Methodological and technical aspects of gamma-spectrometry using Geoscan 401 Gamma UAV system

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Methodological and technical aspects of gamma-spectrometry using Geoscan 401 Gamma UAV system
Methodological and technical aspects of gamma-spectrometry using Geoscan 401 Gamma UAV system

Gamma spectrometry (GS) has become one of the most important methods to address ore mapping and prospecting problems. GS is usually implemented in ground and aerial versions. In the first case, the area survey is performed over a long time, but it allows accumulating a larger number of pulses per point to reliably determine the specific activities (and concentrations) of uranium, thorium, potassium. In case of aerial survey, the productivity of works is an order of magnitude higher, but anomalies are essentially smoothed, and the error of definition of quantitative characteristics of natural sources of gamma-radiation grows. Combining the advantages of both methods is the newly developed gamma spectrometry method based on unmanned aerial vehicles, where imaging can be performed at low altitude and flight speed, with hovering if necessary (Balkov et al., 2019; Briechle et al., 2018; Danilov et al., 2015; Gachenko et al., 2020; Kremcheev et al., 2019; Peterson et al., 2019; Šálek, 2021, Tang et al., 2019).

The authors of this paper set the following objectives:

  • Evaluate the technical properties of a spectrometer that can be used for UAVs in a laboratory setting;
  • provide recommendations on gamma spectrometry methodology;
  • process field gamma spectrometry data obtained using Geoscan 401 Gamma UAV.

Methodology

The research is divided into 2 phases.

The first stage of the research was performed in laboratory conditions. The object of the study is a gamma spectrometer adapted for the Geoscan 401 Gamma system, equipped with a 0.4 L cylinder-shaped sodium scintillation detector; the survey data was recorded at 1 Hz interval.

A set of PCU (portable calibration units) corresponding to common rock profiles by the content of U, Th, K natural radionuclides, as well as additional samples with relatively high content of radioactive elements, including artificial ones (Figure 1), were used to verify the calibration of energy scale and to obtain conversion ratios of spectral parameters to the content of radioactive elements. Integral readings were compared with the data obtained using SRP-97 radiometer. The required measurement duration for obtaining the target error in determining the concentrations of natural radionuclides in rock is estimated.

In the second stage of research, the authors apply revised ratios in the processing of field data. The work shows the results of field works in an area that looks promising for hydrothermal gold-copper ores; aerial gamma spectrometry survey is conducted using Gamma unmanned aerial geophysical system. The site is located in the Trans-Baikal Territory. Geoscan 401 Gamma UAV system was used to perform the works. Its main properties are as follows: the copter flight duration without recharging – up to 45 minutes, flight speed – 0 - 50 km/h, maximum payload – 3.5 kg. The detector described in the first stage of the research was used as a sensor.

Results

The results of the first (laboratory) research phase can be presented in the form of individual conclusions:

1. The gamma-quantum energy and the channel number have a linear correlation, with a ratio close to 1 (1.0749 to be precise), which is convenient for interpreting the spectra. Based on the peaks identified, the dependence of gamma-quantum energy on the channel numbers was plotted.

2. According to the experimental work, some dependence between the spectrometer readings and the sensor position (vertical or horizontal) was observed. It was determined that 1 pulse per second corresponds to approximately 30 μR/h for the given spectrometer. The ratios for conversion from spectral parameters to percentages of radioactive elements were derived.

img1

Figure 1. General view of Geoscan 401 Gamma system, examples of registered spectra for samples containing cesium, cobalt, uranium, thorium, potassium in logarithmic and linear scales.

3. The duration of gamma spectrometer “hovering” required to achieve the specified accuracy in determining contents of uranium, thorium, potassium content was estimated. If the measurement time in seconds is denoted as T, the relative accuracy of measurements over time T can be defined as follows (Miller et al., 2020):

form1

where 𝛿К (𝑇) is the relative measurement error for potassium content for measurement time T, δ_К is the relative statistical measurement error, i. e. ratio of standard deviation to concentration value. According to the regulatory documents, permissible error values when measuring the percentage content of radioactive elements are defined as 0.2 % for potassium, 0.3 g/t for uranium and 0.5 g/t for thorium. The holding time (in seconds) required to collect the data is calculated based on the given relative accuracies for the radioactive elements:

form2

where TК is the time in seconds needed to achieve relative accuracy in determining the potassium content 𝛿К (𝑇). Similar dependencies (2) can be drawn for uranium and thorium. The resulting values are: 𝑇К = 2907 s, 𝑇𝑈 = 44100 s, 𝑇𝑇ℎ = 22500 s.

Traditionally, the error due to the statistical nature of measurements is set to 0.15. Based on this value, the measurement time for potassium, uranium, thorium is calculated according to (4) as follows: 𝑇𝐾 = 336 s, 𝑇𝑈 = 282 s, 𝑇𝑇ℎ = 361 s. That is, if we set the longest time for all elements, the minimum measurement time to obtain an acceptable statistical error of content measurement is 5 minutes.

The result of the second research stage is the maps characterizing the distribution of uranium, thorium, potassium over the research area (Figure 2). The authors did not task themselves with performing a detailed interpretation of the processing results and left this point for future research.

img2

Figure 2. Elevation map of the survey area with plotted flight lines and the count results (pulses per second) in the uranium, thorium, potassium windows, and the aggregate result in RGB-composition format.

Anomalous concentrations of radioactive elements or their anomalous ratios can be inherent in different mineral paragenesis (Alekseev, 2020; Ilalova et al., 2020; Veshev et al., 1996). The tendency for spacial isolation of paragenesis is never fully realized (Movchan, Yakovleva, 2019): each mineral association is superimposed on previous formations, which creates a mottled picture of the distribution of natural radioactive elements in ore deposits. The intensity of radiogeochemical anomalies in hydrothermal ore fields is relatively low. The ore fields of copper and gold deposits are characterized by confinement to areas of potassium and potassium-uranium radiogeochemical specialization (which corresponds to a combination of shades of yellow in the RGB-composition).

Conclusions

The materials obtained indicate the possibility of studying rather weak anomalies, not related to deposits of radioactive elements, by means of gamma spectrometry (GS) using drones in continuous flight mode. More accurate quantitative assessments of the content of naturally occurring radioactive elements are possible by performing measurements while hovering for up to 5 minutes and with partial verification (at individual points) of the resulting concentrations and ratios by the ground-based GS method. For the full calibration of equipment and comparison of different technological complexes of aerial gamma spectrometry, it is necessary to have an accredited testing range, the lack of which at the moment is acutely felt. Convenient and relatively cheap UAV-based GS technique opens up vast prospects for gamma spectrometry in the search for ore, oil and gas deposits, deposits of construction materials, in geological mapping and solving environmental problems.


Source: “Engineering and Ore Geophysics 2021” – Gelendzhik, Russia, April 26-30, 2021

E.YU. Ermolin (GM-Service Ltd.), D.A. Andriets* (St. Petersburg Mining University), N.P. Senchina (GM-Service Ltd.), A.A. Miller (St. Petersburg Mining University