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Year : 2018  |  Volume : 41  |  Issue : 1  |  Page : 42-46

Spectral gamma ray logging: A cost-effective method for uranium exploration

1 Department of Atomic Energy, Atomic Minerals Directorate for Exploration and Research, Bengaluru, Karnataka, India
2 Department of Atomic Energy, Atomic Minerals Directorate for Exploration and Research, Hyderabad, Telangana, India

Correspondence Address:
G Jegannathan
Department of Atomic Energy, Atomic Minerals Directorate for Exploration and Research, Bengaluru, Karnataka
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/rpe.RPE_17_18

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The most useful technique in uranium exploration program is undoubtedly radiometric surveys. This is due to the fact that uranium emits gamma rays ranging from as low as 47kev to 2.2Mev, which can be detected and quantified using suitable radiation detector. Combination of aerial radiometric surveys, ground examination of the detected anomalies, followed by drilling and gamma ray logging of drilled boreholes has resulted in the identification of large uranium resources. Borehole logging provides the most important subsurface information required for the uranium exploration program. An area known to contain only uranium, computed gamma ray logging with a Geiger Muller (GM) Detector rapidly gives the required subsurface radioactivity information whereas, in a heterogeneously mineralized area of uranium with thorium, logging data using GM detector may mislead to wrong interpretation. Under such condition, using the principle of gamma ray spectrometry, scintillation detector-based spectral gamma ray logging is carried out. Identifying uranium in the presence of thorium is a complex process and this paper deals with a case study on the spectral gamma ray logging carried out to locate the subsurface uraniferous zone in Pakkanadu area, Salem district of Tamil nadu, where the surface anomaly indicated the presence of high thorium content. The various limitations such as small detector size, large sample volume, high-correction factor required for quantifying the individual elements, and the study carried out for optimizing the time required for data acquisition are discussed.

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