The low-energy region of the gamma ray spectrum, less than 200 keV, often is either discarded or not analyzed in borehole logging or airborne radiometric surveys. There is much useful information about earth properties to be extracted from the low-energy region because it is sensitive to photoelectric absorption within the rock, a process that is highly sensitive to the atomic number of the elements within the rock. In addition, the rate of photoelectric absorption is proportional to the density of the rock. At higher energies, the spectrum is primarily sensitive to density variations only. The ratio of counts in the two energy regions may be used as a heavy mineral indicator (HMI). This ratio normalizes density effects and is primarily sensitive to variations in the average (or effective) atomic number (Zeff) of the rock. Previous work by other authors has focused on the application of this idea for wireline logging with an isotopic source and multiple scattering of copious primary gamma rays, which allows for good counting statistics in the recorded spectrum. Recent advances in gamma ray detectors and logging-while-drilling (LWD) techniques open the possibility of applying the HMI measurement to the natural gamma ray LWD logs. Drilling speeds are much slower than the running speeds of wireline tools, resulting in improved counting statistics. Using computer simulations, laboratory experiments, and field measurements, we find that the natural gamma ray spectrum, recorded while (diamond) drilling, provides sufficient counting statistics to be used for robustly calculating HMI. As iron is the most abundant and influential element in photoelectric gamma ray scattering processes in rock fabrics, we postulate that we can, in most cases, use HMI to indicate the iron content of the rocks. The HMI calculated under these conditions provides a good measure of changes in Zeff of rocks and correlates well with iron-rich sections. Our field and laboratory tests demonstrate that the HMI measures can be used as a proxy to separate many metalliferous ores from waste based on the differences in Zeff.

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