for Redlich – Kwong – Soave volumes. Fluid Phase Equilibria, 8, p. 7. https://doi.org/10.1016/0378-3812(82)80002-2
  • Poling B.E., Prausnitz M., O’Connell J.P (2000). The properties of gases and Liquids. Fifth Edition. McGRAW – Hil, 768 p.
  • Rafael A. Aguilar Zurita, McCain W.D. Jr. (2002). An efficient tuning strategy to calibrate cubic EOS for compositional simulation. SPE-77382.https://doi.org/10.2118/77382-MS
  • Riazi M.R., Al-Sahhaf T.A. (1996). Physical Properties of Heavy Petroleum Fractions and Crude Oils. Fluid Phase Equilibria, 117, p. 217. https://doi.org/10.1016/0378-3812(95)02956-7
  • Riazi, M.R., Daubert, T.E. (1980). Simplify Property Predictions. Hydro.Proc., 115 p.
  • Rodriguez I., Hamouda A.A. (2010). An approach for characterization and lumping of plus fractions of heavy oil. SPE-117446. https://doi.org/10.2118/117446-PA 
  • Schebetov A.V., Galkin M.V. (2009). Evaluation of the quality and modeling of gas condensate studies under conditions of initial data uncertainty. Gazovaya promyshlennost, 9, p. 40. (In Russ.)
  • Schebetov A., Rimoldi A., Piana M. (2010). Quality Check of Gas-Condensate Pvt Studies and Eos Modelling Under Input Data Uncertainty. SPE-133258-MS. https://doi.org/10.2118/133258-MS
  • Soave G.S. (1972). Equilibrium Constants from a Modified Redlich-Kwong equation of state. Chem. Eng. Sci., 27, p. 1197. https://doi.org/10.1016/0009-2509(72)80096-4
  • Stamataki S., Magoulas S., Tassios D. (1990). Prediction of Phase Behavior and Physico-chemical Properties of HT-HP Reservoir Fluids. SPE-37294. https://doi.org/10.2118/37294-MS.
  • Whatson K.M., Nelson E.F., Murphy G.B. (1935). Characterization of Petroleum Fractions. Ind. Eng. Chem., 27, p. 1460. https://doi.org/10.1021/ie50312a018
  • Whitson C.H., Andersen T.F., Soreide I. (1989). C7+ Charactereziation of Related Equilibrium Fluids using the Gamma Distribution. Advances in Thermodynamics, 1, p. 35. https://doi.org/10.1007/978-1-4899-0771-4_3
  • Whitson C.H. (1983). Characterizing hydrocarbon plus fractions. SPE Journal, August, pp. 683-694. https://doi.org/10.2118/12233-PA
  • Whitson C.H., Brule M.R. (2000). Phase behavior. Texas: SPE Henry L. Doherty series, 235 p. https://doi.org/10.2118/9781555630874
  • Whitson C.H., Fevang O. (1996). Modeling Gas-condensate Well Deliverability. SPE-30714, 9 p. http://dx.doi.org/10.2118/30714-PA
  • Whitson C.H., Torp S.B. (1983). Evaluating Constant-Volume Depletion Data. JPT, pp. 610-620.
  • Yushchenko T.S., Brusilovsky A.I. (2014). Efficient Engineering Method for Creating Adequate PVT-model of Natural Gas Condensate Mixture Using Equation of State. SPE-171238, 18 p. https://doi.org/10.2118/171238-MS
  • Yushchenko T.S., Brusilovsky A.I. (2016). Mathematical modeling of gas-condensate mixture PVT-properties including presence of brine in reservoir. Fluid Phase Equilibria, 409, pp. 37-48. https://doi.org/10.1016/j.fluid.2015.09.029
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Taras S. Yushchenko – Cand. Sci. (Physics and Mathematics), Senior Researcher, Oil and Gas Research Institute of the Russian Academy of Sciences
3, Gubkin st., Moscow, 119333, Russian Federation
 
Alexander I. Brusilovsky – Dr. Sci. (Engineering), Professor, Senior Expert, Gazpromneft NTC LLC
Liter D, 75–79, Moyka river emb., St.Petersburg, 190000, Russian Federation
 

For citation:

Yushchenko T.S., Brusilovsky A.I. (2022). A step-by-step approach to creating and tuning PVT-models of reservoir hydrocarbon systems based on the state equation. Georesursy = Georesources, 24(3), pp. 164–181. DOI: https://doi.org/10.18599/grs.2022.3.14

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