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A case study of gas-condensate reservoir performance with gas cycling

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The study examines the application of dry gas injection technology (cycling process) in different depletion stages (25%, 50%, 75%, 100% of the initial reservoir pressure, and the dew point pressure) at a gas condensate field. The injection took place with varying numbers of injection wells relative to production wells (4:1, 3:1, 2:1, 1:1, and 1:2). The study assessed the impact of dry gas injection periods, ranging from 1 to 3 years, on increasing the condensate recovery factor in a real gas condensate reservoir named X. A hydrodynamic model was used and calibrated with historical data, resulting in a comprehensive approach. Compared to the traditional depletion development method, this approach led to a significant 9% rise in the condensate recovery factor. The results indicate that injection has a positive effect on enhancing the recovery factor of condensate and gas when compared to primary development methods based on depletion. As a result, these findings facilitate a rapid evaluation of the possibility of introducing similar measures in gas-condensate reservoirs in the future for reservoir systems that have a low and moderate potential for liquid hydrocarbons C5+. The optimised multidimensional hydrodynamic calculations, utilising geological and technological models, are crucial in determining the parameters for the technological production and injection wells.
Rocznik
Strony
25--49
Opis fizyczny
Bibliogr. 29 poz., rys., tab., wykr.
Twórcy
  • AGH University of Krakow, al.Mickiewicza 30, 30-059 Kraków, Poland
  • Ivano-Frankivsk National Technical University of Oil and Gas, Ukraine
  • AGH University of Krakow, al.Mickiewicza 30, 30-059 Kraków, Poland
Bibliografia
  • [1] I .I. Rybchich, V.S. Kremez, Y.I. Kalugin, O.F. Nemchin, V.V. Yakovlev, Optimization of condensate recovery processes in the development of gas condensate fields for depletion. Materials of the 8th International Scientific and Practical Conference Oil and Gas of Ukraine, 15-16 (2004).
  • [2] R . Ter-Sarkisov, Hydrothermodynamic modeling of active methods of GCF development. Oil and Gas Business 13 (2), 68-73 (2015).
  • [3] A.I. Brusilovsky, Multicomponent filtration of gas-condensate systems in deeply submerged deposits. Oil and Gas Geology 7, 31-38 (1997).
  • [4] A.I. Gritsenko, V.V. Remizov, R.M. Ter-Sarkisov, V.G. Podyuk, V.A. Nikolaev, A.N. Shandrygin, Guide to restore the productivity of gas condensate wells, Moscow (1995).
  • [5] L. Fan, B.W. Harris, A.J. Jamaluddin, J. Kamath, R. Mott, G.A. Pope, A. Shandrygin, C. Whitson, Oilfield Review 10 (4), 16-25 (2005).
  • [6] S.N. Zakyrov, R.M. Kondrat, Active influence on the process of development of hydrocarbon gas fields with increased hydrocarbon yield of reservoirs. Reports of the International Conference on Development of Gas Condensate Fields, Development of oil and gas condensate fields, Krasnodar, 24-28 (1990).
  • [7] A. Al-Shawaf, M. Kelkar, M. Sharifi, A New Method To Predict the Performance of Gas-Condensate Reservoirs. SPE Reservoir Evaluation & Engineering 17 (2), 177-189 (2014). DOI: https://doi.org/10.2118/161933-PA.
  • [8] I .M. Kuper, A.V. Uhrynovskyi, Physics of oil and gas reservoir. Ivano-Frankivsk (2018).
  • [9] V.S. Boyko, R.M. Kondrat, Р.S. Yaremiychuk, Handbook of oil and gas business. Lviv (1996).
  • [10] E.S. Bikman, M.P. Gnip, V.M. Doroshenko, Prospects for increasing the hydrocarbon recovery of Andriyashivske GCF. Oil and gas of Ukraine: Proceedings of the 8th international scientific and and Practical Conf. on Oil and Gas of Ukraine – 2004, Sudak 2, 19-21 (2004).
  • [11] R .I. Vyakhirev, A.I. Gritsenko, R.M. Ter-Sarkisov, Development and exploitation of gas fields. Moscow (2002).
  • [12] K. Deepak, Gupta, Fluid Characterization and Modeling of Compositional Variation, Dukhan Field. International Petroleum Technology Conference, Qatar (2009). DOI: https://doi.org/10.2523/IPTC-13657-MS.
  • [13] M.G. Miller, M.R. Lents, Performance of Bodcaw Reservoir, Cotton Valley Field Cycling Project; New Methods of Predicting Gas-condensate Reservoir Performance Under Cycling Operations Compared to Field Data. Oklahoma (1946). DOI: https://api.semanticscholar.org/CorpusID:109236740.
  • [14] K. Luo, S. Li, X. Zheng, G. Chen, Z. Dai, N. Liu, Experimental Investigation into Revaporization of Retrograde Condensate by Lean Gas Injection. Indonesia (2001). DOI: https://doi.org/10.2118/68683-MS.
  • [15] C.A. Kossack, S.T. Opdal, Recovery of Condensate From a Heterogeneous Reservoir by the Injection of a Slug of Methane Followed by Nitrogen. USA (1988). DOI: https://doi.org/10.2118/18265-MS.
  • [16] G. Massonnat, C. Bachtanik, E. Tutenuit, P. Gouel, N. Carles, Early Evaluation of Uncertainties in the Incremental Condensate Recovery Through a Gas Cycling Process 2, 33-47 (1997). DOI: https://doi.org/10.2118/30569-PA.
  • [17] S. Karra, E.O. Egbogah, F.W. Yang, Stochastic and Deterministic Reserves Estimation in Uncertain Environments. Malaysia (1995). DOI: https://doi.org/10.2118/29286-MS.
  • [18] R .M. Kondrat, Gas-condensate recovery of reservoirs. Moscow (1992).
  • [19] O.V. Burachok, Study of the possibility of water displacement of condensate that has fallen out in the formation. Oil and Gas Industry 2, 29-32 (2007).
  • [20] Qi Xinlei, Liu Shenghui, Yu Zhengliang, Sun Hedong, Chang Baohua, Luo Zhengyuan, Bai Bofeng, Interfacial dynamics of gas-water displacement in fractured porous media under high pressure. Physics of Fluids 33, (2021). DOI: https://doi.org/10.1063/5.0062141.
  • [21] Reporting materials received from an oil and gas enterprise during the 2020-2021 industrial practice (2020).
  • [22] Schlumberger product. User manual for the PETREL software module «Guru of PETREL 2017» Saturation tab (2017).
  • [23] A. Afanasyev, Crude oil and gas condensate forecasting in the computable simulation model for money circulation in the russian economy. Econ. Math. Methods 53 (2), 50-65 (2017).
  • [24] S.P. Rodriguez, Methodology and Equations of Mineral Production Forecast – Part I. Crude Oil in the UK and Gold in Nevada, USA, Prediction of Late Stages of Production. Open Journal of Geology 352-360 (2013). DOI: https://doi.org/10.4236/ojg.2013.35040.
  • [25] T. Hastie, R. Tibshirani, J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, second ed. Springer Series in Statistics (2009). DOI: https://doi.org/10.1111/j.1541-0420.2010.01516.x.
  • [26] M. Amani, N. Nguyen, An Overview of Methods to Mitigate Condensate Banking in Retrograde Gas. Advances in Petroleum Exploration and Development 9 (2), 1-6 (2015). DOI: https://doi.org/10.3968/7023.
  • [27] R. Hosein, R. A. Dawe, M. Amani, Peng-Robinson equation of state predictions for gas condensate before and after lumping. Journal of Advances in Petroleum Exploration and Development 2 (2), 41-46 (2011). DOI: https://doi.org/10.3968/j.aped.1925543820110202.105.
  • [28] R. Engineer, Cal Canal field, California: Case history of a tight and abnormally pressured gas condensate reservoir. California (1985). DOI: https://doi.org/10.2118/13650-MS.
  • [29] A.M. Al-Yami, F.A. Gomez, K.I. Al Hamed, M.H. Al-Buali, A successful field application of a new chemical treatment in a fluid blocked well in Saudi Arabia, Saudi Arabia (2013). DOI: https://doi.org/10.2118/168086-MS.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-03cad5e2-2b9d-4aba-b09b-489c1318a732
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