USES OF THE GAMMA‐RAY SPECTROMETER IN MINERAL EXPLORATION

Gamma‐ray spectroscopy offers a rapid and reliable radiometric method of analysis of uranium and/or thorium ores. Methods of ore analysis are described and experimental results are presented. The uranium‐thorium ratios of rocks, which are important in strata recognition and correlation studies, can be determined directly by gamma‐ray spectroscopy without the necessity of making individual uranium or thorium assays. Analysis of potash ores is facilitated with a gamma‐ray spectrometer. Erratic behavior of gamma‐ray well logs can often be resolved by studying the gamma‐ray spectra of these logs. Neutron‐activation, followed by gamma‐ray spectral analysis, of common earth materials offers a method of borehole rock analysis for elements such as calcium, hydrogen, chlorine, sulphur and magnesium. Data in studies employing radioactive tracers can often be enhanced through use of a gamma‐ray spectrometer. Other present and potential applications of the gamma‐ray spectrometer in mineral exploration are also discussed.

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Calibration of a coincidence gamma-ray spectrometer for directional correlation studies

Nuclear Instruments and Methods ◽

10.1016/0029-554x(72)90427-2 ◽

1972 ◽

Vol 98 (1) ◽

pp. 77-85 ◽

Cited By ~ 5

Author(s):

P. Jagam ◽

D.S. Murty ◽

V. Lakshminarayana

Keyword(s):

Gamma Ray ◽

Correlation Studies ◽

Gamma Ray Spectrometer

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Statistical analysis of airborne gamma‐ray data for geologic mapping purposes: Crixas‐Itapaci area, Goias, Brazil

Geophysics ◽

10.1190/1.1442592 ◽

1989 ◽

Vol 54 (10) ◽

pp. 1326-1332 ◽

Cited By ~ 7

Author(s):

A. C. B. Pires ◽

N. Harthill

Keyword(s):

Statistical Analysis ◽

Gamma Ray ◽

Mineral Exploration ◽

Aerial Survey ◽

Geologic Mapping ◽

Good Correspondence ◽

Gamma Ray Spectrometer ◽

Data Points ◽

Spectrometer Data ◽

Mode Technique

Q‐mode factor analysis, K‐means clustering, and G‐mode clustering were used on digitized gamma‐ray spectrometer data from an aerial survey of the Crixas‐Itapaci area, Goias, Brazil. The data points including seven variables—eU, eTh, K, total count, U/Th, U/K, and Th/K—were digitized for a 2 km square grid. For the northwest corner of the area the data were gridded at 1 km. The Q‐mode classification method supplied results that do not show a good correspondence with the known geology. The K‐means clustering procedure barely identified the main lithologic features of the area. The G‐mode technique produced results that correlate well with the known geology and identified the greenstone belts present in the area by discriminating their ultramafic and mafic components from adjacent felsic rocks. Statistical analysis of aerial gamma‐ray spectrometer data can be very helpful in mapping geologic units in poorly known areas. It can also be used for mineral exploration purposes if mineralization is known to be associated with lithologies that can be identified by the techniques used in this study.

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