بررسی عوامل کلیدی مؤثر بر دقت محاسبات اشباع آب در مخازن کربناته: سازندهای کنگان و دالان، غرب خلیج فارس

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشکده زمین‌شناسی، دانشکدگان علوم، دانشگاه تهران، تهران، ایران

چکیده

ارزیابی خصوصیات مخازن کربناته باتوجه‌به ناهمگنی بسیار زیاد این مخازن، همواره با دشواری‌ها و عدم‌قطعیت‌های زیادی همراه است. اشباع آب یکی از پارامترهای بسیار مهم در ارزیابی این مخازن به شمار می‌آید. علاوه بر این، تأثیر اشباع آب بر مکانیک سنگ به‌عنوان یک پدیده‌ی مهم در مهندسی ژئوتکنیک شناخته می‌شود. رایج‌ترین رابطه برای اشباع آب، معادله‌ی آرچی است. دقت اشباع آب محاسبه شده از طریق معادله‌ی آرچی به‌دقت پارامتر‌های آن از جمله ضریب سیمانی‌شدن، ضریب پیچاپیچی و ضریب اشباع بستگی دارد. ناهمگنی مخازن کربناته، به طور قابل‌توجهی بر ضرایب معادله‌ی آرچی و در نتیجه محاسبات اشباع آب تأثیر می‌گذارد. در این مطالعه، از ۱۵۷ داده‌ی اشباع آب دین استارک، ۵۷ داده‌ی فاکتور مقاومت سازند، ۲۰ داده‌ی شاخص مقاومت سازند، ۱۳۶۸ مقطع نازک و ۱۱۱۴ داده‌های تخلخل و نفوذپذیری تهیه شده از یک چاه اکتشافی در غرب خلیج‌فارس استفاده شده است. به‌منظور مدیریت ناهمگنی، از روش‌های مختلفی از جمله روش راندمان الکتریکی، نشانگر زون جریان و وینلند استفاده شد. پس از دسته‌بندی سنگ‌ها با پارامترهای الکتریکی و پتروفیزیکی مشابه، پارامترهای آرچی در دسته‌های مختلف محاسبه شدند. سپس اشباع آب با استفاده از رابطه‌ی آرچی در هریک از دسته‌های تعیین شده، محاسبه و با اشباع آب دین استارک مقایسه شد. علاوه بر این، پارامترهای تأثیرگذار بر دقت اشباع آب، موردبحث و برسی قرار گرفت. نتایج، اهمیت برسی ویژگی‌های رفتار الکتریکی و شعاع گلوگاه‌های منفذی به‌عنوان عوامل کلیدی مؤثر بر دقت محاسبات اشباع آب را نشان دادند. بر اساس یافته‌ها، استفاده از پارامترهای ثابت آرچی منجر به محاسبه اشباع آب، بیش از اندازه‌ی واقعی و در نتیجه، برآورد کمتر از میزان واقعی هیدروکربور در مخازن می‌شود. یافته‌ها نشان داد که مدیریت ناهمگنی مخزن به روش راندمان الکتریکی، تأثیر قابل‌توجهی بر افزایش دقت اشباع آب پیش‌بینی‌شده در مقایسه با دیگر روش‌ها دارد. در مقابل، روش وینلند بیشترین عدم‌قطعیت را در پیش‌بینی اشباع آب دارد.

کلیدواژه‌ها


عنوان مقاله [English]

Examining Key Factors Influencing the Accuracy of Water Saturation Calculations in Carbonate Reservoirs: A Case Study of Kangan and Dalan Formations in the Western Persian Gulf

نویسندگان [English]

  • Sajjad Omrani
  • Vahid Tavakoli
School of Geology, College of Science, University of Tehran, Tehran, Iran
چکیده [English]

Evaluating the characteristics of carbonate reservoirs, given their significant heterogeneity, is always accompanied by challenges and high uncertainties. Water saturation is a crucial parameter in assessing these reservoirs, and the Archie equation is commonly used for water saturation estimation. Moreover, the effect of water saturation on the mechanical behavior of rock is recognized as an important phenomenon in geotechnical engineering. The accuracy of water saturation calculated through the Archie equation depends on the precision of its parameters, including cementation exponent, saturation exponent, and tortuosity exponent. The heterogeneity of carbonate reservoirs significantly affects the Archie equation coefficients and, consequently, water saturation calculations. In this study, various methods, including the electrical efficiency, current zone indicator, and Winland method, were employed to manage reservoir heterogeneity. Subsequently, Archie parameters were calculated for each category, and water saturation was determined and compared with Dean-Stark water saturation. Furthermore, the influential parameters on the accuracy of water saturation were discussed and examined. To achieve the study objectives, 157 Dean-Stark water saturation data, 57 core plug samples for formation resistivity factor (FRF) determination, 20 core plug samples for measuring formation resistivity index (FRI), 1114 porosity and permeability measurements from core plug samples and 1368 thin sections were utilized from an exploration well in the western Gulf of Persian. Our findings highlight the significance of exploring electrical behavior characteristics and pore throat radii as crucial elements influencing the precision of water saturation calculations. As per the results, employing constant Archie parameters leads to an overestimation of water saturation and, consequently, an underestimation of hydrocarbon reserves. Our analysis illustrates that effectively managing reservoir heterogeneity through the electrical efficiency method significantly improves the accuracy of predicted water saturation compared to other approaches. Conversely, the Winland method exhibits the highest uncertainty in predicting water saturation.

کلیدواژه‌ها [English]

  • Rock type
  • electrical efficiency
  • Archie parameters
  • heterogeneity management
  • current zone indicator
  • electrical conductivity
[1] J. Abdolmaleki, V. Tavakoli, A. Asadi-Eskandar, Sedimentological and diagenetic controls on reservoir properties in the Permian-Triassic successions of Western Persian Gulf, Southern Iran, J. Pet. Sci. Eng. 141 (2016) 90–113. https://doi.org/10.1016/j.petrol.2016.01.020.
[2] C. Hollis, Diagenetic controls on reservoir properties of carbonate successions within the Albian-Turonian of the Arabian Plate, Pet. Geosci. 17 (2011) 223–241. https://doi.org/10.1144/1354-079310-032.
[3] H. Mehrabi, E. Yahyaei, A. Navidtalab, H. Rahimpour-Bonab, R. Abbasi, M. Omidvar, A. Assadi, J. Honarmand, Depositional and diagenetic controls on reservoir properties along the shallow-marine carbonates of the Sarvak Formation, Zagros Basin: Petrographic, petrophysical, and geochemical evidence, Sediment. Geol. 454 (2023) 106457. https://doi.org/10.1016/j.sedgeo.2023.106457.
[4] H. Rahimpour-Bonab, A. Asadi-Eskandari, A. Sonei, Control of Permian-Triassic Boundary over reservoir characteristics of South Pars Gas Field, (2009).
[5] V. Tavakoli, H. Rahimpour-Bonab, B. Esrafili-Dizaji, Diagenetic controlled reservoir quality of South Pars gas field, an integrated approach, Comptes Rendus Geosci. 343 (2011) 55–71. https://doi.org/10.1016/J.CRTE.2010.10.004.
[6] A.M. Mohamad, G.M. Hamada, Determination techniques of Archie’s parameters: A, m and n in heterogeneous reservoirs, J. Geophys. Eng. 14 (2017) 1358–1367. https://doi.org/10.1088/1742-2140/aa805c.
[7] S.S. El Din, M.R. Dernaika, I. Al Hosani, L. Hannon, S.M. Skjæveland, M.Z. Kalam, Whole core versus plugs: Integrating log and core data to decrease uncertainty in petrophysical interpretation and STOIP calculations, in: Soc. Pet. Eng. - 14th Abu Dhabi Int. Pet. Exhib. Conf. 2010, ADIPEC 2010, SPE, 2010: pp. 1139–1155. https://doi.org/10.2118/137679-ms.
[8] G.M. Hamada, A.A. Almajed, T.M. Okasha, A.A. Algathe, Uncertainty analysis of Archie’s parameters determination techniques in carbonate reservoirs, J. Pet. Explor. Prod. Technol. 3 (2013) 1–10. https://doi.org/10.1007/s13202-012-0042-x.
[9] H.T. Janjuhah, G. Kontakiotis, A. Wahid, D.M. Khan, S.D. Zarkogiannis, A. Antonarakou, Integrated porosity classification and quantification scheme for enhanced carbonate reservoir quality: Implications from the miocene malaysian carbonates, J. Mar. Sci. Eng. 9 (2021) 1410. https://doi.org/10.3390/jmse9121410.
[10] H. Sun, H. Belhaj, G. Tao, S. Vega, L. Liu, Rock properties evaluation for carbonate reservoir characterization with multi-scale digital rock images, J. Pet. Sci. Eng. 175 (2019) 654–664. https://doi.org/10.1016/j.petrol.2018.12.075.
[11] M.N. Ali Akbar, J.T. Musu, B. Milad, Water saturation interpretation model for organic-rich shale reservoir: A case study of North Sumatra Basin, SPE/AAPG/SEG Unconv. Resour. Technol. Conf. 2018, URTC 2018. (2018). https://doi.org/10.15530/urtec-2018-2879229.
[12] A. Alimoradi, A. Moradzadeh, M.R. Bakhtiari, Methods of water saturation estimation: Historical perspective, J. Pet. Gas Eng. 2 (2011) 45–53. http://www.academicjournals.org/JPGE.
[13] A.R. Gupta, Kamal, A theoretical approach for water saturation estimation in shaly sandstones, Geoenergy Sci. Eng. 228 (2023) 212001. https://doi.org/10.1016/j.geoen.2023.212001.
[14] M.I. Miah, M. Tamim, Hydrocarbon Saturation Assessment of Thick Shaly Sand Reservoir Using Hydrocarbon Saturation Assessment of Thick Shaly Sand Reservoir Using Wireline Log Data : A Case Study, 10th Int. Forum Strateg. Technol. (2015) 1–6.
[15] B. Zhang, J. Xu, Methods for the evaluation of water saturation considering TOC in shale reservoirs, J. Nat. Gas Sci. Eng. 36 (2016) 800–810. https://doi.org/10.1016/j.jngse.2016.11.023.
[16] H.A. Jumaah, Modified Archie’s parameters for estimating water saturation for carbonate reservoir in north of Iraq, J. Pet. Explor. Prod. Technol. 11 (2021) 3689–3697. https://doi.org/10.1007/s13202-021-01258-3.
[17] E.S. Kazak, A. V. Kazak, A novel laboratory method for reliable water content determination of shale reservoir rocks, J. Pet. Sci. Eng. 183 (2019). https://doi.org/10.1016/j.petrol.2019.106301.
[18] L. Zhuang, K.Y. Kim, M. Diaz, S. Yeom, Evaluation of water saturation effect on mechanical properties and hydraulic fracturing behavior of granite, Int. J. Rock Mech. Min. Sci. 130 (2020). https://doi.org/10.1016/j.ijrmms.2020.104321.
[19] G.E. Archie, The Electrical Resistivity Log as an Aid in Determining Some Reservoir Characteristics, Trans. AIME. 146 (1942) 54–62. https://doi.org/10.2118/942054-G.
[20] S. Gomaa, A.A. Soliman, A. Mohamed, R. Emara, A.M. Attia, New Correlation for Calculating Water Saturation Based on Permeability, Porosity, and Resistivity Index in Carbonate Reservoirs, ACS Omega. 7 (2022) 3549–3556. https://doi.org/10.1021/acsomega.1c06044.
[21] F. Hadavimoghaddam, M. Ostadhassan, M.A. Sadri, T. Bondarenko, I. Chebyshev, A. Semnani, Prediction of water saturation from well log data by machine learning algorithms: Boosting and super learner, J. Mar. Sci. Eng. 9 (2021). https://doi.org/10.3390/jmse9060666.
[22] A. Movahhed, M.N. Bidhendi, M. Masihi, A. Emamzadeh, Introducing a method for calculating water saturation in a carbonate gas reservoir, J. Nat. Gas Sci. Eng. 70 (2019). https://doi.org/10.1016/j.jngse.2019.102942.
[23] M. Nazemi, V. Tavakoli, H. Rahimpour-Bonab, M. Hosseini, M. Sharifi-Yazdi, The effect of carbonate reservoir heterogeneity on Archie’s exponents (a and m), an example from Kangan and Dalan gas formations in the central Persian Gulf, J. Nat. Gas Sci. Eng. 59 (2018) 297–308. https://doi.org/10.1016/j.jngse.2018.09.007.
[24] J.C. Rasmus, Variable Cementation Exponent, M, for Fractured Carbonates., Log Anal. 24 (1983) 13–23.
[25] M.R. Rezaee, H. Motiei, E. Kazemzadeh, A new method to acquire m exponent and tortuosity factor for microscopically heterogeneous carbonates, J. Pet. Sci. Eng. 56 (2007) 241–251. https://doi.org/10.1016/j.petrol.2006.09.004.
[26] A. Soleymanzadeh, M. Jamialahmadi, A. Helalizadeh, B.S. Soulgani, A new technique for electrical rock typing and estimation of cementation factor in carbonate rocks, J. Pet. Sci. Eng. 166 (2018) 381–388. https://doi.org/10.1016/j.petrol.2018.03.045.
[27] V. Tavakoli, D. Hassani, H. Rahimpour-Bonab, A. Mondak, How petrophysical heterogeneity controls the saturation calculations in carbonates, the Barremian–Aptian of the central Persian Gulf, J. Pet. Sci. Eng. 208 (2022). https://doi.org/10.1016/j.petrol.2021.109568.
[28] R. Woodhouse, Accurate reservoir water saturations from oil-mud cores: Questions and answers from Prudhoe Bay and beyond, Log Anal. 39 (1998) 23–44.
[29] L. Xiao, C. chun Zou, Z. qiang Mao, Y. jiang Shi,  xiao peng Liu, Y. Jin, H. peng Guo, X. xin Hu, Estimation of water saturation from nuclear magnetic resonance (NMR) and conventional logs in low permeability sandstone reservoirs, J. Pet. Sci. Eng. 108 (2013) 40–51. https://doi.org/10.1016/j.petrol.2013.05.009.
[30] Z.Q. Mao, C.G. Zhang, C.Z. Lin, J. Ouyang, Q. Wang, C.J. Yan, The effects of pore structure on electrical properties of core samples from various sandstone reservoirs in tarim basin, SPWLA 36th Annu. Logging Symp. 1995. (1995).
[31] M. Miller, K. Shanley, Petrophysics in tight gas reservoirs - Key challenges still remain, Lead. Edge (Tulsa, OK). 29 (2010) 1464–1469. https://doi.org/10.1190/1.3525361.
[32] Z. Qin, H. Pan, H. Ma, A.A. Konaté, M. Hou, S. Luo, Fast prediction method of Archie’s cementation exponent, J. Nat. Gas Sci. Eng. 34 (2016) 291–297. https://doi.org/10.1016/j.jngse.2016.06.070.
[33] Y. Ghanbari, M. Mavaddat, Introducing a new correlation for calculating cementation factor in petrophysical evaluation in South Iranian oil reservoirs, 81st EAGE Conf. Exhib. 2019. (2019). https://doi.org/10.3997/2214-4609.201900982.
[34] S. Mahmoodpour, E. Kamari, M.R. Esfahani, A.K. Mehr, Prediction of cementation factor for low-permeability Iranian carbonate reservoirs using particle swarm optimization-artificial neural network model and genetic programming algorithm, J. Pet. Sci. Eng. 197 (2021). https://doi.org/10.1016/j.petrol.2020.108102.
[35] J. Raiga-Clemenceau, The cementation exponent in the formation factor-porosity relation: The effect of permeability, SPWLA 18th Annu. Logging Symp. 1977. (1977).
[36] H.S. Salem, G. V. Chilingarian, The cementation factor of Archie’s equation for shaly sandstone reservoirs, J. Pet. Sci. Eng. 23 (1999) 83–93. https://doi.org/10.1016/S0920-4105(99)00009-1.
[37] M. Tabibi, M.A. Emadi, Variable Cementation Factor Determination (Empirical Methods), in: Proc. Middle East Oil Show, SPE, 2003: pp. 541–549. https://doi.org/10.2118/81485-ms.
[38] W.Z. Wan Bakar, I. Mohd Saaid, M.R. Ahmad, Z. Amir, N.S. Japperi, M.F.I. Ahmad Fuad, Improved water saturation estimation in shaly sandstone through variable cementation factor, J. Pet. Explor. Prod. Technol. 12 (2022) 1329–1339. https://doi.org/10.1007/s13202-021-01391-z.
[39] M. Watfa, R. Nurmi, S.T. Services, Calculation of Saturation, Secondary Porosity and Producibility in Complex Middle East Carbonate Reservoirs, Middle East. (1987) 1–24.
[40] D. Tiab, E.C. Donaldson, Petrophysics. Theory and Practice of Measuring Reservoir Rock and Fluid Transport Properties, Elsevier, 2012. https://doi.org/10.1016/C2009-0-64503-7.
[41] J.W. Focke, D. Munn, Cementation Exponents in Middle Eastern Carbonate Reservoirs., SPE Form. Eval. 2 (1987) 155–167. https://doi.org/10.2118/13735-PA.
[42] M. Al Hammadi, S. Al-Maskari, E.-S. Radwan, Improving Oil In Place Estimation through an Improve Water Saturation Prediction – A Case Study in the Middle East, in: All Days, SPE, 2008: pp. 1369–1374. https://doi.org/10.2118/118126-MS.
[43] P.R. Sharland, D.M. Archer, R.B. Casey, S.H. Davies, A.P. Hall, A.D. Heward, A.D. Horbury, M.D. Simmons, Arabian plate sequence stratigraphy, Geo-Marine Spec. Publ. 2. 3 (2001) 56–74.
[44] E. Insalaco, A. Virgone, B. Courme, J. Gaillot, M.R. Kamali, A. Moallemi, M. Lotfpour, S. Monibi, Upper Dalan Member and Kangan Formation between the Zagros Mountains and offshore Fars, Iran: Depositional system, biostratigraphy and stratigraphic architecture, GeoArabia. 11 (2006) 75–176. https://doi.org/10.2113/geoarabia110275.
[45] M.S. Kashfi, GEOLOGY OF THE PERMIAN “SUPER‐GIANT” GAS RESERVOIRS IN THE GREATER PERSIAN GULF AREA, J. Pet. Geol. 15 (1992) 465–480. https://doi.org/10.1111/j.1747-5457.1992.tb01046.x.
[46] B. Esrafili-Dizaji, H. Rahimpour-Bonab, A review of permo-triassic reservoir rocks in the zagros area, sw iran: Influence of the qatar-fars arch, J. Pet. Geol. 36 (2013) 257–279. https://doi.org/10.1111/jpg.12555.
[47] A.S. Alsharhan, A.E.M. Nairn, Sedimentary basins and petroleum geology of the Middle East, 1997. https://doi.org/10.1016/s0264-8172(99)00008-2.
[48] S.N. Dasgupta, M.R. Hong, I.A. Al-Jallal, Accurate reservoir characterization to reduce drilling risk in Khuff-C carbonate, Ghawar field, Saudi Arabia, GeoArabia. 7 (2002) 81–100. https://doi.org/10.2113/geoarabia070181.
[49] H. Rahimpour-Bonab, A. Asadi-Eskandar, R. Sonei, Effects of the Permian-Triassic boundary on reservoir characteristics of the South Pars gas field, Persian Gulf, Geol. J. 44 (2009) 341–364. https://doi.org/10.1002/gj.1148.
[50] V. Tavakoli, Chemostratigraphy of the Permian-Triassic Strata of the Offshore Persian Gulf, Iran, in: Chemostratigraphy Concepts, Tech. Appl., 2015: pp. 373–393. https://doi.org/10.1016/B978-0-12-419968-2.00014-5.
[51] J. Aali, H. Rahimpour-Bonab, M.R. Kamali, Geochemistry and origin of the world’s largest gas field from Persian Gulf, Iran, J. Pet. Sci. Eng. 50 (2006) 161–175. https://doi.org/10.1016/j.petrol.2005.12.004.
[52] O. Rahmani, M. Khoshnoodkia, H. Mohseni, M. Hajian, Sequence stratigraphy of the Triassic Period: Case from the Dashtak and Khaneh-Kat formations, the Zagros Basin, Iran, J. Pet. Sci. Eng. 167 (2018) 447–457. https://doi.org/10.1016/j.petrol.2018.03.092.
[53] S. Kolodzie, Analysis Of Pore Throat Size And Use Of The Waxman-Smits Equation To Determine Ooip In Spindle Field, Colorado, in: All Days, SPE, 1980. https://doi.org/10.2118/9382-MS.
[54] A. Soleymanzadeh, A. Helalizadeh, M. Jamialahmadi, B.S. Soulgani, Development of a new model for prediction of cementation factor in tight gas sandstones based on electrical rock typing, J. Nat. Gas Sci. Eng. 94 (2021) 104128. https://doi.org/10.1016/j.jngse.2021.104128.
[55] V. Tavakoli, Carbonate Reservoir Heterogeneity, Springer International Publishing, Cham, 2020. https://doi.org/10.1007/978-3-030-34773-4.
[56] P. Kolah-kaj, S. Kord, A. Soleymanzadeh, Application of electrical rock typing for quantification of pore network geometry and cementation factor assessment, J. Pet. Sci. Eng. 208 (2022). https://doi.org/10.1016/j.petrol.2021.109426.
[57] B. Esmaeili, H. Rahimpour-Bonab, A. Kadkhodaie, A. Ahmadi, S. Hosseinzadeh, Developing a saturation-height function for reservoir rock types and comparing the results with the well log-derived water saturation, a case study from the Fahliyan formation, Dorood oilfield, Southwest of Iran, J. Pet. Sci. Eng. 212 (2022). https://doi.org/10.1016/j.petrol.2022.110268.