Geochemical Mapping Research Articles

A New Method to Evaluate Gold Mineralisation-Potential Mapping Using Deep Learning and an Explainable Artificial Intelligence (XAI) Model

Geoscientists have extensively used machine learning for geological mapping and exploring the mineral prospect of a province. However, the interpretation of results becomes challenging due to the complexity of machine learning models. This study uses a convolutional neural network (CNN) and Shapley additive explanation (SHAP) to estimate potential locations for gold mineralisation in Rengali Province, a tectonised mosaic of volcano-sedimentary sequences juxtaposed at the interface of the Archaean cratonic segment in the north and the Proterozoic granulite provinces of the Eastern Ghats Belt in Eastern India. The objective is to integrate multi-thematic data involving geological, geophysical, mineralogical and geochemical surveys on a 1:50 K scale with the aim of prognosticating gold mineralisation. The available data utilised during the integration include aero-geophysical (aeromagnetic and aerospectrometric), geochemical (national geochemical mapping), ground geophysical (gravity), satellite gravity, remote sensing (multispectral) and National Geomorphology and Lineament Project structural lineament maps obtained from the Geological Survey of India Database. The CNN model has an overall accuracy of 90%. The SHAP values demonstrate that the major contributing factors are, in sequential order, antimony, clay, lead, arsenic content and a magnetic anomaly in CNN modelling. Geochemical pathfinders, including geophysical factors, have high importance, followed by the shear zones in mineralisation mapping. According to the results, the central parts of the study area, including the river valley, have higher gold prospects than the surrounding areas. Gold mineralisation is possibly associated with intermediate metavolcanics along the shear zone, which is later intruded by quartz veins in the northern part of the Rengali Province. This work intends to model known occurrences with respect to multiple themes so that the results can be replicated in surrounding areas.

Application of arsenic surveying for determining the position of former mining and metallurgical constructions: an example from the Radzimowice area (Lower Silesia, SW Poland)

Soil geochemical prospecting is becoming an increasingly important part of archaeological research. Therefore, it is possible to determine the location of various archaeological facilities that no longer exist in the study region. In this study, a morphological analysis of the “Stara Góra” deposit in Radzimowice (Lower Silesia, Poland) was performed using LiDAR DTM (light detection and ranging digital terrain model) images and historical data that describe mining in the vicinity of Radzimowice. This method identified numerous remains of centuries-old mining and metallurgical activity. The data collected were used to create a map of arsenic soil concentrations in this area. The map helped point to the exact locations of the old ore-processing facilities. Geochemical mapping was performed on a 20 × 20-m grid at a sampling depth of approximately 0.2 m. The samples were analysed by X-ray fluorescence spectrometry with energy-dispersive X-ray spectroscopy (XRF-EDS). The highest concentrations of this element occurred near the arsenic calciner and related dumps, as well as near dumps created during extraction from the Arnold shaft. In summary, in this article, we present the possibility of using a geochemical map of arsenic concentrations in soils supported by LiDAR data for archaeological purposes.

Geochemical Occurrence Characteristics of Geogenic Heavy Metals in Korea Evaluated Using Geochemical Map Data

Joo Sung Ahn, Seung-Jun Youm, Yong-Chan Cho, Gil-Jae Yim, Sang-Woo Ji, Jung-Hwa Lee, Pyeong-Koo Lee, Jeong-Ho Lee, Seong-Cheon Shin. Econ. Environ. Geol. 2022;55:339-52. https://doi.org/10.9719/EEG.2022.55.4.339

3DU–TA: A new multifractal model involving surface topography for separation of geochemical anomalies

A novel anomaly recognition technique was propounded to help reconcile mineralization-related geochemical patterns with topographic non-stationaries within the study area. The topography variations were characterized by elevation and slope factors of grid cells in a digital elevation model (DEM). In the first step of the technique architecture, the spatial U-statistics formulation was expanded for a 3D framework to integrate elevation-related information into geochemical measurements. Slope angles were then modeled across the cell-based geochemical map using DEM information to modulate planimetric areas into topographic attributes. Three-dimensional spatial U-values and topographic attributes were integrated in a multifractal model called 3DU–TA, providing power-law relations that aid in decomposition of geochemical patterns. The mathematical formulation established for the 3DU–TA model was implemented by programming in MATLAB platform and it was applied to geochemical data pertaining to a deposit-scale porphyry copper system. Core drilling data were used as benchmark to appraise the performance of the 3DU–TA model in the recognition and separation of metal enrichment levels from background and it was compared with the well-established concentration–area (C–A) fractal model. We defined mineralization rate Mr and normalized productivity Np as criteria for judging the integrity of anomalous geochemical patterns derived by the 3DU–TA model in reflecting subsurface mineralization. We also adapted a success-rate plot for deposit-scale experiments and the relevant areas under the curve (AUC) as gauges for quantitative evaluation of model relevance in reflecting subsurface metal enrichment. The derived values of Mr and Np imply that the geochemical populations decomposed with the 3DU–TA model, compared with those decomposed with the C–A model, yielded anomaly patterns that were more consistent with subsurface metallogenic realities. The success-rate curve for topography-enhanced results had an AUC = 0.940, which was higher than that for the C–A model (AUC = 0.867), indicating that the former revealed anomalies with substantially stronger spatial correlations with subsurface metal contents. Intuitive geochemical and quantitative metallogenic assessments suggest that the proposed multifractal modeling technique is capable of providing more practical insights into mineralization realities in geosystems with complex topographic variations.

Putting South-West England on the (strontium isotope) map: A possible origin for highly radiogenic 87Sr/86Sr values from southern Britain

Reconstructions of ancient mobility based on strontium isotopes are only ever as reliable as estimates for baseline values of bioavailable strontium in the study area. Current biosphere mapping for Britain suggests that there are no sizeable areas hosting 87Sr/86Sr values above 0.714 south of Cumbria. As a result, archaeological humans or animals with such (for Britain) ‘highly radiogenic’ strontium isotope values are commonly interpreted as having moved either from Scotland or abroad. This paper presents the first dedicated strontium isotope map for South-West England based on 98 modern biosphere samples (including 68 new measurements). Numerous samples from the Cornubian granite (Dartmoor) have 87Sr/86Sr values above 0.714 (maximum 0.7287) and, based on their distribution, it is suggested that the previously elusive ‘highly radiogenic’ values are characteristic for areas where the soil has with high rubidium concentrations. These occur at lower elevations which are better suited for agriculture and permanent human settlement than the high moors. Previous interpretations of archaeological samples from southern Britain may need to be revised considering these new results, but they also highlight the continued need for biosphere sampling and the usefulness of geochemical maps as a routine part of strontium isotope investigations in archaeology.

Coastal Marine Geochemical Provinces and Background Values in Sediments: A Methodological Approach

The Italian approach to determining background values (BGVs) of metals and trace elements in marine sediments according to the national legislation transposing the water framework directive (WFD) has been illustrated. This study may be helpful for all countries that need to establish local BGVs for the correct assessment of contamination in areas with wide geological and geochemical variability and, particularly, for those that need assessing the good chemical status according to the WFD. The first step was clearly defining the BGV as a concentration value that allows for discriminating between natural and anthropogenic contributions and establishing the concept of the marine geochemical province (MGP). Successively, criteria for delimiting the MGPs were provided, similar to those adopted for the geochemical mapping of the territory. Finally, an integrated method based on the constitution of a dataset from unpolluted sediments obtained from pre-industrial levels was chosen for determining the BGV.

Central Java regional geochemistry: influence of environmental geology and mineral occurrences

Stream sediments geochemical surveys were undertaken in Central Java, Indonesia as a part of the Geological Agency’s geochemical mapping project with support from several universities. A total of 1583 stream sediment samples were collected from Central Java and analyzed using X-Ray Fluoresces for 29 elements. Geochemical maps were processed by the GIS software. Based on the overlay between geological and geochemical maps, there are several elemental anomalies, for example, the ultramafic formation from Kebumen showing distinctive Chromium (Cr), Cobalt (Co), and Magnesium (Mg) anomalies. Meanwhile, the potassic igneous rocks from Muria Mountain have Cerium (Ce), Lanthanum (La), and Zirconium (Zr) anomalies. Elemental anomalies related to mineral resources and mining areas such as Arsenic (As), Copper (Cu), and Lead (Pb) are found in Trenggalek, Pacitan, and Kebumen; while Barium (Ba), Iron (Fe), and Manganese (Mn) are scattered along the southern coast of Central Java. Anthropogenic elements (Chlorine (Cl), Ce, and As) spread along the north coast of Central Java probably because of pollution by industrial, farming, and urban areas. Heavy metals pollutions that were identified previously in the Bengawan Solo River flow can be seen on this geochemical map which can convincingly delineate elements anomalies due to geological and environmental conditions.

Exhumation of the high‐pressure Richarddalen Complex in NW Svalbard: Insights from 40Ar/39Ar geochronology

Abstract40Ar/39Ar dating of white mica from foliated metamorphic rocks of the Caledonian orogen of NW Svalbard was performed using the single‐grain fusion technique. Two samples, an augen orthogneiss and a mica schist, were collected from the high‐pressure Richarddalen Complex. Three additional mica schist samples were collected from the tectonically underlying Montblanc Unit. 40Ar/39Ar analysis of white mica separates yielded weighted average 40Ar/39Ar dates of 446.1 ± 1.1, 438.4 ± 1.1, 439.4 ± 1.2, 439.8 ± 1.5 and 439.3 ± 1.0 Ma, with the oldest date provided by the Richarddalen mica schist. The single‐grain fusion 40Ar/39Ar dating was accompanied by geochemical mapping of white mica using a microprobe. We interpret the oldest date as the age of cooling after a Late Ordovician high‐pressure event and the four younger dates to represent the timing of subsequent deformation associated with assembly of a Caledonian nappe stack.

Quantifying diffuse contamination: Comparing silver and mercury in organogenic and minerogenic soil

For both, silver (Ag) and mercury (Hg), the median concentrations in an aqua regia extraction of minerogenic top- and subsoil from continental scale geochemical surveys (Australia, China, Europe) are around 0.02 mg/kg. When the soil O horizon is collected as topsoil sample, the concentration of again both elements is higher by about a factor of 10 (range 7–30), with median concentrations around 0.2 mg/kg Ag and Hg. Geochemical maps of top- and subsoil at different scales for both elements display regional patterns which reflect mainly geology, climate and topography. Anthropogenic sources like mines, power plants, or major cities visually occur only as local anomalies. For Ag in organogenic topsoil the maximum possible input due to diffuse contamination is estimated to be in the 0.02 mg/kg range, about 10% of the median concentration in the soil O horizon. For Hg this value is slightly higher at 0.03 mg/kg. In the soil O horizon Hg concentrations show less variability than in the C horizon. Substantial Hg soil contamination should lead to noticeably increased Hg/Ag ratios.

Google Earth-aided visualization and interpretation of geochemical survey data

Geochemical prospecting is an important and effective approach for discovering mineral deposits. Collection, management, visualization, interpretation, modelling and publishing of geochemical survey data remain challenging. The main aim of this study is to illustrate the application of Google Earth in the visualization and interpretation of geochemical survey data using a dataset collected from the Daqiao district, Gansu Province, China. Google Earth, a free web-based program that provides a rich set of global images along with satellite and map data, can be applied to design geochemical sampling strategies, display geochemical sampling location landscapes, collect and manage geochemical survey data, visualize and publish 0D (point), 1D (profile), 2D (raster map) and 3D (superposition of multiple maps) geochemical maps, and interpret and model geochemical patterns using various Google Earth functions and the Keyhole Markup Language. Thematic collection: This article is part of the Applications of Innovations in Geochemical Data Analysis collection available at: https://www.lyellcollection.org/cc/applications-of-innovations-in-geochemical-data-analysis

The Relationship between Particle Size and Element Distribution in Stream Sediments from the Dongyuan W-Mo Deposit, Eastern China

Particle size exerts significant control on the concentration of elements in stream sediments and is therefore critical in stream sediment-based geochemical exploration, which has proved important in China’s National Geochemical Mapping Project. There are various geographical landscapes in China with different distribution characteristics of stream sediments. Therefore, we studied the relationship between particle size and element distribution in stream sediments, which is always a crucial but challenging issue in geochemical surveys. The distributions of minerals and elements in eight size fractions of stream sediments (2–0.84, 0.84–0.42, 0.42–0.25, 0.25–0.177, 0.177–0.125, 0.125–0.096, 0.096–0.074, and <0.074 mm) from the Dongyuan W-Mo deposit in eastern China were studied. The results show that the 2–0.25 mm particle size fraction of stream sediments is composed mainly of rock debris and various minerals from broken bedrock upstream, while the <0.25 mm fraction is composed mainly of clay, individual minerals, and organic matter. The pilot survey results prove that using 2–0.25 mm as the sampling particle size fraction is better than using <0.25 mm, especially in geochemical prospecting and geological body delineation. Sampling the 2–0.25 mm particle size fraction of stream sediments can help to delineate proven ore bodies, ore-related anomalies, and geological bodies more effectively and more credibly. The suggested sampling particle size fraction for a stream sediment geochemical survey in a humid to semi-humid low mountain landscape in eastern China is therefore 2–0.25 mm, rather than the particle size fraction of <0.25 mm that was used for sampling in this area before. This paper depicts a successful example for determining the optimal sampling particle size fraction for stream sediment-based geochemical exploration.

Gold enrichment characteristics and exploration prospects in Zambia: Based on 1 ∶ 1000000 geochemical mapping

The 1∶1000000 geochemical mapping of Zambia provides catchment sediment geochemical data for 58 elements including Au from 746 sediment samples at 736 sampling sites, corresponding to a sampling density of about one site per 1000 km2. Under strict quality control using field duplicates, certified reference materials, and analytical replicate samples, the Au was determined by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The detection limit of Au was 0.20 × 10−9. The 95% range (2.5%–97.5%) of Au concentrations was from 0.24 × 10−9 to 1.36 × 10−9, and the median value was 0.40 × 10−9. The most noticeable Au distribution patterns shown on the map are mainly located between Lusaka and Ndola (Lufilian Arc Belt). In addition, several high Au value areas occurred in Mansa, Muyombe, Chipata, and Livingstone. The spatial distribution patterns of Au in tectonic units, drainage basins, and geomorphological landscapes could be related to the Lufilian Arc Belt and Bangweulu Block. The Au concentrations show metallogenic belts between Muyombe and Mbala areas, between Mansa and Ndola areas, and between Lusaka and Kasempa areas.© 2022 China Geology Editorial Office.

Radiological, geochemical, and environmental assessment in Xuancheng, China: The airborne gamma-ray spectrometric view

Radionuclides in the environment have been considered a health risk for many years owing to their contribution to the radiation dose to the human body. A great deal of field survey research has been conducted in this area. However, few researchers have studied the key sources of geological and geochemical substances that pose radioactive environmental problems from the perspective of airborne gamma-ray spectrometry. This study aims to determine the radiation variations in geological units caused by rocks containing radionuclides, evaluate the level of radiation, and analyze as well as identify the key radio-elements. The content of 40K, 238U, 232Th, and the total count (TC) in 15 different geological units were studied based on the concentration data. The gamma absorbed dose rate (D) of the whole region was calculated to identify and evaluate the main areas of high radiation. The quantitative statistical methods, the Pearson correlation analysis, principal component analysis (PCA), hierarchical cluster analysis (HCA), and geochemical mapping were used to analyze the selected high radiation areas and reveal potential key lithological factors. The results indicate that the Cretaceous intrusive rock, in the northeast of the study area, is a major source of natural radionuclides and continuous radiation. The high radiation in this area is strongly associated with the Yaocun rock mass containing K-feldspar granite, and the correlation coefficient of the 232Th with effective dose was the highest (0.91), whereas that of 238U was the lowest (0.49). The study has determined that 232Th is the key radio-element, causing high radiation by comparing the results of HCA of field gamma-ray measurement data. The findings from this study are valuable for determining the key factors causing high radiation levels in similar exposure conditions.

Contamination Levels and the Ecological and Human Health Risks of Potentially Toxic Elements (PTEs) in Soil of Baoshan Area, Southwest China

The primary goals of this study were to reveal the environmental status of potentially toxic elements (PTEs) and their ecological risks, as well as their associated health risks in the Baoshan area, southwest China, which has been surveyed with the scale of 1:250,000 geochemical mapping. Based on a comparison of the PTE concentrations with the soil environmental quality of China and the enrichment factor (EF), geo-accumulation index (Igeo), contamination factor (Cf), and potential ecological risk indexes (Eri and PERI), as well as the potential non-carcinogenic hazard indices (HI and CHI) and carcinogenic risks indices (TCR and CTCR), the following conclusions were drawn: The PTE concentrations in the surface soil samples that were collected from the investigated area (1.65% sites) exceeded the risk intervention values (RIV) for soil contamination of agricultural land of China. Cadmium (Cd) and mercury (Hg) posed higher ecological risks than other PTEs (arsenic (As), chromium (Cr), lead (Pb), copper (Cu), nickel (Ni), and zinc (Zn)), which was highlighted by their toxic response factor. Arsenic was the main PTE with a non-carcinogenic risk (19.57% sites for children and 0.25% sites for adults) and the only PTE that carries a carcinogenic risk (2.67% sites for Children and 0.76% sites for adults) to humans in the research area. Children are more vulnerable to health risks when compared to adults because of their behavioral and physiological traits. Geological genesis was responsible for the high concentrations, ecological risk, and health risk distribution patterns of the examined PTEs. Even though the present research highlights several important aspects related to PTE pollution in the research area, further investigations are needed, especially in mining areas.

Handheld Laser-Induced Breakdown Spectroscopy (hLIBS): A Valuable Tool for Terrestrial and Extraterrestrial Recognition of Meteorites in the Field

The role and performance of handheld laser-induced breakdown spectroscopy (hLIBS) devices is discussed in the context of meteorite research exploration while targeting specific questions of geologic interest in the field. The fast data acquisition and minimal sample preparation features of these devices make them very attractive as candidate tools for future astronauts in geochemical mapping, resource prospecting, sample selection, and hazard identification. Although hLIBS instruments have recently become commercially available, they have not yet been widely applied to meteoritical field campaign. This article reviews how the very promising advanced analytical tool hLIBS may be helpful to classify and discriminate meteorites in the field.

Exploration of overlapped endogenous mineralization on the basis of paleovolcanic reconstructions

By these days issues of survey of blind and covered deposits are very actual. High affectivity of geological and prospecting abilities could be achieved only when complex studies have been done which allow to indicate structural elements of explores area and evaluate geological and geochemical potential of prospective areas. In the article the structural and geochemical criterion developed by authors is considered. Its use is preceded by definition of the structural and geological characteristic of the territory based on the method of paleovolcanic reconstruction. At the later stage areas, perspective for detection of an ore mineralization are outlined basing on localization of various type of a mineralization at specified structural units of paleovolcanic structures. Application of geochemical mapping within the perspective areas allows to estimate prospects of the areas, to allocate most perspective sites with their preliminary geochemical estimate.

Assessment of groundwater study using geophysical and geochemistry mapping in Thamirabarani sub-basin, Karunkulam area, Southern India

Groundwater exploration study has been carried out in Karunkulam area, Srivaikundam taluk, Thoothukudi district, Tamil Nadu, with the help of geophysical and geochemical characteristics. The study area was covered in the meta-sedimentary rock of quartzite, and the source rock of sandstone was delineated from the channel of the Thamirabarani River. Resistivity sounding square array, 2D electrical resistivity imaging technique and magneto-telluric method were used to identify the aquifer thickness and bedrock in quartzite terrain of the study area. An attempt has been made to use GIS spatial distribution map for irrigation suitability and livestock drinking purposes. The hydro-geochemical facies were used to analyze the cations and anions exchange process. It was also observed that the Ca2+- HCO3− was dominant in the low alkalinity in nature and the quality of groundwater represents the geochemical nature in aquifer media. The type of rock–water interaction with Mg2+-Na+-Ca2+-Cl−-HCO−3, Na+-Ca2+-Mg2+-Cl− and Na+-Mg2+-Ca2+-Cl− indicates the rock water interaction between the quartzite, gneissic and some granitic intrusion in the part of the area. Based on geophysical 2D imaging and magneto-telluric resistivity, inferred fracture quartzite zones were water-bearing formation in the study area. This primarily supports the hypothesis assumed at the beginning of the research in the study area.

Geochemical anomaly definition using stream sediments landscape modeling

Geochemical anomaly mapping is a crucial part of environmental and mineral exploration projects. Stream sediments are the most frequently sampling medium for geochemical mapping in regional scales, resulting from various geological processes. To enhance geochemical anomaly in stream sediments, the geochemical landscape, including topographic factors and drainage catchment basin extracted from a digital elevation model (DEM), and average precipitations, were applied. These factors were taken into consideration in this research to investigate the influence of the geochemical landscape constraints on the Mo polymetallic mineralization anomaly of stream sediments in a typical hilly area of Jining, Inner Mongolia, China, using Bayesian Maximum Entropy (BME) approach. Geographically weighted regression was applied to construct probability density function of soft data based on slope, aspect, drainage catchment basin and precipitation. Stream sediment data, at a scale of 1:200,000 (hard data), was integrated with the soft data to map stream sediment anomalies associated with molybdenum-polymetallic mineralization. Considering the influences of geochemical landscape during stream sediment anomaly identification can make up the shortage of missing and incomplete observations in regional geochemical data. By integrating the geochemical landscape factors during the stream sediment anomaly identification process, the impacts of the geochemical landscape on sediment dispersion halos were addressed, and the anomaly identification accuracy was improved. The anomaly areas defined by the BME model demonstrated that 31.41% of the study area contained 75% of the known mineral deposits and consequently the uncertainty of geochemical anomalies was reduced.

Bayesian Deep Learning for Spatial Interpolation in the Presence of Auxiliary Information

Earth scientists increasingly deal with ‘big data’. For spatial interpolation tasks, variants of kriging have long been regarded as the established geostatistical methods. However, kriging and its variants (such as regression kriging, in which auxiliary variables or derivatives of these are included as covariates) are relatively restrictive models and lack capabilities provided by deep neural networks. Principal among these is feature learning: the ability to learn filters to recognise task-relevant patterns in gridded data such as images. Here, we demonstrate the power of feature learning in a geostatistical context by showing how deep neural networks can automatically learn the complex high-order patterns by which point-sampled target variables relate to gridded auxiliary variables (such as those provided by remote sensing) and in doing so produce detailed maps. In order to cater for the needs of decision makers who require well-calibrated probabilities, we also demonstrate how both aleatoric and epistemic uncertainty can be quantified in our deep learning approach via a Bayesian approximation known as Monte Carlo dropout. In our example, we produce a national-scale probabilistic geochemical map from point-sampled observations with auxiliary data provided by a terrain elevation grid. By combining location information with automatically learned terrain derivatives, our deep learning approach achieves an excellent coefficient of determination (R^{2} = 0.74) and near-perfect probabilistic calibration on held-out test data. Our results indicate the suitability of Bayesian deep learning and its feature-learning capabilities for large-scale geostatistical applications where uncertainty matters.Graphic

Geochemical and Hydrothermal Alteration Patterns of the Abrisham-Rud Porphyry Copper District, Semnan Province, Iran

In this study, the zonality method has been used to separate geochemical anomalies and to calculate erosional levels in the regional scale for porphyry-Cu deposit, Abrisham-Rud (Semnan province, East of Iran). In geochemical maps of multiplicative haloes, the co-existence of both the supra-ore elements and sub-ore elements local maxima implied blind mineralization in the northwest of the study area. Moreover, considering the calculated zonality indices and two previously presented geochemical models, E and NW of the study have been introduced as ZDM and BM, respectively. For comparison, the geological layer has been created by combining rock units, faults, and alterations utilizing the K-nearest neighbor (KNN) algorithm. The rock units and faults have been identified from the geological map; moreover, alterations have been detected by using remote sensing and ASTER images. In the geological layer map related to E of the study area, many parts have been detected as high potential areas; in addition, both geochemical and geological layer maps only confirmed each other at the south of this area and suggested this part as high potential mineralization. Therefore, high potential areas in the geological layer map could be related to the mineralization or not. Due to the incapability of the geological layer in identifying erosional levels, mineralogy investigation could be used to recognize this level; however, because of the high cost, mineralogy is not recommended for application on a regional scale. The findings demonstrated that the zonality method has successfully distinguished geochemical anomalies including BM and ZDM without dependent on alteration and was able to predict erosional levels. Therefore, this method is more powerful than the geological layer.