AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home Advances in Geo-Energy Research Article
PDF (1.2 MB)
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Invited Review | Open Access

Understanding and modeling of gas-condensate flow in porous media

Department of Chemical Engineering, University of Utah, Salt Lake City, Utah 84112, United States
Energy & Geoscience Institute, University of Utah, Salt Lake City, Utah 84108, United States
Show Author Information

Abstract

Well deliverability impairment due to liquid dropout inside gas-condensate reservoirs below dewpoint pressure is a common production problem. The operating conditions and the thermodynamic properties of the condensate govern the production performance of this type of reservoir. Modeling condensate production using analytical, semi-analytical or empirical formula for quick assessment of reservoir performance is a complicated method due to the complex thermodynamic behavior. The objective of this study is to provide a fundamental understanding of the flow and thermodynamics of gas-condensate fluid to develop tools for the production prediction. The prior developments of flow modeling of gas-condensate are briefly reviewed. The multi-phase flow and the depletion stages during production are discussed. Each component of pseudo-pressure calculations to determine the condensate flow rate is explained. Thermodynamic properties and laboratory experiment relevant to the flow of condensate are also explored. Pressure-volume-temperature (PVT) properties such as two-phase envelope, constant composition expansion (CCE) and constant volume depletion (CVD) are demonstrated for three different gas-condensate fluids namely lean, intermediate and rich.

Keywords

Gas-condensateflow modelingdepletion mechanismpseudo-pressurePVT properties

References

 

Agarwal, R.G., Gardner, D.C., Kleinsteiber, S.W., et al. Analyzing well production data using combined type curve and decline curve analysis concepts. SPE Reserv. Eval. Eng. 1999, 2(5): 478-486.
Crossref Google Scholar
 

Ahmed, T. Reservoir Engineering Handbook. Oxford, United Kingdom, Gulf Professional Publishing, 2010.
 
Amorim, T.C.A.D., Schiozer, D.J. Risk analysis speed-up with surrogate models. Paper SPE 153477 Presented at SPE Latin America and Caribbean Petroleum Engineering Conference, Mexico City, Mexico, 16-18 April, 2012.https://doi.org/10.2118/153477-MS
Crossref
 
Anifowose, F.A., Ewenla, A.O., Eludiora, S.I. Prediction of oil and gas reservoir properties using support vector machines. Paper IPTC-14514-MS Presented at International Petroleum Technology Conference, Bangkok, Thailand, 15-17 November, 2011.https://doi.org/10.2523/IPTC-14514-MS
Crossref
 

Arps, J.J. Analysis of decline curves. Trans. AIME 1945, 160(1): 228-247.
Crossref Google Scholar
 

Behmanesh, H., Hamdi, H., Clarkson, C.R. Production data analysis of gas condensate reservoirs using two-phase viscosity and two-phase compressibility. J. Nat. Gas Sci. Eng. 2017, 47: 47-58.
Crossref Google Scholar
 

Bonyadi, M., Rahimpour, M.R., Esmaeilzadeh, F. A new fast technique for calculation of gas condensate well productivity by using pseudopressure method. J. Nat. Gas Sci. Eng. 2012, 4: 35-43.
Crossref Google Scholar
 
Carreras, P.E., Turner, S.E., Wilkinson, G.T. Tahiti: Development strategy assessment using design of experiments and response surface methods. Paper SPE 100656 Presented at SPE Western Regional/AAPG Pacific Section/GSA Cordilleran Section Joint Meeting, Anchorage, Alaska, USA, 8-10 May, 2006.https://doi.org/10.2118/100656-MS
Crossref
 

Chen, Z., Huan, G., Wang, H. Computer simulation of compositional flow using unstructured control volume finite element methods. Computing 2006, 78: 31-53.
Crossref Google Scholar
 
Clark, A.J., Lake, L.W., Patzek, T.W. Production forecasting with logistic growth models. Paper SPE 144790 Presented at SPE Annual Technical Conference and Exhibition, Denver, Colorado, USA, 30 October-2 November, 2011.https://doi.org/10.2118/144790-MS
Crossref
 

Clarkson, C.R., Qanbari, F., Nobakht, M., et al. Incorporating geomechanical and dynamic hydraulic-fracture-property changes into rate-transient analysis: Example from the haynesville shale. SPE Reserv. Eval. Eng. 2013, 16(3): 303-316.
Crossref Google Scholar
 

Coleman, S., Wilde Jr., H.D., Moore, T.W. Quantitative effect of gas-oil ratios on decline of average rock pressure. Trans. AIME 1930, 86(1): 174-184.
Crossref Google Scholar
 

Cook, R.E., Jacoby, R.H., Ramesh, A.B. A beta-type reservoir simulator for approximating compositional effects during gas injection. Soc. Pet. Eng. J. 1974, 14(5): 471-481.
Crossref Google Scholar
 
Dahaghi, A.K., Esmaili, S., Mohaghegh, S.D. Fast track analysis of shale numerical models. Paper SPE 162699 Presented at SPE Canadian Unconventional Resources Conference, Calgary, Alberta, Canada, 30 October-1 November, 2012.
 

Dong, J.J., Hsu, J.Y., Wu, W.J., et al. Stress-dependence of the permeability and porosity of sandstone and shale from TCDP Hole-A. Int. J. Rock Mech. Min. Sci. 2010, 47(7): 1141-1157.
Crossref Google Scholar
 
Dong, X., Liu, H., Hou, J., et al. Phase behavior of hydrocarbon mixtures in the organic nanopores of unconventional gas condensate reservoirs. Paper URTEC-2460485-MS Presented at SPE/AAPG/SEG Unconventional Resources Technology Conference, San Antonio, Texas, USA, 1-3 August, 2016.https://doi.org/10.15530/urtec-2016-2460485
Crossref
 
Duong, A.N. An unconventional rate decline approach for tight and fracture-dominated gas wells. Paper SPE 137748 Presented at Canadian Unconventional Resources and International Petroleum Conference, Calgary, Alberta, Canada, 19-21 October, 2010.https://doi.org/10.2118/137748-MS
Crossref
 

Eilerts, C.K., Sumner, E.F., Potts, N.L. Integration of partial differential Eq. for transient radial flow of gas-condensate fluids in porous structures. Soc. Pet. Eng. J. 1965, 5(2): 141-152.
Crossref Google Scholar
 
El-Sebakhy, E.M., Sheltami, T., Al-Bokhitan, S.Y. et al. Support vector machines framework for predicting the PVT properties of crude-oil systems. Paper SPE 105698 Presented at SPE Middle East Oil and Gas Show and Conference, Manama, Bahrain, 11-14 March, 2007.https://doi.org/10.2118/105698-MS
Crossref
 

Evinger, H.H., Muskat, M. Calculation of theoretical productivity factor. Trans. AIME 1942, 146(1): 126-139.
Crossref Google Scholar
 

Fatt, I. The effect of overburden pressure on relative permeability. J. Pet. Technol. 1953, 5(10): 15-16.
Crossref Google Scholar
 

Fatt, I., Davis, D.H. Reduction in permeability with overburden pressure. J. Pet. Technol. 1952, 4(12): 16.
Crossref Google Scholar
 
Fetkovich, M.D., Guerrero, E.T., Fetkovich, M.J., et al. Oil and gas relative permeabilities determined from rate-time performance data. Paper SPE 15431 Presented at SPE Annual Technical Conference and Exhibition, New Orleans, Louisiana, 5-8 October, 1986.https://doi.org/10.2118/15431-MS
Crossref
 

Fetkovich, M.J. Decline curve analysis using type curves. J. Pet. Technol. 1980, 32(6): 1065-1077.
Crossref Google Scholar
 

Fevang, Ø., Whitson, C.H. Modeling gas-condensate well deliverability. SPE Reserv. Eng. 1996, 11(4): 221-230.
Crossref Google Scholar
 

Fussell, D.D. Single-well performance predictions for gas condensate reservoirs. J. Pet. Technol. 1973, 25(7): 860-870.
Crossref Google Scholar
 
Gerami, S., Sadeghi, A., Masihi, M. New technique for calculation of gas condensate well deliverability. Paper SPE 130139 Presented at SPE Deep Gas Conference and Exhibition, Manama, Bahrain, 24-26 January, 2010.https://doi.org/10.2118/130139-MS
Crossref
 

Gondouin, M., Iffly, R., Husson, J. An attempt to predict the time dependence of well deliverability in gas condensate fields. Soc. Pet. Eng. J. 1967, 7(2): 113-124.
Crossref Google Scholar
 
Guehria, F.M. Inflow performance relationships for gas condensates. Paper SPE 63158 Presented at SPE Annual Technical Conference and Exhibition, Dallas, Texas, 1-4 October, 2000.https://doi.org/10.2118/63158-MS
Crossref
 

Havlena, D., Odeh, A.S. The material balance as an Eq. of a straight line. J. Pet. Technol. 1963, 15(8): 895-900.
Crossref Google Scholar
 
Ilk, D., Rushing, J.A., Perego, A.D., et al. Exponential vs. Hyperbolic decline in tight gas sands: Understanding the origin and implications for reserve estimates using Arps' decline curves. Paper SPE 116731 Presented at SPE Annual Technical Conference and Exhibition, Denver, Colorado, USA, 21-24 September, 2008.https://doi.org/10.2118/116731-MS
Crossref
 
Johnson, C., Jamiolahmady, M. Production data analysis using type curves in tight gas condensate reservoirs-impact of pressure-dependent permeability. Paper SPE 190832 Presented at SPE Europec featured at 80th EAGE Conference and Exhibition, Copenhagen, Denmark, 11-14 June, 2018.
 

Jones, J.R., Raghavan, R. Interpretation of flowing well response in gas-condensate wells (includes associated papers 19014 and 19216). SPE Form. Eval. 1988, 3(3): 578-594.
Crossref Google Scholar
 

Kikani, J., Pedrosa Jr., O.A. Perturbation analysis of stress-sensitive reservoirs (includes associated papers 25281 and 25292). SPE Form. Eval. 1991, 6(3): 379-386.
Crossref Google Scholar
 

Kniazeff, V.J., Nvaille, S.A. Two-phase flow of volatile hydrocarbons. Soc. Pet. Eng. J. 1965, 5(1): 37-44.
Crossref Google Scholar
 

Labed, I., Oyeneyin, B., Oluyemi, G. Gas-condensate flow modelling for shale reservoirs. J. Nat. Gas Sci. Eng. 2018, 59: 156-167.
Crossref Google Scholar
 
Li, B., Friedmann, F. Novel multiple resolutions design of experiment/response surface methodology for uncertainty analysis of reservoir simulation forecasts. Paper SPE 92853 Presented at SPE Reservoir Simulation Symposium, The Woodlands, Texas, 31 January-2 February, 2005.https://doi.org/10.2118/92853-MS
Crossref
 

Liu, L., Yao, J., Sun, H., et al. Compositional modeling of shale condensate gas flow with multiple transport mechanisms. J. Pet. Sci. Eng. 2019, 172: 1186-1201.
Crossref Google Scholar
 
Mannon, R.W. Oil production forecasting by decline curve analysis. Paper SPE 1254 Presented at Fall Meeting of the Society of Petroleum Engineers of AIME, Denver, Colorado, 3-6 October, 1965.https://doi.org/10.2118/1254-MS
Crossref
 

McCain, W.D. The Properties of Petroleum Fluids. Tulsa, USA, PennWell Books, 2017.
 

McKee, C.R., Bumb, A.C., Koenig, R.A. Stress-dependent permeability and porosity of coal and other geologic formations. SPE Form. Eval. 1988, 3(1): 81-91.
Crossref Google Scholar
 

Mead, H.N. Modifications to decline curve analysis. Trans. AIME 1956, 207(1): 11-16.
Crossref Google Scholar
 

Millikan, C.V. Gas-oil ratio as related to the decline of oil production, with notes on the effect of controlled pressure. Trans. AIME 1926, G-26(1): 147-157.
Crossref Google Scholar
 

Momeni, A., Dadvar, M., Hekmatzadeh, M., et al. 3D pore network modeling and simulation for dynamic displacement of gas and condensate in wellbore region. Int. J. Multiph. Flow 2017, 97: 147-156.
Crossref Google Scholar
 

Mott, R. Engineering calculations of gas condensate well productivity. SPE Reserv. Eval. Eng. 2003, 6(5): 298-306.
Crossref Google Scholar
 

Muskat, M. The production histories of oil producing gas-drive reservoirs. J. Appl. Phys. 1945, 16(3): 147-159.
Crossref Google Scholar
 

O'Dell, H.G. Successfully cycling a low-permeability, high-yield gas condensate reservoir. J. Pet. Technol. 1967, 19(1): 41-47.
Crossref Google Scholar
 
Okouma Mangha, V., Guillot, F., Sarfare, M., et al. Estimated ultimate recovery (EUR) as a function of production practices in the Haynesville shale. Paper SPE 147623 Presented at SPE Annual Technical Conference and Exhibition, Denver, Colorado, USA, 30 October-2 November, 2011.https://doi.org/10.2118/147623-MS
Crossref
 
Orangi, A., Nagarajan, N.R., Honarpour, M.M., et al. Unconventional shale oil and gas-condensate reservoir production, impact of rock, fluid, and hydraulic fractures. Paper SPE 140536 Presented at SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, USA, 24-26 January, 2011.https://doi.org/10.2118/140536-MS
Crossref
 

Ostensen, R.W. The effect of stress-dependent permeability on gas production and well testing. SPE Form. Eval. 1986, 1(3): 227-235.
Crossref Google Scholar
 
Palacio, J.C., Blasingame, T.A. Decline-curve analysis with type curves-Analysis of gas well production data. Paper SPE 28688 Presented at International Petroleum Conference and Exhibition of Mexico, Veracruz, Mexico, 10-13 October, 1994.https://doi.org/10.2118/25909-MS
Crossref
 

Panja, P., Conner, T., Deo, M. Factors controlling production in hydraulically fractured low permeability oil reservoirs. Int. J. Oil Gas Coal Technol. 2016, 13(1): 1-18.
Crossref Google Scholar
 

Panja, P., Deo, M. Factors that control condensate production from shales: Surrogate reservoir models and uncertainty analysis. SPE Reserv. Eval. Eng. 2016, 19(1): 130-141.
Crossref Google Scholar
 

Panja, P., Deo, M. Unusual behavior of produced gas oil ratio in low permeability fractured reservoirs. J. Pet. Sci. Eng. 2016, 144: 76-83.
Crossref Google Scholar
 

Panja, P., Pathak, M., Deo, M. Productions of volatile oil and gas-condensate from liquid rich shales. Adv. Geo-Energy Res. 2019, 3(1): 29-42.
Crossref Google Scholar
 
Panja, P., Pathak, M., Velasco, R., et al. Least square support vector machine: An emerging tool for data analysis. Paper SPE 180202 Presented at SPE Low Perm Symposium, Denver, Colorado, 5-6 May, 2016.https://doi.org/10.2118/180202-MS
Crossref
 
Pan, S., Ma, J., Zuo, J.Y., et al. A pore-scale mechanistic investigation of shale gas condensate at near saturation pressure on fluid flow in shale. Paper URTEC-2019-248-MS Presented at SPE/AAPG/SEG Unconventional Resources Technology Conference, Denver, Colorado, USA, 22-24 July, 2019.https://doi.org/10.15530/urtec-2019-248
Crossref
 

Parikh, H. Reservoir characterization using experimental design and response surface methodology. USA, Texas A & M University, 2003.
 
Pathak, M., Deo, M., Panja, P., et al. The effect of kerogen-hydrocarbons interaction on the PVT properties in liquid rich shale plays. Paper SPE 175905 Presented at SPE/CSUR Unconventional Resources Conference, Calgary, Alberta, Canada, 20-22 October, 2015.https://doi.org/10.2118/175905-MS
Crossref
 
Pratikno, H., Rushing, J.A., Blasingame, T.A. Decline curve analysis using type curves-Fractured wells. Paper SPE 84287 Presented at SPE Annual Technical Conference and Exhibition, Denver, Colorado, 5-8 October, 2003.https://doi.org/10.2118/84287-MS
Crossref
 

Qanbari, F., Clarkson, C.R. Rate-transient analysis of liquid-rich tight/shale reservoirs using the dynamic drainage area concept: Examples from north american reservoirs. J. Nat. Gas Sci. Eng. 2016, 35: 224-236.
Crossref Google Scholar
 

Raghavan, R., Scorer, J.D.T., Miller, F.G. An investigation by numerical methods of the effect of pressure-dependent rock and fluid properties on well flow tests. Soc. Pet. Eng. J. 1972, 12(3): 267-275.
Crossref Google Scholar
 
Rushing, J.A., Perego, A.D., Sullivan, R., et al. Estimating reserves in tight gas sands at hp/ht reservoir conditions: Use and misuse of an arps decline curve methodology. Paper SPE 109625 Presented at SPE Annual Technical Conference and Exhibition, Anaheim, California, 11-14 November, 2007.https://doi.org/10.2118/109625-MS
Crossref
 

Santos, M.P.P.C., Carvalho, M.S. Pore network model for retrograde gas flow in porous media. J. Pet. Sci. Eng. 2020, 185: 106635.
Crossref Google Scholar
 

Schilthuis, R.J. Active oil and reservoir energy. Trans. AIME 1936, 118(1): 33-52.
Crossref Google Scholar
 

Tarner, J. How different size gas caps and pressure maintenance programs affect amount of recoverable oil. Oil Wkly. 1944, 144(2): 32-44.
Google Scholar
 

Thomas, R.D., Ward, D.C. Effect of overburden pressure and water saturation on gas permeability of tight sandstone cores. J. Pet. Technol. 1972, 24(2): 120-124.
Crossref Google Scholar
 
Thompson, J.M., Nobakht, M., Anderson, D.M. Modeling well performance data from overpressured shale gas reservoirs. Paper SPE 137755 Presented at Canadian Unconventional Resources and International Petroleum Conference, Calgary, Alberta, Canada, 19-21 October, 2010.https://doi.org/10.2118/137755-MS
Crossref
 
Thornton, O.F. Gas-condensate reservoirs-a review. Paper API-46-150 Presented at Drilling and Production Practice, New York, 1 January, 1946.
 

Tracy, G.W. Simplified form of the material balance Eq.. Trans. AIME 1955, 204(1): 243-246.
Crossref Google Scholar
 

Vairogs, J., Hearn, C.L., Dareing, D.W., et al. Effect of rock stress on gas production from low-permeability reservoirs. J. Pet. Technol. 1971, 23(9): 1161-1167.
Crossref Google Scholar
 
Valko, P.P. Assigning value to stimulation in the Barnett Shale: A simultaneous analysis of 7000 plus production hystories and well completion records. Paper SPE 119369 Presented at SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, 19-21 January, 2009.https://doi.org/10.2118/119369-MS
Crossref
 
Velasco, R., Panja, P., Deo, M. New production performance and prediction tool for unconventional reservoirs. Paper URTEC-2461718-MS Presented at SPE/AAPG/SEG Unconventional Resources Technology Conference, San Antonio, Texas, USA, 1-3 August, 2016.https://doi.org/10.15530/urtec-2016-2461718
Crossref
 
Whitson, C.H., Sunjerga, S. PVT in liquid-rich shale reservoirs. Paper SPE 155499 Presented at SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, 8-10 October, 2012.https://doi.org/10.2118/155499-MS
Crossref
 
Xiao, J.J., Al-Muraikhi, A.J. A new method for the determination of gas condensate well production performance. Paper SPE 90290 Presented at SPE Annual Technical Conference and Exhibition, Houston, Texas, 26-29 September, 2004.https://doi.org/10.2118/90290-MS
Crossref
 

Xiong, Q., Baychev, T.G., Jivkov, A.P. Review of pore network modelling of porous media: Experimental characterisations, network constructions and applications to reactive transport. J. Contam. Hydrol. 2016, 192: 101-117.
Crossref Google Scholar
 

Yang, S., Wu, K., Xu, J., et al. Roles of multicomponent adsorption and geomechanics in the development of an eagle ford shale condensate reservoir. Fuel 2019, 242: 710-718.
Crossref Google Scholar
Advances in Geo-Energy Research
Volume 4 Issue 2,
June 2020
Pages 173-186
DOI: 10.26804/ager.2020.02.06
Cite this article:
Panja P, Velasco R, Deo M. Understanding and modeling of gas-condensate flow in porous media. Advances in Geo-Energy Research, 2020, 4(2): 173-186. https://doi.org/10.26804/ager.2020.02.06

874

Views

236

Downloads

10

Crossref

8

Web of Science

12

Scopus

Altmetrics
Received: 20 March 2020
Revised: 10 April 2020
Accepted: 10 April 2020
Published: 19 April 2020
© The Author(s) 2020

This article, published at Ausasia Science and Technology Press on behalf of the Division of Porous Flow, Hubei Province Society of Rock Mechanics and Engineering, is distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Return