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Calculation of porosity from nuclear magnetic resonance and conventional logs in gas-bearing reservoirs

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Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The porosity may be overestimated or underestimated when calculated from conventional logs and also underestimated when derived from nuclear magnetic resonance (NMR) logs due to the effect of the lower hydrogen index of natural gas in gas-bearing sandstones. Proceeding from the basic principle of NMR log and the results obtained from a physical rock volume model constructed on the basis of interval transit time logs, a technique of calculating porosity by combining the NMR log with the conventional interval transit time log is proposed. For wells with the NMR log acquired from the MRIL-C tool, this technique is reliable for evaluating the effect of natural gas and obtaining accurate porosity in any borehole. In wells with NMR log acquired from the CMR-Plus tool and with collapsed borehole, the NMR porosity should be first corrected by using the deep lateral resistivity log. Two field examples of tight gas sandstones in the Xujiahe Formation, central Sichuan basin, Southwest China, illustrate that the porosity calculated by using this technique matches the core analyzed results very well. Another field example of conventional gas-bearing reservoir in the Ziniquanzi Formation, southern Junggar basin, Northwest China, verifies that this technique is usable not only in tight gas sandstones, but also in any gas-bearing reservoirs.
Czasopismo
Rocznik
Strony
1030--1042
Opis fizyczny
Bibliogr. 17 poz.
Twórcy
autor
autor
autor
autor
  • Key Laboratory of Geo-detection (China University of Geosciences, Beijing), Ministry of Education, Beijing, People’s Republic of China, nmrlogging@21cn.com
Bibliografia
  • Abushanab, M.M., G.M. Hamada, A.A. Abdelwally, and M.E. Oraby (2005), DMR technique improves tight gas porosity estimate, Oil Gas J. 103, 47, 54-59.
  • Archie, G.R. (1942), The electrical resistivity log as an aid in determining some reservoir characteristics, Trans. AIME, 146, 54-62.
  • Chu, Z.H., J. Gao, L.J. Huang, and L.Z. Xiao (2007), Principles and methods of geophysical logging (Part II), Petroleum Industry Pressure, Beijing, 224-326.
  • Clavier, C., G. Coates, and J. Dumanoir (1984), Theoretical and experimental bases for the dual-water model for interpretation of shaly sands, SPE J. 24, 2, 153-168, DOI: 10.2118/6859-PA.
  • Coates, G.R., L.Z. Xiao, and M.G. Prammer (2000), NMR Logging Principles and Applications, Gulf Publishing Company, Houston, 42-78.
  • Hamada, G.M., and M.A. Abushanab (2007), Better porosity estimate of gas sandstone reservoir using density and NMR logging data, SPE Conf. Paper 106627, DOI: 10.2118/106627-MS.
  • Kamel, M.H., and M.M. Mohamed (2006), Effective porosity determination in clean/shaly formations from acoustic logs with applications, J. Petrol. Sci. Eng. 51, 3, 267-274, 10.1016/j.petrol.2006.01.007.
  • Kamel, M.H., W.M. Mabrouk, and A.I. Bayoumi (2002), Porosity estimation Rusing a combination of Wyllie–Clemenceau equation in clean sand formation from acoustic logs, J. Petrol. Sci. Eng. 33, 4, 241-251, DOI: 10.1016/S0920-4105(01)00169-3.
  • Makar, K.H., and M.H. Kamel (2011), An approach for minimizing errors in computingeffective porosity in reservoir of shaly nature in view of Wyllie–Raymer–Raiga relationship, J. Petrol. Sci. Eng. 77, 3, 386-392, DOI:10.1016/jpetrol.2011.04.013.
  • Mao, Z.Q., C. Zhang, and L. Xiao (2010), A NMR-based porosity calculationmethod for low porosity and low permeability gas reservoir, Oil Geophys.Prospect. 45, 1, 105-109 (in Chinese).
  • Raiga-Clemenceau, J., J.P. Martine, and S. Nicoletis (1988), The concept of acousticformation factor for more accurate porosity determination from sonic transittime data, The Log Analyst. 29, 1, 54-60
  • Raymer, L.L., E.R. Hunt, and J.S. Gardner (1980), An improved sonic transit timeto-porosity transform, SPWLA 21st Annual Logging Symp., Conf. Paper 1980-P.
  • Waxman, M.H. (1974), Electrical conductivities in shaly Sands—I. The relation between hydrocarbon saturation and resistivity index; II. The temperature coefficient of electrical conductivity, J. Petrol. Technol. 26, 2, 213-225, DOI: 10.2118/4094-PA.
  • Waxman, M.H., and L.J.M. Smits (1968). Ionic double-layer conductivity in oilbearing shaly sands, SPE Formation Eval. 4, 1, 20-32.
  • Wyllie, M.R.J., A.R. Gregory, and L.W. Gardner (1956), Elastic wave velocities in heterogeneous and porous media, Geophysics. 21, 1, 41-70, DOI: 10.1190/1.1438217.
  • Xiao, L.Z. (1998), Magnetic Resonance Imaging Logging and Rock Nuclear Magnetic Resonance and its Application, Science Press, Beijing (in Chinese).
  • Yong, S.H., C.M. Zhang, and Z.Y. Liu (1996), Well Log Data Processing and Comprehensive Interpretation, China University of Petroleum Press, Dongyin (in Chinese).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSL1-0023-0021
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