تفکیک زون مخزن هیدروکربنی با استفاده از داده های لرزه نگاری سه بعدی، چاه و پارامترهای ژئومکانیکی در یکی از میادین نفتی جنوب ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 موسسه ژئوفیزیک دانشگاه تهران

2 استاد- موسسه ژیوفیزیک دانشگاه تهران

چکیده

تفکیک پتانسیل زون‌های مختلف یک مخزن هیدروکربنی یکی از چالش‌های مطرح برای محققین در این حوزه است. تاکنون رهیافت‌های مختلفی در زمینه زون‌بندی مخزن هیدروکربنی ارائه شده است. در این میان سئوالی که مطرح می‌شود این است که آیا با استفاده از پارامترهای ژئومکانیکی می‌توان زون‌های مختلف یک مخزن را به لحاظ پتانسیل هیدروکربنی از یکدیگر تفکیک نمود؟ برای مثال آیا می‌توان در یک مخزن هیدروکربنی ماسه سنگی، زون‌های  ماسه‌ای و شیلی را از یکدیگر تفکیک کرد؟ در این تحقیق برای پاسخ به این سؤال برآن شدیم که با محاسبه پارامترهای ژئومکانیکی درک مناسبی از تفاوت رفتار ژئومکانیکی زون مخزنی و غیرمخزنی را به دست آوریم. به این منظور برای به دست آوردن پارامترهای ژئومکانیکی از داده‌های لرزه‌ای سه‌بعدی یکی از میادین نفتی جنوب ایران به همراه داده‌های چهار حلقه چاه موجود استفاده شد. ابتدا وارون‌سازی بر روی داده‌های لرزه‌ای سه‌بعدی پیش از برانبارش انجام شد و سه پارامتر، امپدانس‌های صوتی S ، P و چگالی استخراج گردید. سپس با استفاده از نتایج مرحله وارون‌سازی، پارامترهای ژئومکانیکی شامل مدول‌های الاستیک، ضرایب لامه و ضریب شکنندگی مخزن مورد محاسبه قرار گرفت. در مرحله بعد با استفاده از پارامترهای ژئومکانیکی محاسبه شده، زون مخزنی به خوبی از زون غیرمخزنی به لحاظ پتانسیل هیدروکربنی در مقاطع زمانی تفکیک شد. پارامترهای ژئومکانیکی محاسبه شده با استفاده از نمودارهای نقطه‌ای و مقایسه با نگاره‌های یکی از چاه‌های موجود که از فرایند محاسبات کنار گذاشته شده بود مورد صحت سنجی قرار گرفت. در نتیجه مقدار همبستگی برای امپدانس صوتی بیش از ۹۰ درصد به دست آمد.

کلیدواژه‌ها


عنوان مقاله [English]

Separation of hydrocarbon reservoir zone using three-dimensional seismic data, wells and geomechanical parameters in one of the oil fields in southern Iran

نویسندگان [English]

  • Yasser Taras 1
  • Mohammad Ali Riahi 2
1 Geophysics institute of Tehran university
2 Geophysics Institution, University of Tehran,Iran
چکیده [English]

Determining the hydrocarbon reservoir zone is one of the challenges for researchers in this field. So far, various approaches have been proposed in the field of hydrocarbon reservoir zoning. In the meantime, the question that arises is whether the potential of different zones of a hydrocarbon reservoir can be separated using geomechanical parameters? For example, in a sandstone reservoir, can the sandy and shale zones be separated? To answer this question, it is necessary to calculate some of the geomechanical parameters of the reservoir. Therefore, in this study, to obtain geomechanical parameters, three-dimensional seismic data of one of the oil fields in southern Iran were used along with the data of four existing wells. In this way, first inversion was performed on three-dimensional pre-stack seismic data, and three parameters, acoustic impedances (S and P waves) and density were extracted. Then, using the results of the inversion step, geomechanical parameters including elastic modulus, Lame parameters (LMR) and brittleness were calculated. In the next step, using the calculated geomechanical parameters, the reservoir zone was well separated from the non-reservoir zone in terms of hydrocarbon potential in time sections. Then, the calculated geomechanical parameters were verified using scatter diagrams and by comparing with the logs of the existing wells. The correlation value for the acoustic impedance was more than 90%.

کلیدواژه‌ها [English]

  • Geomechanics
  • Hydrocarbon Reservoir
  • Elastic Modulus
  • Lame Parameters
  • Brittleness
[1] Guo S, Wang H. (2019). Seismic absolute acoustic impedance inversion with L1 norm reflectivity constraint and combined first and second-order total variation regularizations. J Geophys Eng 16(4):773–788
[2] Mandal A, Ghosh SK. (2020) Estimating broad trend of acoustic impedance profile from observed seismic reflection data using first principles only. J Geophys Eng 17(3):475–483
[3] Das B, Chatterjee R.. (2017) Wellbore stability analysis and prediction of minimum mud weight for few wells in Krishna–Godavari Basin, India. Int J Rock Mech Min Sci 93:30–37
[4] Nakaten N, Schlüter R, Azzam R, Kempka T. (2014). Development of a techno-economic model for dynamic calculation of the cost of electricity, energy demand, and CO2 emissions of an integrated UCG–CCS process. Energy 66:779–790
[5] Chen, Q., and Sidney, S. (1997). Seismic Attribute Technology for Reservoir Forecasting and Monitoring. The Leading Edge, Vol. 16, P. 445–456.
[6] Han Y, Liu C, Phan D, AlRuwaili K, Abousleiman Y. (2019). Advanced wellbore stability analysis for drilling naturally fractured rocks. In: SPE middle east oil and gas show and conference. Society of Petroleum Engineers
[7] Bagheri H, Tanha AA, Doulati Ardejani F, Heydari-Tajareh M, Larki E. (2021).  Geomechanical model and wellbore stability analysis utilizing acoustic impedance and reflection coefficient in a carbonate reservoir. J Pet Explor Prod Technol 11(11):3935–3961
[8] Afsari, M., Ghafoori, M. R., et al. (2009). Mechanical Earth Model (MEM): An Effective Tool for Borehole Stability Analysis and Managed Pressure Drilling (Case Study). Presented at the SPE Middle East Oil & Gas Show and Conference, Bahrain.
[9] Akbar Ali, A. H., Brown, T., et al. (2003). Watching Rocks Change Mechanical Earth Modeling Oilfield Review. Vol. 15, P. 22-39.
[10] Radwan AE, Abdelghany WK, Elkhawaga MA. (2021). Present-day insitu stresses in Southern Gulf of Suez, Egypt: insights for stress rotation in an extensional rift basin. J Struct Geol 147:104334
[11] Pelletier H. (2009). AVO Cross plotting II: Examining Vp/Vs behavior: CSPG, CSEG, CWLS Convention, Calgary, Alberta, Canada, 105-110
[12] Kassem AA, Sen S, Radwan AE, Abdelghany WK, Abioui M. (2021). Effect of depletion and fluid injection in the Mesozoic and paleozoic sandstone reservoirs of the October oil field, central Gulf of Suez Basin: implications on drilling, production and reservoir stability. Nat Resour Res 30(3):2587–2606
[13] Kong L, Ostadhassan M, Zamiran S, Bo Liu, Chunxiao Li, Gennaro G. Marino. (2019). Geomechanical upscaling methods: comparison and verification via 3D printing. Energies 12(3):382
[14] Khoshnevis-zadeh R, Soleimani B, Larki E. (2019). Using drilling data to compare geomechanical parameters with porosity (a case study, South Pars gas field, south of Iran). Arab J Geosci 12(20):611
[15] Hoseinpour M., Riahi M.A. (2021).  Determination of the mud weight window, optimum drilling trajectory, and wellbore stability using geomechanical parameters in one of the Iranian hydrocarbon reservoirs. Journal of Petroleum Exploration and Production Technology, 12(13):1-20
[16] Shahbazi, K., Zarei, A.H., Shahbazi, A., Tanha, A.A. (2020). Investigation of production depletion rate effect on the near-wellbore stresses in the two Iranian southwest oilfields. Petrol. Res. 8, 231e243.
[17] Yang, J., Zong, J., Li, Y., Cheng, A. (2020). Application of Reverse Time Migration with Random Space Shift to Vertical Seismic Profiling (VSP) Data, 82nd EAGE Annual Conference & Exhibition. European Association of Geoscientists & Engineers, pp. 1e5.
[18] Rutqvist J., Moridis G.J., Grover T., Collett T. (2009). Geomechanical response of permafrost-associated hydrate deposits to depressurization-induced gas production. Journal of Petroleum Science and Engineering. Volume 67, Issues 1–2, Pages 1-12
[19] Das B, Chatterjee R. (2018). Mapping of pore pressure, in-situ stress, and brittleness in unconventional shale reservoir of Krishna-Godavari basin. J Natural Gas Sci Eng 50:74–89
[20] Wu, X., Willis, M.E., Palacios, W., Ellmauthaler, A., Barrios, O., Shaw, S., Quinn, D. (2017). Compressional and shear-wave studies of distributed acoustic sensing acquired vertical seismic profile data. Lead. Edge 36 (12), 987e993.
[21] Aki K, Richards PG. (1980). Quantitative seismology. Freeman, W. H. and Co San Francisco, p 557
[22] Goodway B. (2013). A tutorial on AVO and Lamé constants for rock parameterization and fluid detection. Geophysical Society of Alaska, http://gsa.seg.org/pdf_forms/RecorderJune2001LMRAVO_new2007july.pdf
[23] Sharma R, Chopra S.; 2012: New attribute for determination of lithology and brittleness. SEG Las Vegas Annual Meeting. Canada, P. 1-5
[24] Zoback MD (2010) Reservoir geomechanics. Cambridge University Press, Cambridge
[25] Ogbamikhumi, A. Igbinigie, N. S. (2020). Rock physics attribute analysis for hydrocarbon prospectivity in the Eva field onshore Niger Delta Basin. Journal of Petroleum Exploration and Production Technology, 10:3127–3138.
[26] Goodway W, Chen T, Downton J. (1997). Improved AVO fluid detection and lithology discrimination using lame petrophysical parameters. The society of exploration geophysicists; In: 67th annual international meeting, Denver.
[27] Ujuanbi, O., J.C. Okolie, and S.I. Jegede. (2008). Lambda-Mu-Rho techniques as a viable tool for litho-fluid discrimination- the Niger Delta example: International Journal of Physical Sciences, v. 2/7, p. 173-176.
[28] Coates, D.F., and R.C. Parsons. (1966). Experimental criteria Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, 3, 181-189, DOI:  10.1016/0148-9062 (66)90022-2.
[29] Perez, R. and Marfurt, K. (2013). “Brittleness estimation from seismic measurements in unconventional reservoirs: Application to the Barnett Shale”, ConocoPhillips School of Geology and Geophysics, The University of Oklahoma, SEG Houston  Annual Meeting. P. 2258-2263 
[30] Zhang, B. Zhao, T. Jin, X. and Marfur, K.J. (2015). Brittleness evaluation of resource plays by integrating petrophysical and seismic data analysis.  Society of Exploration Geophysicists and American Association of Petroleum Geologists Technical paper, Vol. 3, No. 2, P. T81–T92, 13 FIGS.
[31] Rickman, R., Mullen, M. J., Petre, J. E., Grieser, W. V., & Kundert, D. (2008). Practical use of shale petrophysics for stimulation design optimization: All shale plays are not clones of the Barnett Shale. In SPE annual technical conference and exhibition. OnePetro.
[32] Castagna JP, Swan HW. (1987). Principle of AVO crossposting, Lead Edge 12:337-343