Estimation of Permeability from NMR Logs Based on Formation Classification Method in Tight Gas Sands

• Autorzy: Wei D.- F. , Liu X.-P. , Hu X.-X. , Xu R. , Zhu L.-L.

Identyfikatory

DOI

10.1515/acgeo-2015-0042

• Języki publikacji: EN

Abstrakty

EN

The Schlumberger Doll Research (SDR) model and cross plot of porosity versus permeability cannot be directly used in tight gas sands. In this study, the HFU approach is introduced to classify rocks, and determine the involved parameters in the SDR model. Based on the difference of FZI, 87 core samples, drilled from tight gas sandstones reservoirs of E basin in northwest China and applied for laboratory NMR measurements, were classified into three types, and the involved parameters in the SDR model are calibrated separately. Meanwhile, relationships of porosity versus permeability are also established. The statistical model is used to calculate consecutive FZI from conventional logs. Field examples illustrate that the calibrated SDR models are applicable in permeability estimation; models established from routine core analyzed results are effective in reservoirs with permeability lower than 0.3 mD, while the unified SDR model is only valid in reservoirs with permeability ranges from 0.1 to 0.3 mD.

Słowa kluczowe

EN

tight gas sandstones; permeability; formation classification method; SDR model; nuclear magnetic resonance (NMR) log

PL

piaskowce; przepuszczalność; klasyfikacja; model SDR; magnetyczny rezonans jądrowy

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2015
• Tom: Vol. 63, no. 5
• Strony: 1316--1338
• Opis fizyczny: Bibliogr. 26 poz., rys., tab., wykr.

Twórcy

autor

Wei D.- F.

• School of Graduate Student, College of Resources and Environment, Southwest Petroleum University, Sichuan, PR China

autor

Liu X.-P.

• Geological Exploration and Development Research Institute, Sichuan-Changqing Drilling and Exploration Engineering Corporation, CNPC, Sichuan, PR China

autor

Hu X.-X.

• Geological Exploration and Development Research Institute, Sichuan-Changqing Drilling and Exploration Engineering Corporation, CNPC, Sichuan, PR China

autor

Xu R.

• Tuha Division of CNPC Well Logging Company Ltd., Xinjiang, PR China

autor

Zhu L.-L.

• Tuha Division of CNPC Well Logging Company Ltd., Xinjiang, PR China

Bibliografia

• [1] Abbaszadeh, M., H. Fujii, and F. Fujimoto (1996), Permeability prediction by hydraulic flow units - theory and applications, SPE Formation Eval. 11, 4, 263-271, DOI: 10.2118/30158-PA.
• [2] Coates, G.R., L.Z. Xiao, and M.G. Prammer (1999), NMR Logging - Principles and Applications, Gulf Publ. Co., Houston, 256 pp.
• [3] D’Windt, A. (2007), Reservoir zonation and permeability estimation: A Bayesian approach. In: Proc. 48th SPWLA Annual Logging Symposium, 3-6 June 2007, Austin, USA, paper UUU.
• [4] Delli, M.L., and J.L.H. Grozic (2013), Prediction performance of permeability models in gas-hydrate-bearing sands, SPE J. 18, 2, 274-284, DOI: 10.2118/ 149508-PA.
• [5] Deng, J.M., X.X. Hu, X.P. Liu, and X.M. Wu (2013), Estimation of porosity and permeability from conventional logs in tight sandstone reservoirs of north Ordos basin. In: SPE Unconventional Gas Conference and Exhibition, 28-30 January 2013, Muscat, Oman, SPE163953, DOI: 10.2118/163953-MS.
• [6] Dunn, K.-J., D.J. Bergman, and G.A. Latorraca (2002), Nuclear Magnetic Resonance: Petrophysical And Logging Applications, Handbook of Geophysical Exploration, Vol. 32, Pergamon, New York, 176 pp.
• [7] Gao, J.B., L.T. Sun, and C.R. Wang (1991), Development of a transient pulse permeameter for tight rocks, Chin. J. Sci. Instr. 12, 4, 365-371 (in Chinese).
• [8] Haghighi, M.B.P., M. Shabaninejad, and K. Afsari (2011), A permeability predictive model based on hydraulic flow unit for one of Iranian carbonate tight gas reservoir. In: SPE Middle East Unconventional Gas Conference and Exhibition, 31 January - 2 February 2011, Muscat, Oman, SPE 142183, DOI: 10.2118/142183-MS.
• [9] Hearn, C.L., W.J. Ebanks Jr., R.S. Tye, and V. Ranganathan (1984), Geological factors influencing reservoir performance of the Hartzog Draw field, Wyoming, J. Petrol. Technol. 36, 8, 1335-1347, DOI: 10.2118/12016-PA.
• [10] Hulea, I.N. (2013), Capillary pressure and permeability prediction in carbonate rocks - New methods for fractures detection and accurate matrix properties prediction. In: SPE Middle East Oil and Gas Show and Conference, 10-13 March 2013, Manama, Bahrain, SPE164251, DOI: 10.2118/164251-MS.
• [11] Hulea, I.N., and C.A. Nicholls (2012), Carbonate rock characterization and modeling: Capillary pressure and permeability in multimodal rocks - A look beyond sample specific heterogeneity, AAPG Bull. 96, 9, 1627-1642, DOI: 10.1306/02071211124.
• [12] Kenyon, W.E. (1997), Petrophysical principles of applications of NMR logging, The Log Analyst 38, 2, 21-43.
• [13] Kenyon, W.E., P.I. Day, C. Straley, and J.F. Willemsen (1988), A three-part study of NMR longitudinal relaxation properties of water-saturated sandstones, SPE Formation Eval. 3, 3, 622-636, DOI: 10.2118/15643-PA.
• [14] Lucia, F.J. (1995), Rock-fabric/petrophysical classification of carbonate pore space for reservoir characterization, AAPG Bull. 79, 9, 1275-1300.
• [15] Mao, Z.Q., Z.N. Wang, Y. Jin, W.N. Zhou, X.G. Liu, and B. Xie (2008), Study on petrophysical foundation, methodology and techniques of logging reservoir evaluation for Upper Triassic Xujiahe Formation in Sichuan Basin, Well Log. Technol. 31, 3, 203-206.
• [16] Mao, Z.Q., L. Xiao, Z.N. Wang, Y. Jin, X.G. Liu, and B. Xie (2013), Estimation of permeability by integrating nuclear magnetic resonance (NMR) logs with mercury injection capillary pressure (MICP) data in tight gas sands, Appl. Magn. Reson. 44, 4, 449-468, DOI: 10.1007/s00723-012-0384-z.
• [17] Morriss, C., D. Rossini, C. Straley, P. Tutunjian, and H. Vinegar (1997), Core analysis by low-field NMR, The Log Analyst 38, 2, 84-94.
• [18] Rezaee, R., A. Saeedi, and B. Clennell (2012), Tight gas sands permeability estimation from mercury injection capillary pressure and nuclear magnetic resonance data, J. Petrol. Sci. Eng. 88-89, 92-99, DOI: 10.1016/j.petrol.2011.12.014.
• [19] Salah, A. (2012), The impact of pore geometry aspects on porosity-permeability relationship - a critical review to evaluate NMR estimated permeability. In: North Africa Technical Conference and Exhibition 2012, 20-22 February 2012, Cairo, Egypt, 808-818, SPE150887, DOI: 10.2118/150887-MS.
• [20] Tiab, D., D.M. Marschall, and M.H. Altunbay (1993), Method for identifying and characterizing hydraulic units of saturated porous media: tri-kappa zoning process, U.S. Patent No. 5193059 A.
• [21] Xiao, L., Z.Q. Mao, and Y. Jin (2012a), Calculation of irreducible water saturation (Swirr) from NMR logs in tight gas sands, Appl. Magn. Reson. 42, 1, 113-125, DOI: 10.1007/s00723-011-0273-x.
• [22] Xiao, L., Z.Q. Mao, G.R. Li, and Y. Jin (2012b), Calculation of porosity from nuclear magnetic resonance and conventional logs in gas-bearing reservoirs, Acta Geophys. 60, 4, 1030-1042, DOI: 10.2478/s11600-012-0015-y.
• [23] Xiao, L., Z.Q. Mao, Z.N. Wang, and Y. Jin (2012c), Application of NMR logs in tight gas reservoirs for formation evaluation: A case study of Sichuan basin in China, J. Petrol. Sci. Eng. 81, 182-195, DOI: 10.1016/j.petrol.2011.12.025.
• [24] Xiao, L., X.P. Liu, C.C. Zou, X.X. Hu, Z.Q. Mao, Y.J. Shi, H.P. Guo, and G.R. Li (2014), Comparative study of models for predicting permeability from nuclear magnetic resonance (NMR) logs in two Chinese tight sandstone reservoirs, Acta Geophys. 62, 1, 116-141, DOI: 10.2478/s11600-013-0165-6.
• [25] Xiao, Z.X., and L. Xiao (2008), Method to calculate reservoir permeability using nuclear magnetic resonance logging and capillary pressure data, Atom. Ener. Sci. Technol. 42, 10, 868-971 (in Chinese).
• [26 Yang, M.S. (2001), Study of optimal work condition about instantaneous-pulse permeability test equipment, J. Southwest Petrol. Inst. 23, 1, 46-48 (in Chinese).