Airborne Gamma-ray Spectrometry Data Research Articles

A deep neural network for predicting soil texture using airborne radiometric data

The ternary nature of soil texture, defined by its proportions of clay, silt, and sand, makes it challenging to predict through linear regression models from other soil attributes and auxiliary variables. The most promising results in this field have been recently achieved by Machine Learning methods which are able to derive non-linear, non-site-specific models to predict soil texture. In this paper we present a method of constructing a pair of Deep Neural Network (DNN) algorithms that can predict clay and sand soil contents from Airborne Gamma Ray Spectrometry data of K and Th ground abundances.We tested the algorithm's hyperparameters through various configurations to optimize the DNNs' performance, effectively avoiding underfitting and overfitting of the models. This led to the creation of a high-resolution 20 m × 20 m soil texture map from dense AGRS data, significantly refining the previous map's granularity. The application of the obtained DNN models to unseen sites can be supported by future training on additional textural classes.

Inference of minerals at Redondão kimberlite crater, Parnaíba Basin, Brazil, based on interpretation of airborne gamma-ray spectrometry and ASTER data

Inference of minerals at Redondão kimberlite crater, Parnaíba Basin, Brazil, based on interpretation of airborne gamma-ray spectrometry and ASTER data

Mapping bauxite-associated alterations in the Boke region (NW part of Republic of Guinea), using the airborne gamma-ray spectrometry data

Mapping of highly altered zones favorable to mineralization is crucial to finding useful mineral deposits. However, several methods have been used to locate areas subject to weathering processes, including analysis of airborne gamma-ray spectrometry data, which have demonstrated accurate and reliable results. In order to target other promising areas, and ensure the sustainability of bauxite mining, gamma-ray spectrometry was carried out and applied for the first time in the Boke region, located in the north–west of the Republic of Guinea which encompassing the world's famous bauxite district. The results obtained from the K/eU, K/eTh ratios, the F parameter and the potassium map were processed by the fuzzy logic model using ArcGIS software, the model can be used to merge the resulting informative maps into a single mineral prospectivity map, serving as a guide for mineral exploration. Three zones of high mineral prospectivity have been identified, essentially the Ordovician formations at Pita, the Silurian at Telimele and the Devonian at Faro. According to these preliminary prospecting results, the delineated areas contain localities that are probably potential, giving the green light for more advanced prospecting.

Radiometric characteristics of some metallic ores and nonmetallic deposits: an example, Wadi Al-Allaqi, South Eastern Desert, Egypt

Hydrothermal alteration processes are connected to many mineral formations, particularly auriferous deposits. In this study, airborne gamma-ray spectrometry (GRS) data and the analysis of radioactive materials (eU, eTh, and K) are applied to search for regions with hydrothermal alteration activity. An example is presented from Wadi Al-Allaqi, South Eastern Desert, Egypt. GRS was used to analyse various radiometric data to address potential mineral deposit areas, to map regions potentially showing metallic ore mineralisation, and to point out new geological mineral resources. The Kd (potassium deviation), “F” parameter and Th-normalisation of the K and eU anomalies were calculated, and locating new exploratory targets in the study area that exhibit high F-parameter, Kd, and K/eTh values was recommended. Additionally, the research region has a few isolated enriched spots of (K). Therefore, GRS data was used to characterise and estimate potential metallic ores, nonmetallic deposits, and gold ore zones associated with the alteration zones. Results show that most of the known mineral deposits and gold occurrences in the area, according to the metallogenic map of Egypt, are located in zones with a ratio value of (0.25–0.30) (K%/(U or Th ppm)) maps which may suggest a moderate degree of alteration. Also, most mineral deposits and gold occurrences are found in intermediate altered zones, or K-enriched sites, with a Kd% of (0.2. The work represents an attempt to map hydrothermal alteration zones associated with mineral deposits in the Wadi Al-Allaqi area. Generally, natural radiation characteristics and attributes suggest criteria that can be used globally for regional mineral exploration.

Application of High-Resolution Aeromagnetic and Gamma-ray Spectrometry Surveys for Litho-Structural Mapping in Southwest China

Airborne geophysical surveys serve as an effective tool for litho-structural mapping, providing extensive and high-resolution underground information. They offer vital data support for the interpretation and analysis of lithologies and structures, complementing surface geological mapping. In the study area of the Nanpanjiang-Youjiang metallogenic belt in southeast China, we obtained high-resolution aeromagnetic and gamma-ray spectrometry data covering an area of approximately 27,000 km2, which facilitated the conduct of litho-structural mapping. The total magnetic intensity, reduction to the pole, and directional derivative maps generated from the aeromagnetic data, efficiently identified concealed rocks and faults. Additionally, the total count, potassium, thorium to potassium ratio, and ternary maps generated from the airborne gamma-ray spectrometry data demonstrated advantages in distinguishing carbonate rocks from clastic rocks. They also provided more comprehensive geological information, refining the structural strike and location interpreted by the aeromagnetic data. The litho-structural map produced in this study significantly contributes to our understanding of the structures in the Nanpanjiang area and offers valuable guidance for successful mineral exploration endeavors.

Decomposing and recovering airborne radiometric data through principal component analysis applied on flight-line data: An alternative to reduce noise

Airborne gamma-ray spectrometry (AGRS) data provide valuable information about the distribution of radiometric elements on earth’s surface. However, the presence of noise can hinder the interpretation or the identification of subtle variations of radioelement concentrations that can be economically attractive. Previous research has demonstrated that techniques based on matrix factorization, such as noise-adjusted singular value decomposition (NASDV) and minima noise fraction (MNF), can reduce noise when applied to AGRS raw spectra. Nevertheless, the raw spectra often are unavailable for end users, limiting the widespread adoption of such techniques. In this context, we use principal component analysis with the flight-line data before interpolating the data onto a regular grid as a means to reduce noise when the raw spectra are no longer available. We use our approach on two AGRS data sets located in Brazil and one in the United States. For Brazil’s AGRS data, results indicate that noise can be attenuated through eigendecomposition projection and recovery of the radiometric variables. Furthermore, our technique can highlight some geologic features dependent on the number of eigenvectors used to reconstruct the database. For the U.S. AGRS data set previously filtered with NASDV, our methodology seems to produce only marginal improvement. Therefore, our methodology might be particularly successful for AGRS data whose acquisitions were conducted before NASDV and MNF were proposed as radiometric data processing techniques.

Clustering airborne gamma-ray spectrometry data in Nova Friburgo, State of Rio de Janeiro, southeastern Brazil

The goal of this study was to test different image clustering techniques, using airborne gamma-ray spectrometry data to optimize the interpretation of areas with similar properties in large scale. The methodology applied was based on the comparison of two techniques of data-driven classification (K-means and Gaussian Mixture Models) and a technique of knowledge-driven classification (Simplified RGB) to discriminate domains from the primary variables potassium (K), uranium (eU), and thorium (eTh) obtained from airborne gamma-ray spectrometry surveys. The performance of these three methods was evaluated through pre-processing techniques and post-processing including the best number of clusters/classes, visual interpretation, internal validation, and boxplot analysis. The clustering performance was considered satisfactory through the visual interpretation and comparison with the geological map and the DEM, for all three methods. For a quantitative analysis, the simplest model of unsupervised clustering Gaussian Mixture Models prevailed.

Using of airborne gamma-ray spectrometric data to the exposure of potassic alteration -recognition of alteration relates to gold mineralization

It is well known that many mineral deposits are related to hydrothermal processes, especially auriferous deposits. In this research paper, we show how to distinguish areas that have experienced hydrothermal activity, by construing airborne gamma-ray spectrometry data, especially potassium. An indirect application of aerial gamma-ray spectrometry technique is used to detect possible minerals deposits.In this region, an airborne gamma ray survey (K, eU and eTh) was carried out, based on irregular K, “F” parameter -, and Th-normalized of the K and eU anomalies. This work exhibits the mapping of hydrothermal regions possibly showing gold mineralization and the pointing out of new geological portions for this sequence, establishing prospective criteria for regional mineral exploration.We can suggest a new exploratory target, the area that is located next to Jabal Al-Ardiya (white colour on ternary map), which is characterized by high values of F-parameter, KD%, and K/eTh. Besides, enriched areas are found scattered in the north-eastern side of the study area. As result, the airborne gamma ray spectromertic data, might be used for estimation of prospective Gold Ore zones associated with the potassium alteration."

Analysis of airborne magnetic and gamma-ray spectrometry data for the geothermal source and conduits of the Ikogosi warm spring, southwestern Nigeria

Analysis of airborne magnetic and gamma-ray spectrometry data for the geothermal source and conduits of the Ikogosi warm spring, southwestern Nigeria

Mapping of Hydrothermal Alteration Zones in the Kelâat M’Gouna Region Using Airborne Gamma-Ray Spectrometry and Remote Sensing Data: Mining Implications (Eastern Anti-Atlas, Morocco)

The mapping of hydrothermal alteration zones associated with mineralization is of paramount importance in searching for metal deposits. For this purpose, targeting alteration zones by analyzing airborne geophysical and satellite imagery provides accurate and reliable results. In the Kelâat M’Gouna inlier, located in the Saghro Massif of the Moroccan Anti Atlas, natural gamma-ray spectrometry and ASTER satellite data were used to map hydrothermal alteration zones. Natural gamma-ray spectrometry data were processed to produce maps of Potassium (K in %), Uranium (eU in ppm), Thorium (eTh in ppm) and ratios of K/eTh and K/eU. In addition, four-band ratios were computed, on ASTER data, to map the distribution of clay minerals, phyllitic minerals, propylitic minerals, and iron oxides. The combined results obtained from geophysical and satellite data were further exploited by fuzzy logic modelling using the Geographic Information System (GIS) to generate a mineral prospectivity map. Seven hydrothermal alteration zones likely to be favorable for mineralization have been identified. They show a spatial correlation with (i) known surface prospects and mineral occurrences, (ii) the granite-encasing contact zone, and (iii) the fault zones (Sidi Flah and Tagmout faults). This research therefore provides important information on the prospecting of mineral potential in the study area.

Detection of Uranium Anomalies and Alteration Zones Using Airborne Gamma-Ray Spectrometry at Gabal Attala and Its Surrounding Area, Eastern Desert, Egypt

Gamma-ray spectrometry method is widely used in various fields. The study area is located in the Central Eastern Desert of Egypt and covers about 1200 square kilometers. The rock units in the study area can be organized in ages from the Precambrian (mainly granite) to Quaternary. Airborne gamma-ray spectrometry data were collected by Aero-Service, 1984. The main objectives of this study are to detect hydrothermal alteration zones and the uranium anomalies in the study area. The processing of the data was conducted to generate radioactive element concentration maps (K, eU and eTh). Hydrothermal alteration zones such as potassic and phyllic altered areas were detected using the Potassium Ternary Composite Image map and the eTh/K map. The F-parameter technique and K ideal method were used to determine the locations of the potassium-enrichment. These locations are characteristically associated with the orogenic gold mineralization in the study area. Fourteen radioactivity zones were classified based on the Interpreted Radio-Spectrometric Zonation (IRSZ) Map. These zones were divided into high, medium and low radioactive response where zones of high radioactive response were revealed as zones 1, 6, 9 and 13. Uranium anomalies have been identified as these anomalies are abundant in eU values and also associated with higher values of eU/eTh and eU/K, where the maximum value of eU is associated with the Younger Granite with a value of 18.831 ppm. These uranium anomalies are associated with Taref Formation, Post-Hammamat felsite, Quaternary deposits and Younger Granite. The locations of uranium anomalies are considered important exploration targets, as these locations are promising and have priority for ground geophysical and geological follow-up.

Boolean and fuzzy logic operators and multivariate linear regression applied to airborne gamma-ray spectrometry data for regolith mapping in granite-greenstone terrain in Midwest Brazil

Recent studies have proposed several possibilities of combining K, Th and U airborne gamma-ray spectrometry channels to generate predictive algorithms maps. These algorithms can be used for mapping regolith in deeply weathered terrains with residual, erosion, and deposition surfaces helping to developed strategies to better understand the regolith landscape and to improve geomorphology interpretation, and to identify mineral exploration target sites for primary (bedrock or saprolite) or supergene (hosted in lateritic duricrust) ore deposits. With the goal to easily map the regolith, two mathematical procedures were used on airborne gamma-ray spectrometry data in GIS software, validated by fieldwork on granite-greenstone belts in Midwest Brazil: 1. airborne gamma-ray spectrometry and altimetric data integrated in Boolean and fuzzy logic allowed segregating the areas with ferruginous and manganese residual lateritic duricrusts from erosional surface with rocks and saprolite with 90% of accuracy (κBoolean = 0.69 and κFAPO = 0.66) and 2. airborne gamma-ray spectrometry and altimetric data integrated with weathering stages in multivariate linear regression (basic statistic) helped establish the regional weathering intensity index, with acceptable error (r2 adjusted >0.6 and p-value < 5%). These two modeling techniques provide useful, accurate, rapidly and complementary regolith maps and can be applied in large regions for preliminary interpretations.

Effects of environmental factors on the monitoring of environmental radioactivity by airborne gamma-ray spectrometry

This study describes and discusses the results of a 14 month-long campaign (April 2019 to June 2020) aimed at characterizing and quantifying the influence of environmental factors (cosmic rays, rainfall events, soil moisture and atmospheric radon) on airborne radiometric surveys, which are used for mapping the concentrations of potassium (K), uranium (U) and thorium (Th), or for monitoring the natural radioactivity in the environment. A large NaI(Tl) airborne spectrometer (4 down + 1 up detectors of 4 L) was installed at a height of 50 m on a meteorological tower to simulate an airborne hover at the Pyrenean Platform for Observation of the Atmosphere (P2OA) in Lannemezan. The continuous, high frequency acquisition of gamma-rays was accompanied by measurements of rainfall intensity, soil moisture content, atmospheric radon activity and meteorological parameters. A semi-diurnal cycle of apparent 232Th and 40K was observed and explained by atmospheric thermal tides. Both diurnal and seasonal cycles are also evident in the gamma-ray signal, mostly due to variations of soil moisture at these timescales with a maximum during summer when surface soil moisture (0–5 cm depth) is the lowest. An increase of 25% vol. of the soil moisture content, representing the range of variation between the end of summer (18% vol.) and the beginning of spring (43% vol.) leads to a decrease of gamma-rays in the K and Th window by the same amount. Conversely, these results illustrate the potential of using airborne gamma-ray spectrometry to monitor soil moisture at hectometer scales. The washout of radon-222 progeny during rainfall events influences the count of gamma-rays in the U window by adding an atmospheric component to the soil component. The amplitude of the signal increase in the U window varies with the precipitation rate and reaches 30% for an average event. By clear weather, atmospheric radon-222 volumic activity influences the count rate in the U window by about ±3.8% per Bq m−3, which translates into an influence of 148%/Bq m−3/kg Bq−1 (U). This comprehensive, multi-compartment approach is necessary to optimize and improve the processing and analysis of airborne gamma-ray spectrometry data for high sensitivity environmental studies. These results show the importance of environmental factors on the variability of gamma-ray spectrometry and the importance of taking them into account to accurately map radionuclides activities.

Interpretation of aerospectrometric, aeromagnetic and geochemical data, Um-Alhuweitat basin area, Central Eastern Desert, Egypt

This study presents the analysis of airborne gamma-ray spectrometry and aeromagnetic data to delineate the distribution of the radioactive elements and determine their anomalous zones, subsurface structures controlled mineralized zones, and 3D magnetic inversion to give a full view of basement relief. According to statistical treatment of airborne gamma-ray spectrometry measurements, the highest values of potassium and equivalent thorium associated with Nakhiel Formation are 3.2% and 12.8 ppm respectively. Meanwhile, the equivalent uranium associated with phosphate beds attains 19.1 ppm. The spatial distribution of the relatively high concentrations of eU, eU/K and eU/eTh are recorded in adjacent areas in Upper Cretaceous deposits as > 12, 25 ppm and 5 ppm for eU, eU/K and eU/eTh, respectively.According to field measurements, the highest values of eU associated with phosphate beds and black Shale are 117 ppm and 20 ppm respectively. Meanwhile, the highest value of potassium associated with Quaternary sediments is 2.9%. Moreover, the highest value of eTh associated with Taref Formation is 16.2 ppm. The geochemical studies of collected samples from the anomalous zones showed the presence of secondary uranium in addition to rare earth elements. Meanwhile, the black shale trace elements are measured and showed high concentrations of tungsten. The magnetic data analysis is performed using tilt derivative and 3D magnetic modeling methods. Most of the deduced structures are trending in NW–SE, and NE–SW directions. The depths to the basement rocks are ranged from 0.475 km to 1.07 km below the ground surface.

Interpretation of geophysical data for iron ore detailed survey in Laje, Bahia, Brazil.

The transition zone between the Archean blocks, Jequié and Itabuna-Salvador-Curaçá, in the county of Laje, Bahia, Brazil, is potentially important for iron ore deposits of economic interest. This research investigates one of the eighteen anomalies defined by a previous integrated interpretation of geological and airborne gamma ray spectrometry and magnetic data in this transition zone. Its choice resulted from being located in an area with intense transcurrent shear and from the occurrence of pebbles rich in magnetite. Because of paucity of surface geological information, a ground-based geophysical survey added valuable information for the definition of a drilling program in the area. The survey consisted of two parts and followed up the aforementioned previous integrated interpretation of the Valença sheet. The first part consisted of one gravity and magnetic profile, which indicated a favorable site for additional investigation. The second part consisted of a detailed survey in the selected area with gravity, magnetic, and VLF-EM. The interpretation of the data of the geophysical methods allowed to delineate two zones in the area, both located at magnetic anomalies, gravity highs and relatively conductive parts. The two zones have a high potential for iron ore, because they present significant and correlated anomalies.

A log –barrier approach for airborne gamma-ray spectrometry inversion

The standard processing of airborne gamma-ray spectrometry (AGRS) data provides useful preliminary information to interpretation in several contexts, such as environmental studies, geological mapping, and analysis of mineral deposits. For optimal results, the acquisition conditions should be nearly constant, and the flight height should be uniform. However, abrupt changes in flight height (often originated from mountainous terrain) are common and lead to spurious variations and incorrect anomaly interpretation. Moreover, the commonly used corrections applied to radiometric data do not consider the effective sampling area of a survey, especially the overlap between successive fields of view. As a consequence, the concentrations estimates of potassium (K), uranium (eU), and thorium (eTh) are not sharp. A solution to deal with this problem is to compute the concentration from the AGRS data through an inversion algorithm. Inversion of AGRS data has shown to be an effective approach to suppress the significant overlap between successive fields of view. We introduce a logarithmic barrier approach for the radiometric inversion to avoid spurious negative values in the radioelement concentration models. We choose calibration ranges from Brazil and Canada to test the proposed methodology. We produced concentration models for K, eU and eTh and compared the standard approach model with the recovered model from both ranges. The predicted data from inversion of both calibration ranges are mostly consistent with the survey data, not over smoothing the data or fitting noise. The predicted data from inversion showed more consistency with the observed data than the one predicted from the standard procedure.

Retrieving geological units with unsupervised clustering of gamma-ray spectrometry data

Airborne gamma-ray spectrometry (AGRS) provides valuable insights for geological mapping, mineral exploration, geomorphological studies, and lithological differentiation. The interpretation of AGRS data is usually performed by skilled interpreters, requires visual acuity and is time-consuming. In this study, we used unsupervised clustering and object-based classification on the primary variables potassium (K), uranium (eU), and thorium (eTh) to automatically retrieve geological units in Mara Rosa Magmatic Arc – Goiás, Brazil, a well-studied area known by a gold district. We first cluster a color image composition (Red = K; Green = eTh; Blue = eU) using gaussian mixture models. We estimate the ideal number of classes to partition the image with the bayesian information criterion. Then, we performed a class separability analysis to identify and merge classes with low statistical separability. Finally, we used an object-based approach to reduce inconsistencies in the unsupervised classification map. To assess our approach, we compute the structural similarity index between the classification map and a reference geological map of the study area. The results show that our approach retrieved geologically meaningful regions in the AGRS data, reaching 0.94 of overall structural similarity with the geological map. Combining unsupervised clustering and AGRS data allows a better interpretation of the geological units into the same Complex or Groups.

Structural and hydrothermal alteration mapping related to orogenic gold mineralization in part of Kushaka schist belt, North-central Nigeria, using airborne magnetic and gamma-ray spectrometry data

This paper presents an interpretation of airborne magnetic and gamma-ray spectrometry data over a part of the Kushaka schist belt of Nigeria with a view to assess the sub-surface structural framework and hydrothermal alteration haloes that are related to orogenic gold mineralization in the study area. The geophysical analyses performed to improve the quality of the aeromagnetic data for better understanding of the subsurface geology were reduction to the equator, upward continuation, total horizontal derivative, analytical signal, source edge detection, tilt-angle derivative of total horizontal derivative. The analyses performed on the airborne gamma-ray spectrometry data were made on K/eTh, F parameter and deviation of ideal K values (Kd). Deep-seated, brittle–ductile shear/fracture zones with characteristic depth of 428.0–607.6 m and area extent of 15.5 km by 6.5 km that were delineated in the area coincide with beehive of artisanal miners exploiting gold deposits. In this study, subsurface geologic structures, specifically dykes/faults, that trend in the ENE–WSW direction constitute a first-order control on orogenic gold mineralization in the study area. The hydrothermally altered zones mapped in the area indicated they are structurally controlled and closely associated with orogenic gold mineralization. Apart from geologic structural evidences that are controlling orogenic gold mineralization, this study has indicated that hydrothermal alteration mapping is equally important for a promising orogenic gold mineralization mapping.

Application of Bayesian classifier to magnetic and gamma ray spectrometry data for targeting hydrocarbon microseepages

The search for new hydrocarbon resources is becoming increasingly complicated and expensive. Conventional geophysical methods, such as seismic, continue to focus on finding traps in deeper and more complex structures. To save significant amounts of both time and money, hydrocarbon microseepages may dramatically change the way we carry out hydrocarbon exploration by focusing more on searching petroleum deposits and by tracking their near-surface expressions. Hydrocarbon microseepages result in predominantly vertical long-term migration and it can be manifested with a number of near surface alterations such as formation of ferromagnetic minerals and modification of radioactive element concentrations in soil (potassium depletion and increase of the uranium concentration, in relation to the thorium content).In this study, airborne gamma ray spectrometry and magnetic data have been used in Hassi R'mel region (Algeria) to identify subtle variations in radioactive element concentrations and shallow magnetic anomalies induced by hydrocarbon microseepages. A Bayesian classification algorithm has been applied to characterize the residual magnetic and radiometric anomalies that occur above the known hydrocarbon reservoirs within the study area. Weights of evidence method was used to provide a quantitative measure of the spatial association between these anomalies and the mapped hydrocarbon accumulations. Most hydrocarbon areas were confirmed by the concurrent presence of the characteristic attributes of magnetic and radiometric anomalies, and those occurring outside the known hydrocarbon occurrences may point to yet unproven underlying hydrocarbon accumulations. The wells and drill core data, together with the blind wells available in the study area, validate the final results.

ANÁLISE GEOFÍSICA DA REGIÃO DO RIO CONCEIÇÃO, QUADRILÁTERO FERRÍFERO, ASSOCIADOS A DADOS DE CAMPO, PETROGRÁFICOS E DE IMAGENS AÉREAS

The Quadrilátero Ferrífero region, located in the southeast portion of the São Francisco Craton, is one of the main metallogenic provinces in Brazil. Fieldwork, petrography, high-resolution airborne geophysics (magnetic and gamma-ray spectrometry data), and aerial images allowed us to produce a new map at the 1:25,000 scale, with important contributions in the lithotypes detailing, understanding of the geological structures and relationship between the different stratigraphic units. Interpretation of airborne geophysical data integrated with field structural and lithological observations were successfully employed in the creation of the litho-structural framework in a poorly exposed Proterozoic and Archean terrain. Airborne gamma-ray spectrometry data aided in the mapping process in areas with regolith cover including erosional ridges. The magnetic total derivative image revealed regional and local structures. In addition, our work details the units of occurrence of Rio das Velhas and Minas Supergroup. The aerial coverage of the Mindá and Santa Quitéria formations strongly increased, as well as the area of the Cauê Formation was better defined. The new geological map provides many improvements over the pre-existing maps. New lithological facies and structures were identified and others become more visible and lithologicalboundaries are refined or confirmed.