An Evaluation of Steady-State-Based Pressure-Saturation Predictions in Gas-Condensate Reservoirs Under Various Reservoir and Well Operating Conditions
- Caroline Johnson (Heriot-Watt University) | Mahmoud Jamiolahmady (Heriot-Watt University)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- May 2019
- Document Type
- Journal Paper
- 642 - 659
- 2019.Society of Petroleum Engineers
- pressure-saturation prediction, reservoir undersaturation, two-phase steady-state, gas condensate reservoirs, gas fractional flow
- 4 in the last 30 days
- 65 since 2007
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The analysis of pressure-transient and rate-transient data in gas-condensate reservoirs (GCRs), operating below dewpoint pressure (Pdew) often requires using two-phase pseudovariables. These are used to handle the nonlinearities that arise in the governing partial-differential equation as a result of pressure-dependent saturation, mobility, and fluid-property changes. The incorporation of relative permeability (kr) data in the computation of such pseudovariables requires a priori knowledge of sufficiently representative pressure-saturation relationships. For this purpose, a number of analytical and semianalytical pressure-saturation prediction methods can be found in the literature.
In this study, a pressure-saturation prediction method, which relates component weight fractions (in the gas phase, the condensate phase, and the reservoir fluid mixture) and gas fractional flow [or gas to total gas-plus-condensate flow rate (GTR)] to pressure, was used to compute pressure-saturation relationships for various reservoir fluids and two rock types. The computed pressure-saturation relationships were compared to the responses observed in the near-wellbore region of corresponding single-well 1D radial homogeneous compositional reservoir-simulation models operated at constant well flowing pressures (Pwf) lower than Pdew. Sensitivities were conducted to highlight the impact of gas-condensate fluid richness, kr characteristics, degree of reservoir undersaturation (Pi – Pdew), and Pwf on observed trends in the representativity of the predicted pressure-saturation relationships.
Like other methods based on two-phase steady-state (SS) assumptions, the condensate saturations predicted by the GTR method generally matched those observed around the wellbore in the simulation models when Pi – Pdew was sufficiently high. For cases in which Pi – Pdew was not sufficiently high, an examination of radial pressure and saturation profiles from the simulation models showed that the trend of increased condensate saturation levels observed around the wellbore with increasing degrees of reservoir undersaturation, as reported in literature, represents one of three possible trends (i.e., increasing, decreasing, and almost-constant condensate-saturation levels). For cases in which the predicted GTR-based pressure-saturation curve showed lower (higher) condensate saturations than the pressure/volume/temperature (PVT) liquid-saturation curves at the given Pwf, increasing Pi – Pdew resulted in decreasing (increasing) condensate-saturation levels around the wellbore. The results indicate that at low Pi – Pdew values, trends in two-phase SS-based analysis techniques are affected by the gas-condensate fluid richness and the nature of the kr characteristics. It is also shown that for cases in which there is not much of a difference between PVT-based and SS-based pressure-saturation curves, variations in the Pi – Pdew do not affect the condensate-saturation levels around the wellbore.
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Becker, M. D., Zhang, M., and Ayala, H. L. F. 2016. On the Pressure-Saturation Path in Infinite-Acting Unconventional Liquid-Rich Gas Reservoirs. J Nat Gas Sci Eng 35 (Part A): 97–113. https://doi.org/10.1016/j.jngse.2016.08.007.
Behmanesh, H., Hamdi, H., and Clarkson, C. R. 2013. Production Data Analysis of Liquid Rich Shale Gas Condensate Reservoirs. Presented at the SPE Unconventional Resources Conference Canada, Calgary, Alberta, 5–7 November. SPE-167160-MS. https://doi.org/10.2118/167160-MS.
Behmanesh, H., Hamdi, H., Heidari Sureshjani, M. et al. 2014. Production Data Analysis of Overpressured Liquid-Rich Shale Reservoirs: Effect of Degree of Undersaturation. Presented at the SPE Unconventional Resources Conference, The Woodlands, Texas, 1–3 April. SPE-168980-MS. https://doi.org/10.2118/168980-MS.
Chopra, A. K. and Carter, R. D. 1986. Proof of the Two-Phase Steady-State Theory for Flow Through Porous Media. SPE Form Eval 1 (6): 603–608. SPE-14472-PA. https://doi.org/10.2118/14472-PA.
Estrada, C. A. and Settari, A. 2006. Critical Evaluation of Existing Methods for Accounting for Multiphase Effects Around Producers in Depleting Gas Condensate Reservoirs. Presented at the SPE Gas Technology Symposium, Calgary, Alberta, 15–17 May. SPE-100497-MS. https://doi.org/10.2118/100497-MS.
Fetkovich, M., Guerrero, E., Fetkovich, M. et al. 1986. Oil and Gas Relative Permeabilities Determined From Rate-Time Performance Data. Presented at the SPE Annual Technical Conference and Exhibition, New Orleans, Louisiana, 5–8 October. SPE-15431-MS. https://doi.org/10.2118/15431-MS.
Fetkovich, M. J., Vienot, M. E., Bradley, M. D. et al. 1987. Decline Curve Analysis Using Type Curves: Case Histories. SPE Form Eval 2 (4): 637–656. SPE-13169-PA. https://doi.org/10.2118/13169-PA.
Fevang, Ø. and Whitson, C. H. 1996. Modeling Gas-Condensate Well Deliverability. SPE Res Eval & Eng 11 (4): 221–230. SPE-30714-PA. https://doi.org/10.2118/30714-PA.
Fussell, D. D. 1973. Single-Well Performance Predictions for Gas Condensate Reservoirs. J Pet Technol 25 (7): 860–870. https://doi.org/10.2118/4072-PA.
Jamiolahmady, M., Danesh, A., Sohrabi, M. et al. 2007. Gas-Condensate Flow in Perforated Regions. SPE J. 12 (1): 89–99. SPE-94072-PA. https://doi.org/10.2118/94072-PA.
Johnson, C. and Jamiolahmady, M. 2015. Decline Curve Analysis for Low Permeability Gas Condensate Reservoirs: Effect of Fluid Richness, Inertia and Coupling. Presented at the 77th EAGE Conference & Exhibition 2015–Workshops 03–Geological Disposal of Radioactive Waste–Technical and Societal Challenges, Madrid, Spain, 1–4 June. https://doi.org/10.3997/2214- 4609.201413475.
Johnson, C. and Jamiolahmady, M. 2016. Decline Curve Analysis for Two-Phase Flow in Tight Gas Condensate Reservoirs. Presented at the 78th EAGE Conference and Exhibition 2016, Session: Unconventional Reservoirs II, Vienna, Austria, 30 May–2 June. https://doi.org/10.3997/2214-4609.201601139.
Jones, J., Vo, D., and Raghavan, R. 1989. Interpretation of Pressure-Buildup Responses in Gas-Condensate Wells. SPE Form Eval 4 (1): 93–104. SPE-15535-PA. https://doi.org/10.2118/15535-PA.
Jones, J. R. and Raghavan, R. 1988. Interpretation of Flowing Well Response in Gas-Condensate Wells. SPE Form Eval 3 (3): 578–594. SPE-14204-PA. https://doi.org/10.2118/14204-PA.
Mahdiyar, H. and Jamiolahmady, M. 2014. Optimization of Hydraulic Fracture Geometry in Gas Condensate Reservoirs. Fuel 119: 27–37. https://doi.org/10.1016/j.fuel.2013.11.015.
Manning, F. S. and Thompson, R. E. 1991. Oilfield Processing of Petroleum Volume One: Natural Gas. Vol. 1, 7. Tulsa, Oklahoma: PennWell Books.
O’Dell, H. G. and Miller, R. N. 1967. Successfully Cycling a Low-Permeability, High-Yield Gas Condensate Reservoir. J Pet Technol 19 (1): 41–47. https://doi.org/10.2118/1495-PA.
Osorio, R., Stewart, G., Danesh, A. et al. 2005. Estimation of Long Term Gas Condensate Well Productivity Using Pressure Transient Data. Presented at the SPE Europec/EAGE Annual Conference, Madrid, Spain, 13–16 June. SPE-94065-MS. https://doi.org/10.2118/94065-MS.
Raghavan, R., Chu, W. C., and Jones, J. 1999. Practical Considerations in the Analysis of Gas-Condensate Well Tests. SPE Res Eval & Eng 2 (3): 288–295. SPE-56837-PA. https://doi.org/10.2118/56837-PA.
Saleh, A. M. and Stewart, G. 1992. Interpretation of Gas Condensate Well Tests With Field Examples. Presented at the SPE Annual Technical Conference and Exhibition, Washington, DC, 4–7 October. SPE-24719-MS. https://doi.org/10.2118/24719-MS.
Sarisittitham, S. and Jamiolahmady, M. 2014. Decline Curve Analysis for Tight Gas and Gas Condensate Reservoirs. Presented at the International Petroleum Technology Conference, Kuala Lumpur, 10–12 December. IPTC-18188-MS. https://doi.org/10.2523/IPTC-18188-MS.
Sureshjani, M. H. and Gerami, S. 2011. A New Model for Modern Production-Decline Analysis of Gas/Condensate Reservoirs. J Can Pet Technol 50 (7–8): 14–23. SPE-149709-PA. https://doi.org/10.2118/149709-PA.
Taghizadeh Sarvestani, M., Rashidi, F. and Mousavi Dehghani, S. A. 2016. A Production Data Analysis Model for Gas/Condensate Reservoirs. J Pet Sci Eng 141: 52–69. https://doi.org/10.1016/j.petrol.2016.01.016.
Vo, D. T., Jones, J. R., and Raghavan, R. 1989. Performance Predictions for Gas-Condensate Reservoirs. SPE Form Eval 4 (4): 576–584. SPE-16984-PA. https://doi.org/10.2118/16984-PA.