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Because of the effects of background and measurement environment and multiplet effects of different elements, high-precision analysis of mixed capture γ-ray energy spectra of complicated formations remains challenging for geochemical elemental logging. The direct demodulation (DD) method makes full use of the measured data information, enabling physical constraints to be rationally applied to the spectral analysis process, and can yield high-precision elemental content from poor-statistics, low signal-to-noise ratio, and disturbed data. We construct mixed formations of different sandstones and limestones, mixed formations of sandstone and anhydrite, and more complicated mixed formations of multiple lithologies and employ Monte Carlo numerical simulations to obtain the neutron-capture γ-ray energy spectra of these mixed formations. We then employ the DD method and the weighted-least-squares (WLS) method to analyze quantitatively such mixed spectra, respectively, and compare the results with the actual contents of formation elements. The results indicate that the DD method offers higher precision spectral analysis compared with the results of the WLS method. The results for the capture γ-ray energy spectra of the formation for two actual wells also indicate that the DD method can be useful for spectral analysis in actual application.


  • Chapman, S., J. L. Colson, and C. Flaumet al., 1987, The emergence of geochemical well logging: Technical review, 35, no. 2, 27–35.TRMHA30026-6817Google Scholar
  • Ellis, D. V., and J. M. Singer, 2007, Well loggings for earth scientists: Elsevier.CrossrefGoogle Scholar
  • Gadeken, L. L., D. M. Arnold, and H. D. SmithJr., 1984, Applications of the compensated spectral natural gamma tool: 25th Annual Logging Symposium Transactions: Society of Professional Well Log Analysts, Paper JJJ, 1–19.Google Scholar
  • Gartner, M. L., and L. A. Jacobson, 1990, Detector design and data processing effects on elemental yield variance: 13th European Formation Evaluation Symposium Transactions: Society of Professional Well Log Analysts, Paper CC, 1–10.Google Scholar
  • Grau, J. A., and J. S. Schweitzer, 1987, Prompt γ-ray spectral analysis of well data obtained with NaI (Tl) and 14 MeV neutrons: Nuclear Geophysics, 1, 157–165.Google Scholar
  • Grau, J. A., and J. S. Schweitzer, 1989, Elemental concentrations from thermal neutron capture gamma-ray spectra: Nuclear Geophysics, 3, 1–9.Google Scholar
  • Heath, R. L., 1966, Computer techniques for the analysis of gamma-ray spectra obtained with NaI and lithium-ion drifted germanium detectors: Nuclear Instruments and Methods, 43, 1, 209–229.NUIMAL0029-554XCrossrefGoogle Scholar
  • Helmer, R. J., R. L. Heath, and L. A. Schmittrothet al., 1967, Analysis of gamma-ray spectra from NaI(Tl) and Ge(Li) spectrometers. Computer programs: Nuclear Instruments and Methods, 47, no. 2, 305–319, doi: 10.1016/0029-554X(67)90445-4.NUIMAL0029-554XCrossrefWeb of ScienceGoogle Scholar
  • Herron, M. M., 1986, Mineralogy from geochemical well logging: Clays and Clay Minerals, 34, no. 2, 204–213, doi: 10.1346/CCMN.1986.0340211.CLCMAB0009-8604CrossrefWeb of ScienceGoogle Scholar
  • Hertzog, R., 1980, Laboratory and field evaluation of an inelastic neutron scattering and capture gamma ray spectrometry 1001: Society of Petroleum Engineers Journal, 20, no. 5, 327–340, doi: 10.2118/7430-PA.SPTJAJ0037-9999CrossrefGoogle Scholar
  • Hertzog, R., L. Colson, and O. Seemanet al., 1989, Geochemical logging with spectrometry tools: SPE formation evaluation : an official publication of the Society of Petroleum Engineers, 4, no. 2, 153–162, SPE16792, doi: 10.2118/16792-PA.SFEVEG0885-923XCrossrefGoogle Scholar
  • Islavić, I. A., and S. P. Bingulac, 1970, A simple method for full automatic gamma-ray spectra analysis: Nuclear Instruments and Methods, 84, 2, 261–268, doi: 10.1016/0029-554X(70)90270-3.NUIMAL0029-554XCrossrefWeb of ScienceGoogle Scholar
  • Li, T. P., and M. Wu, 1993, The direct method for spectral and image restoration in high energy astronomy: Acta Astrophysica Sinica, 13, 3, 215–224.TWXUDX0253-2379Google Scholar
  • Li, T. P., and M. Wu, 1994, Reconstruction of objects by direct demodulation: Astrophysics and Space Science, 215, 213–227, doi: 10.1007/BF00660079.APSSBE0004-640XCrossrefWeb of ScienceGoogle Scholar
  • Najafi, S. I., and M. Fedoroff, 1985, Accurate gamma ray spectrum analysis: Journal of Radioanalytical and Nuclear Chemistry, 89, 1, 143–152, doi: 10.1007/BF02070211.JRNCDM0236-5731CrossrefWeb of ScienceGoogle Scholar
  • Pang, J. F., 1991, γ-ray spectrum data analysis: Shanxi Science & Technology Press, Xi’an: 50–150.Google Scholar
  • Pelowitz, D. B., ed., 2008. MCNPX user’s manual, version 2.6.0, LA-CP-07-1473, Los Alamos National Laboratory, Los Alamos, New Mexico.Google Scholar
  • Schweitzer, J. S., 1991, Nuclear techniques in the oil industry: Nuclear Geophysics, 5, 1/2, 65.Google Scholar
  • Westaway, P., R. Hertzog, and R. E. Plasek, 1983, Neutron-induced gamma ray spectroscopy for reservoir analysis: SPE Journal, 23, 553–564.SPEJAC0036-1844Google Scholar
  • Zhang, S., T. P. Li, and M. Wu, 1997, Image analyses of Compton data using a direct demodulation method: Acta Astrophysica Sinica, 17, no. 3, 263–270.TWXUDX0253-2379Google Scholar