Evaluation of solid mineral potentials in north western parts of Nigeria using aero radiometric and geochemical data sets

Evaluation of solid mineral potentials in north western parts of Nigeria using aero radiometric and geochemical data sets | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Evaluation of solid mineral potentials in north western parts of Nigeria using aero radiometric and geochemical data sets Abubakar Muhammad Narimi, Adewuyi Rafiu abdulwaheed, Alhasan Defeyn Usman, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7464005/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The study area covers Zamfara and its surrounding regions. It lies between latitude 11°00'N and 13°00'N and longitude 5°00'E and 7°00'E. Geologically, the region consists of Migmatite Gneiss Complex (MGC), Schist Belts and a portion of the Sokoto Basin. It is considered to be one of the richest in mineral resources in Nigeria, comprising of lithium, gold, zinc, copper, and lead. However, some mineralisation and hydrothermal alteration zones identified in the area may lack economically viable ore due to low-grade or dispersed minerals. Consequently, the indiscriminate activities of artisanal mining resulted into a lot of abandoned pits and trenches which facilitate the environmental degradation and loss of farmlands. Petrographic analysis as proposed by some researchers also reveals ambiguous mineral structures; compared X-ray fluorescence (XRF) that provides clearer insights by identifying and quantifying their elemental composition of the minerals. Aero radio metric method was used for mapping hydrothermal alteration zones and concentration of radio element related to solid minerals through, radio element ratio maps, ternary map, F-parameter and K deviation. Geochemical analysis was used to validate the chemical constituents and percentage of minerals present using X-ray florescence (XRF). Hydrothermally altered zones were indicated by an anomalously high F parameter (0.328–0.723) and high K/eTh ratio of roughly (0.1153 to 0533). The radiometric ternary image reveals superior concentration of individual radioelement at their respective areas. On the other hand, X-ray florescence technique pointed out significant percentage concentrations of major oxides by weight, including CaO (18.29%), Al₂O₃ (31.13%), SiO (76.0) Fe₂O₃ (81.81%), SO₃ (0.18%), K₂O (25.29%), Mn₂O₃ (1.67%), P₂O₅ (0.91%), MgO (2.56%), Cr₂O₃ (1.28%), and CuO (0.04%) across multiple sampled locations. and other barred areas in some identified mineralisation zones. In conclusion, these findings highlight key mineralized trends and barren hydrothermal and mineralisation zones. The study underscores the potential of these techniques as reliable tools for structural mapping and detecting alteration zones, offering a robust framework for mineral exploration in similar terrains. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Solid earth sciences Solid minerals hydrothermal alteration zones Minerilisation zones Barren Mineralisation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Solid minerals are naturally occurring substances derived from the earth which are of great value to man. This can also refer to as mineral deposit important to man and can be worked as a profit which includes native or pure element: Gold Au, copper Cu, diamond C, graphite C, manganese Mn, and silver Ag. Metalic ores such as: Hermite (Fe 2 o 3 ) Magnetite (Fe 3 o 4 ), Morundum (Al 2 o 3 ). Sulfides: Galena Pbs, Sphalerite ZnS, Pyrite Fes 2, Chalcopyrite CuFeS 2 . Sulfate such as: Gypsum CaSo 4 + 2H 2 o, Anhydrite Caso 4, Barite BaSo 4 . Carbonate Calcite CaCo 3 , Dolomite CaMg(co 3 ) 2 . Halides such as: sodium chloride NaCl, Fluorite CaF 2 , Sylvite KCl and other silicate minerals that make up off 95% of all rocks 26 . Nigeria as a nation is blessed with abundant solid minerals resources distributed fairly in all the states of the federation 21 . According to the reports by the Nigerian Geological Survey Agency (NGSA), Nigeria has some 34 known major mineral deposits distributed in all locations across the country and offers considerable attraction for investors. Exploration in Nigeria for solid minerals, e.g. tin, niobium, lead, zinc and gold goes back for more than 90 years but only tin and niobium have ranked on a world wide scale. Zamfara state is among the northwestern part of Nigeria considered to be one of the richest in mineral resources, with more than 120 known solid minerals mining fields as identified by unofficial artisan miners in the country 26 , 21 . These deposits are found in vein-type mineralisation (pegmatite veins) or as disseminated mineralisation hosted by different types of rocks ranging from schist, gneiss and granite intrusions 13 , 11 . 2 , tectonic model stated that; solid minerals were deposited from the hydrothermal solution, which was produced in a deeper crustal level (upper mantle) due to magmatic processes 4 . The study area comprises three of the thirteen schist belts of Nigeria namely: Maru, Anka, & Wonaka Schists belt with a small sedimentary sequence of Sokoto Basin. Samples obtained from the explorational activities, mostly by the artisanal miners has found different varieties of solid minerals such as: Hornblende, Galena, Gold, Ruby, Zircon, Tantalite, Columbite, Monzonite, Green cast, Pebble, Lithium, Lepidolite, Kunzite, copper, Mica, Manganese, Coal, Quartz, Rutile, Iron ore, feldspar, Raw, Sun Stone, Cinnabar, Chromate, Morganite, within the study area 22 , 12 . Consequently, these have attracted a lot of interest for the area to be surveyed in the context of geological mapping, geochemistry, structural geology and geophysical survey 27 . However, some mineralisation and hydrothermal alteration zones identified in the area may lack economically viable ore due to low-grade or dispersed minerals. Consequently, the indiscriminate activities of artisanal mining resulted into a lot of abandoned pits and trenches which facilitate the environmental degradation and loss of farmlands. Petrographic analysis as proposed by some researchers also reveals ambiguous mineral structures; compared X-ray fluorescence (XRF) that provides clearer insights by identifying and quantifying their elemental composition of the minerals. 3 , 8 , 31 , 7 . The fundamental objective of this prospecting is to discover mineral resources through a search in areas where mining has not been previously practiced by the multinational companies. The search process should result in obtaining the samples minerals that give reasonable percentage evidence of the existence of the commodity. Once the outcrop has been discovered, considerable further work is necessary in order to advance knowledge of the particular geologic aspects and the extent of the mineral deposit in the area. Solid mineral exploration is restricted here to activities and evaluations necessary to gather data for making decisions on such issues as the quantity and quality of the commodities so as to further decide on the economic feasibility. Geologic mapping is an important task in exploration. Mapping involves compiling detailed field notes, rock types, geologic structures, and man-made structures 10 . Good maps and mapping techniques provide a means for planning and accomplishing exploration 20 . Solid minerals occurrence in the study area is associated with veins, dikes, fractures, faults and any other structure that might serve as conduits for hydrothermal alterations and injections of mineralising fluid. Airborne radiometry provides important information about areas with a great influence of hydrothermal alteration as a result of distribution contents of the radioactive elements K, eU and eTh in rocks 19 , 25 . Description of study area and its mineralogical composition The study area is in West Africa, and it falls entirely within north western Nigeria. It covers some parts of Zamfara basement complex and Sokoto sedimentary basin. Geographically, the study area is positioned between latitude 11°30'N and 13°00'N and longitude 5°30'E and 7°00'E which span to about (9 half-degree aero radiometric grids) as shown in Fig. 1 . The research area covered is 275,994.6 km 2 . Geologically, the study area is situated at the eastern part of the West African Craton 6 , underlain by migmatite, granite, biotite, gneiss, diorite, muscovite schist, phyllite, banded iron ore formation, medium coarse grained, quartz-mica schist, biotite- hornblende granite and hornfels. On the other hand, the north western part of the study area is dominated by small exposure of Sokoto sedimentary basin underlain by sand stone, lignite, clay, shale, limestone, silt stone, gravel, mudstone and coal all in the northwestern region of Nigeria (Fig. 1 ). The area also consists of Proterozoic metasedimentary belts that are made up of schist (undifferentiated), phyllite, and slate. The schist belts within the study area include: Anka, Maru and Wonaka 33 . The granitoids comprise fine-grained, coarse-grained, porphyritic granites and pegmatites of Pan-African age 21 . It has been reported to host a variety of mineral resources, including limestone, iron ores, coal, gold, copper, lithium, manganese, galena, pyrite, gypsum and other silicate minerals 5 , 21 . Data and Methodology Aero radiometric data were acquired from The Nigerian Geological Survey Agency 14 . High-resolution airborne radiometric data were obtained from the Nigerian Geological Survey Agency (NGSA). It was acquired using 512-channels gamma-ray spectrometers (NaI “Tl” crystal size of 2″ × 2″) attached to fixed-wing aircraft. The study area consists of sheets (30,31, 32,52,53, 54,75,76,77,) half degree aero radiometric data sheets of Zamfara basement complex and some part of Sokoto sedimentary basin. On the other hand geochemical data was used to validate the conclusions drawn from radiometric secondary field data. The data was analysed using Geosoft (Oasis Montaj) version 8.5, Arcgis and Microsoft excel software Aero radiometric data Radiometric surveying measures gamma-ray emissions from radioactive minerals like uranium, thorium, and potassium 23 , 9 . It detects radiation from Earth's crust's shallow layers and provides insights into rock chemical composition 10 . It intersects geochemistry and geophysics, allowing high-resolution surveys to map lithological variations, identifies hydrothermal alteration zones, locate radioactive deposits, reveal surface structures, and quantify radioelement concentrations 1 . This study focuses on interpreting radiometric data for mineralisation by integrating concentration channels of K, eU, and eTh with total count data. The ratios between these channels provide stronger indicators of lithological variations and hydrothermal alteration. The K/eTh ratio is particularly effective for detecting hydrothermal alteration and potassic alteration zones. Geochemical Data Analysis To characterize the geochemistry of major elements in the research region, rock samples from the man-made dug wells and outcrops were collected in 11 different locations as identified from the aero radiometric and aeromagnetic data sets. The samples were put into nylon container in order to avoid oxidation, the containers were level specimen: (A - K) which were taken to the of geology laboratory of Bayero University Kano for XRF analysis. In order to determine elemental composition, the samples were crush and grinded into a powder form 16 . After that, fused discs and pressed beads were created for analysis of main and minor elements. To ascertain the natural moisture contents of each prepared sample, they were oven-dried for an entire night at 105˚C. The samples were again roasted at 800˚C for a whole night in order to calculate the Loss on Ignition (LOI). The weight difference was then computed. In a platinum crucible, 1.5 g of powder from each sample for which LOI has been established was combined with 6 g of lanthanum oxide (La 2 O 3 ) and lithium tetraborate (Li 2 B 4 O 7 ). The mixture was then fused at 1200˚C to create melt beads for the main element analysis 17 . Radiometric Concentration and Channel Ratio maps Concentrations of K, eU and eTh tend to be correlated in most rock types. Anomalous areas occur where this ‘normal’ situation breaks down owing to enrichment and/or depletion of one or more of the three radioelements, which can often be identified in the elemental channel data 18 & 30 . The individual channels show the absolute concentrations of the elements, whereas their ratios, i.e., eTh/K, eU/K, eU/eTh and their reciprocals, show their relative concentrations. Using amplified channel values increases the influence that variations in those channels have on the ratio and reduces the effects of variations in the denominator term. They are particularly effective for channels having low count rates with respect to the other channels, typically eU and eTh 30 , 32 . Ternary Map By convention, K is assigned to red, eTh to green and eU to blue When all three elements are abundant the display tends towards white, and when all three are sparse it tends towards black. They allow (semi-)quantitative classification of the ground’s chemical signature and lithological discrimination based on colour. Consequently, they are by far the most common form of display for radiometric data 29 . Channel Ratio maps Potassium Thorium Ratio map (K/eTh) was created through: Grid image bottom → Grid math and applying the expression in Eq. (1) \(\:\text{G}\) 0 \(\:\:=\frac{\text{G}1}{\text{G}2}\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:.\dots\:\dots\:..\left(1\right)\) where G 0 = Potassium Thorium Ratio map while G 1 and G 2 are Potassium and Thorium concentration respectively. The same procedure is repeated for Uranium Thorium Ratio Map (eU/eTh) 15 . Ternary Maps Ternary map was produced through grid and image tool → display → ternary image. Conventional combination of (RGB), (Red = Potassium, Green = Thorium and Blue = Uranium) were also used for this work. F Parameter F – Parameter map was created through: Grid image bottom → Grid math and applying this expression in Eq. (2) below $$\:\text{F}0\:=\:\left(\frac{\text{F}1}{\text{F}2}\right)\text{*}\:\text{F}3\dots\:\dots\:\dots\:\dots\:..\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\left(2\right)$$ Where F 0 = F - Parameter while \(\:\raisebox{1ex}{${F}_{1}$}\!\left/\:\!\raisebox{-1ex}{${F}_{2}$}\right.\) is the Potassium Thorium Ratio and F 3 is equivalent of Uranium concentrations respectively. K - Deviation Equation (3) offered the formula for adjusting the potassium data for each surface or aerial gamma-ray spectral profile based on the thorium data. $$\:\:{\text{K}}_{\text{i}}=\:\left(\raisebox{1ex}{${\text{m}\text{e}\text{a}\text{n}\:\text{K}}_{\text{s}}$}\!\left/\:\!\raisebox{-1ex}{${\text{m}\text{e}\text{a}\text{n}\:\text{T}\text{h}}_{\text{s}}$}\right.\right)\:\text{m}\text{e}\text{a}\text{n}\:{\text{T}\text{h}}_{\text{s}}\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:..\left(3\right)$$ For the location with actual thorium value, K i is the optimal thorium-defined potassium value. The mean values of potassium and thorium are K s and Th s , respectively. This method eliminates the need to prepare charts and use curve fitting by calculating the equations straight from the data and supporting quick field assessments. The expression in Eq. (4) was used to determine the deviances of the real values from the determined ideal values for all location. KD% is the potassium relative deviations stated as a fraction of the location values. K s , is potassium measured values at the station 28 . Interpretation of Results and Discussion Interpreting geological and geophysical data is one of the most important steps in the analysis of geophysical data. Large-scale radiometric data can be used to find near surface geological structures and the latter can be used to develop a regional tectonic model. This study will primarily focus on the geological formations in Zamfara State and a portion of the Sokoto Basin that may contain solid minerals which could be validated using geochemical analysis. Ternary map Multichannel gamma-ray spectrometry data can be enhanced and displayed in a single image with radiometric ternary maps. The colors blue, green, and red were blended with the eU, eTh, and K values, respectively. Significant amounts of the three radioelements—which are inputs from the granite granite, gneiss biotite, porphyritic granite, and migmatite rocks—are present in the white coloring. Conversely, sedimentary and low-grade metamorphic rocks are represented by the black coloring, which indicates low concentration levels of radioelements (Fig. 2). The ternary map's low radio element concentrations may be the consequence of banded iron formation. However, because thorium is released when other materials weather and concentrates in iron oxides, they may appear to be rich in thorium. Radioactive anomalies may target areas of depletion or enrichment of one or more of the three radio element. In case of investigation at hand, High concentration of potassium (HCK) as dominated by red colouration may indicate high potassium contents above uranium and thorium; while its boundaries demarcated by white or yellow lines are likely the product of high-level potassic hydrothermal changes. Whereas, High concentration of Uranium (HCeU) in blue colour represents zones with a greater concentration of uranium over potassium and thorium and its demarcated boundaries may serve as uranium alteration zones. High concentration of Thorium (HCeTh) in green colours represents zones with a higher concentration of thorium over potassium and uranium. For mining purposes, it is also crucial to identify the areas with large concentrations of radioactive elements and the minerals that are associated with them. However, since these elements are extremely hazardous to humans and the environment, care must be taken during exploration processes. Potassium Thorium Ratio Maps K/eTh ratio anomalies, which are characterized by K enrichment in Figure (3), have a proportion of roughly 0.1227 to 0.2204 and indicated in red to pink colours, can be identified as zones of high hydrothermal alteration. Owing to the fact that potassium is more mobile than thorium. As thorium is typically considered to be highly immobile, The K/eTh ratio map's regions with low potassium concentrations may also indicate that thorium was likely mobilized in systems that have undergone hydrothermal alteration. The boundaries of these highly hydrothermal altered zones are accompanied by highly deformed moderate concentration of K/eTh in green and yellow colours and can be indicative of high structurally altered zones. Owing to the fact that K/eTh enrichment generally builds up around fault structures, which could be a sign of hydrothermal alteration. The towns of Zurmi, Maradun, and Mafara in the northeast and centre of the map, as well as the towns of Maru, Bingi, Dansadau, and Gusau in the south and southeast, contain the hydrothermal alteration zones in the medium to coarse-grained biotite granite schist. The high K/eTh ratio map results indicate the possibility of magnetite, garnet, tourmaline, and chloride mineral resources in the vicinity. Low thorium patterns can also be a sign of alteration in different rocks and along lithologic boundaries; hydrothermal fluids that leach thorium concentration are found in faults and fractures within these zones. F-Parameter On the F-parameter map figure (4), anomalies classified as high concentration (HC) accurately depict hydrothermal alteration zones devoid of lithologies and weathering that resulted in signatures. Significantly fractured and hydrothermally altered areas within the study region are identified by an abnormally high F parameter (0.433–0.743). The research area can be broadly divided into three regions based on the distinctive characteristics on these maps: the low hydrothermally transformed region (LC) in the northwestern portion of the map, highly transformed region (HC) in the southern and northeastern parts and moderately affected region (MD) in the north east and south west of the research area, the majority of the hydrothermal alteration zones align with places that have seen artisanal mining activity in either the recent or recent past. In the northwestern section of the research region, which is a portion of the Sokoto sedimentary basin, there are prominent indications of an extremely low F parameter iindicating that there may be less alteration and potentially no significant mineralisation. K Deviation K-deviation figure (5) refers to the amount by which potassium concentrations in the study area deviate from a reference or average level. Since the K deviation value (5) is mostly found in the bedrock or shallow subsurface, it might be less impacted by lithological differences and by factors like vegetation. Variations in the magnetic signature of highs and lows, ranging from (0.053% to.723%), are revealed by K deviation. The ore samples from (A to K) taking for geochemical analysis where indicated in K –deviation map Fig. 4.14, where (MSP) represent mineralised sample point and BSP represent barren sample point. High magnetic anomalies are depicted with pink to red colours, while medium magnetic anomalies are represented with yellow green and low magnetic anomalies are depicted in blue colours. In mineral exploration, high K-deviation areas might be targets for further study as they could be linked to potassic mineralisation. On the other hand, low K-deviation zones might indicate a lack of such mineral resources. Potassium is a major constituent in many minerals, including feldspar, mica, and clay minerals. High potassium levels may also be correlated with areas of potential mineralisation or hydrothermal alteration. In some cases, elevated potassium values can be associated with areas of potassic alteration, which is common in porphyry systems or certain types of ore deposits especially copper and gold. High K values can signify the manifestation of specific rock types, such as granitic or volcanic rocks, which typically have higher potassium content. In contrast, low K values may indicate sedimentary rocks or zones where potassium has been leached or altered. The table (1) and Fig. 6 below presents the various oxide samples collected from the field and analyzed using the XRF machine. Table 1 shows sample of minerals with their respective oxides in percentage Oxides (wt%) Samples A B C D E F G H I J K Crustal abundance (wt %) CaO 0.28 0.00 0.26 18.29 1.66 0.23 4.46 0.00 81.81 0.19 0.00 4.24 SiO 2 65.2 41.73 43.06 41.08 35.86 38.87 47.92 67.90 8.18 75.68 76.08 66.8 Al 2 O 3 8.38 19.29 24.60 15.97 31.13 14.61 15.38 0.18 4.40 11.47 9.40 15.05 Fe 2 O 3 2.39 9.49 0.00 15.45 19.95 0.00 1.19 0.06 81.81 0.28 7.38 4.09 SO 3 0.40 0.16 0.18 0.22 0.15 0.18 0.18 0.16 0.00 0.40 0.00 0.06 K 2 O 7.01 0.03 25.39 0.02 0.01 23.54 0.29 0.00 2.62 9.87 2.03 3.19 Mn 2 O 3 0.16 0.08 0.61 0.29 0.65 5.65 0.04 0.02 0.19 0.00 1.67 0.07 T i O 2 0.66 0.65 0.23 0.15 0.38 0.38 0.18 0.12 0.12 0.20 1.06 0.54 P 2 O 5 0.00 0.00 0.00 0.60 0.14 0.00 0.00 0.00 0.00 0.91 0.00 0.15 MgO 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.56 0.00 1.10 2.30 Cr 2 O 3 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.11 0.00 1.28 0.18 CuO 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.00 0.00 0.0005 Ta 2 O 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.03 0.00 0.00 0.0002 BaO 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.36 0.00 0.042 Cl 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.28 0.00 953 Rb 2 O 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.00 0.05 The oxides and minerals that are used in geochemical analysis include the following: coal, galena, hornblende, kunzite, lead oxide copper, lepidolite/mica, lithium and black mica, lead oxide copper, lithium, malachite copper, malachite, manganese, muscovite, quartz white and rutile as shown in the Plate 4.1, below. Validation of Aero radiometric data sets using Geochemical Analysis The suggested interpretations are constrained by other geological and geochemical findings, but geological and structural mapping based only on the analysis of radiometric field data is insufficient for both geo-scientific and economic applications due to uncertainty in the potential field interpretation 24 . This method offers a thorough understanding of how geological data and underlying structures are distributed spatially. Finding high-potential mineralisation zones is crucial, particularly those connected to tectonics and hydrothermal activity. These studies are important, but their value goes beyond data analysis; on-the-ground validation is also necessary to support the conclusions drawn from possible field data. Eleven sample points were chosen for geological ground verifications in this respect, at a number of prospective locations spread over several magnetic and radiometric domains. These samples were validated using X- ray florescence. It has been discovered that, out of eleven (11) samples four (4) i.e. (36.36%) were barren due to absent or insufficient while the remaining seven (7) i.e. (63.64%) contain economic minerals that can mine for profit. Relationship between Hydrothermal Alteration and Geochemical Analysis Plagioclase, orthoclase, quartz, muscovite, amphibolite, pyroxene, and other primary igneous rocks that were altered by hydrothermal processes were chemically replaced with altered minerals that were enriched in iron oxides, manganese oxide, titanium oxide, chromium oxide, hornblende, and galena and lead oxide; other mineralisation include copper mineralisation such as chalcopyrite, malachite and lithium mineralisation, which included kunzite, lepidolite, and lithium oxide (Plate 1). Conclusion The study effectively integrates geological, geophysical, and geochemical techniques to identify and characterize mineralisation zones in Zamfara and its surroundings. The combination of aeromagnetic and aero radiometric methods, supported by XRF analysis, provides detailed insights into the region's structural complexity, mineral distribution, and hydrothermal alterations. These findings not only classify the site into magnetic lithologic units and reveal depth to magnetic sources but also highlight key mineralized trends and mineralized barren zones. Finally, this study underscores the potential of these techniques as reliable tools for structural mapping and detecting alteration zones, offering a robust framework for mineral exploration in similar terrains. Declarations Access to data The Nigerian Geological Survey Agency is the source of the high-resolution aero radiometric data, which are not publicly accessible. Geochemical analysis data was obtained from Bayero University Kano Geology laboratory. However, with reasonable request, the first author can be able to provide the data. Funding Declaration The authors received no funding was for this work. Author Contributions Statement Abubakar Muhammad Narimi: research, formal analysis, software, validation, conception, methodology, and writing original draft. Resources, data correction, review, and editing, was done by A. A. Rafiu and U.D. Alhassan visualization, project management, and supervision are all handled by A.Idris Nda , A.A Bagare and Fahad Abubakar Declaration of Competing Interest The authors declare that there are no conflicts of interest. All individuals who meet the criteria for authorship have been appropriately included References Abbass, A. A., Fidelis, I. K. & Shakarit, B. A. Interpreting the magnetic signatures and radiometric indicators within Kogi State, Nigeria for economic resources. Geosyst. Geoenviron. 2 , 100157 (2023). Abu-Alarm, T., Grosch, E. & Monsef, M. A. Pan-African shear zone-hosted gold mineralization in the Arabian-Nubian shield. EGU General Assembly (2013). https://ui.adsabs.harvard.edu/abs/2013EGUGA.15.9893A/abstract Augie, A. I. & Ridwan, M. M. Delineation of potential mineral zones from aeromagnetic data over eastern part of Zamfara. Savanna J. Basic Appl. Sci. 3 , 60–66 (2021). http://www.sjbas.com.ng Bowell, R. J. fotibmx, Lagos, L., De Los, H. C. R. & Declercq, J. Classification & characteristics of natural lithium resources. Elements 16 , 259–264 (2020). http://dx.doi.org/10.2138/gselements.16.4.259 Burke, K., Freeth, S. J. & Grant, N. K. The structure and sequence of geological events in the Basement Complex of the Ibadan area, Western Nigeria. Precambrian Res. 3 , 537–545 (1976). Chardon, D., Grimaud, J. L., Beauvais, A. & Bamba, O. West African lateritic pediments: Landform-regolith evolution processes and mineral exploration pitfalls. Earth Sci. Rev. 179 , 124–146 (2018). Dada, S. S. Proterozoic evolution of the Nigeria–Boborema province. Geol. Soc. Lond. Spec. Publ. 294 , 121–136 (2008). Danbatta, U. A. Precambrian crystal development in the northwestern part of Zuru schist belt, northwestern Nigeria. J. Min. Geol. 44 , 45–56 (2008a). Dentith, M. C., Frankcombe, K. F. & Trench, A. Geophysical signatures of Western Australian mineral deposits: an overview. Explor. Geophys. 25 , 103–160 (1994). Dentith, M. & Mudge, S. T. Geophysics for the Mineral Exploration Geoscientist (Cambridge Univ. Press, 2014). Dzukogi, A. N., Sanusi, Y. A., Mohammad, S. B. & Roko, A. Application of aeromagnetic data analysis & interpretations to investigate solid mineral potential in part of Northwest Nigeria. Int. J. Earth Sci. Geophys. 8 , 057 (2022). http://doi.org/10.35840/2631-5033/7557 Dzukogi, A. N. & Mahmud, M. B. Mapping of potential lithium mineral deposits in some parts of Northwestern Nigeria using magnetic and gamma-ray spectrometry data. Afr. J. Environ. Sci. Renew. Energy 10 , 91–108 (2023). Ekwueme, B. N. & Matheis, G. Geochemistry & economic value of pegmatites in the Precambrian basement of southeastern Nigeria. (Oxford & IBH Publishing, 1995). Fugro Airborne Surveys. Aero magnetic survey specification. Furgo Airborne Publishers 1–5 (2006). Galbraith, J. H. & Saunders, D. F. Rock classification by characteristics of aerial gamma-ray measurements. J. Geochem. Explor. 18 , 49–73 (1983). https://doi.org/10.1016/0375-6742(83)90080-8 Jenkins, R. An Introduction to X-Ray Spectrometry (Heyden, London, 1976). Jenkins, R., Gould, R. W. & Gedcke, D. Quantitative X-Ray Spectrometry (Marcel Dekker, New York, 1981). Michael, D. & Stephen, T. M. Geophysics for the Mineral Exploration Geoscientist (Cambridge Univ. Press, London, 2015). Minty, B. R. S. The fundamentals of airborne gamma-ray spectrometry. AGSO J. Aust. Geol. Geophys. 17 , 39–50 (1997). Morrell, A. E., Locke, C. A., Cassidy, J. & Mauk, J. L. Geophysical characteristics of adularia-sericite epithermal gold-silver deposits in the Waihi-Waitekauri region, New Zealand. Econ. Geol. 106 , 1031–1041 (2011). Obaje, N. G. Geology and Mineral Resources of Nigeria Vol. 120 (Springer, 2009). Obaje, N. G., Adukub, M. & Yusuf, I. The Sokoto Basin of Northwestern Nigeria: A preliminary assessment of the hydrocarbon prospectivity. Petrol. Technol. Dev. J. 7 , 1–15 (2013). https://doi.org/10.4236/ojg.2023.138038 Ogah, A. J. & Abubakar, F. Solid mineral potential evaluation using integrated aeromagnetic and aeroradiometric datasets. Sci. Rep. 14 , 1637 (2024). Portnov, A. M. Specialization of rocks towards potassium and thorium in relation to mineralization. Int. Geol. Rev. 29 , 326–344 (1987). Ribeiro, V. B. & Mantovani, M. S. M. Gamma spectrometric and magnetic interpretation of cabaçal copper deposit in Mato Grosso (Brazil): implications for hydrothermal fluids remobilization. J. Appl. Geophys. 135 , 223–231 (2016). https://doi.org/10.1016/j.jappgeo.2016.10.016 Salau, S. L., Danbatta, U. A. & Agunleti, Y. S. The interpretation of aeromagnetic & satellite imagery for structures coincident with gold mineralization in Anka Schist Belt, Northwestern Nigeria. J. Appl. Geol. Geophys. 4 , 29–34 (2016). https://www.iosrjournals.org/iosrjagg/papers/Vol.%204%20Issue%205/Version-2/E0405022934.pdf Sani, A. A., Augie, A. I. & Aku, M. O. Analysis of gold mineral potentials in Anka Schist Belt, Northwestern Nigeria using aeromagnetic data interpretation. J. Niger. Assoc. Math. Phys. 52 , 291–298 (2019). https://www.researchgate.net/publication/337951812 Saunders, D. F., Burson, K. R., Branch, J. F. & Thompson, C. K. Relation of thorium-normalized surface and aerial radiometric data to subsurface petroleum accumulations. Geophysics 58 , 1417–1427 (1993) Tawey, M. D., Adetona, A. A., Alhassan, U. D., Rafiu, A. A., Salako, K. A. & Udensi, E. E. Aeroradiometric data assessment of hydrothermal alteration zones in parts of North Central Nigeria. Asian J. Geol. Res. 4 , 1–16 (2021). Telford, W. M., Geldart, L. P. & Sheriff, R. E. Applied Geophysics (Cambridge Univ. Press, 1990). Usman, M. A. & Ibrahim, A. A. Petrography & geochemistry of rocks of Northern Part of Wonaka Schist Belt, Northwestern Nigeria. Niger. J. Basic Appl. Sci. 25 , 87–99 (2017). http://dx.doi.org/10.4314/njbas.v25i2.10 Uyanık, N. A., Öncü, Z., Uyanık, O. & Bozcu, M. Determination of alteration zones and geological unit limits using natural radioactivity properties of Sandıklı-Suhut areas. J. Appl. Geophys. 196 , 104525 (2022). Woakes, M., Rahaman, M. A. & Ajibade, A. C. Some metallogenetic features of the Nigerian basement. J. Afr. Earth Sci. 6 , 655–664 (1987) Plate 1 Plate 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Plate1.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7464005","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":518187143,"identity":"7d94a6da-3376-4cc0-aec7-d6377640160f","order_by":0,"name":"Abubakar Muhammad Narimi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYPACCQY29sYHzAwHgOwDRGvhOWxAkhaQrmQitfBPO8D24Ocei2g+ycds0gVnGOT4biSwPfyCz+zbCeyGPc8kctukk9mkZ9xgMJa8kcBuLIPPmtsJbBI8B0Ba8o9J83xgSNwAtEVaAo8OeaAWyT8gLZKH2UBa6glqMQBqkQbbIsEMZNxgSDAAapH8gEeL4e3ENmkZkBaeZGbrGWckDGeeedgmjc8rcreTj0m+OVCXO7/9MOPtgmM28nzHgSI/8OlhYGxA5kmARZh58GrBagx+W0bBKBgFo2CEAQDRtkndDxS+PwAAAABJRU5ErkJggg==","orcid":"","institution":"Federal University Birnin Kebbi","correspondingAuthor":true,"prefix":"","firstName":"Abubakar","middleName":"Muhammad","lastName":"Narimi","suffix":""},{"id":518187145,"identity":"141a2bf9-3a52-4113-a81b-e75a85150a8a","order_by":1,"name":"Adewuyi Rafiu abdulwaheed","email":"","orcid":"","institution":"Federal University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Adewuyi","middleName":"Rafiu","lastName":"abdulwaheed","suffix":""},{"id":518187147,"identity":"003883b8-72b5-4843-aab4-2b2d82fe1def","order_by":2,"name":"Alhasan Defeyn Usman","email":"","orcid":"","institution":"Federal University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Alhasan","middleName":"Defeyn","lastName":"Usman","suffix":""},{"id":518187149,"identity":"400f2984-9271-417e-b8c8-0fd1b02dadd6","order_by":3,"name":"Abdullahi Idris Nda","email":"","orcid":"","institution":"Federal University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Abdullahi","middleName":"Idris","lastName":"Nda","suffix":""},{"id":518187150,"identity":"529ef7dc-4c4e-4cfb-a443-7ddc34df5fb3","order_by":4,"name":"Fahad Abubakar","email":"","orcid":"","institution":"Confluence University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Fahad","middleName":"","lastName":"Abubakar","suffix":""},{"id":518187151,"identity":"67cbbdf4-1356-4855-8bfc-76f14a3868c6","order_by":5,"name":"Adamu Aliyu Bagare","email":"","orcid":"","institution":"Yobe State University","correspondingAuthor":false,"prefix":"","firstName":"Adamu","middleName":"Aliyu","lastName":"Bagare","suffix":""}],"badges":[],"createdAt":"2025-08-26 14:38:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7464005/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7464005/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91962673,"identity":"224b90ee-5cd3-41c7-a789-f4d5d13acb70","added_by":"auto","created_at":"2025-09-23 07:58:01","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3225339,"visible":true,"origin":"","legend":"","description":"","filename":"radiometricandgeochem.docx","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/9d5a1a95e1310169e6ddda3d.docx"},{"id":91958197,"identity":"58ee1738-1e50-4cd9-ad16-2080bedb0e0f","added_by":"auto","created_at":"2025-09-23 07:34:00","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8424,"visible":true,"origin":"","legend":"","description":"","filename":"198cfc56096f45218793ab22a309c104.json","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/bb965518bd0dd626a3a1d9e1.json"},{"id":91960031,"identity":"49ea974c-7971-42b0-be04-3e2a90cee52a","added_by":"auto","created_at":"2025-09-23 07:42:01","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":101442,"visible":true,"origin":"","legend":"","description":"","filename":"198cfc56096f45218793ab22a309c1041enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/b85a7c2c04b350d8d7418f6a.xml"},{"id":91960029,"identity":"ddc7a63a-849b-4397-bba1-65f7675a8331","added_by":"auto","created_at":"2025-09-23 07:42:01","extension":"jpeg","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":124434,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/3b99803d1b2d786a54078651.jpeg"},{"id":91961012,"identity":"d0bcc5fa-3cf7-4705-9954-6bcb51ce6680","added_by":"auto","created_at":"2025-09-23 07:50:01","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":571503,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/7a9b199568a95bd2a5bafd60.png"},{"id":91958206,"identity":"0a16f326-3a9c-4674-9b50-a37edd9cf1a0","added_by":"auto","created_at":"2025-09-23 07:34:01","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":628373,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/0dbe3e19ad34292eddd5a39d.png"},{"id":91961013,"identity":"98df82d8-6d67-46ab-9096-b7035fa0dd50","added_by":"auto","created_at":"2025-09-23 07:50:01","extension":"jpeg","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1646076,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/2e7f88d7f97c8f88e9a3dd39.jpeg"},{"id":91960034,"identity":"6aa6aa17-9a55-44ef-a6a1-b626e1f50c0d","added_by":"auto","created_at":"2025-09-23 07:42:01","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":617896,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/df41595001e48968f944ff53.png"},{"id":91961010,"identity":"6ac8f1d6-c51a-4e45-9aa9-7033e981410c","added_by":"auto","created_at":"2025-09-23 07:50:01","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":603530,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/4cb587554aa935981175bfb0.png"},{"id":91960037,"identity":"14ad5238-217b-4779-a311-ac0b5b1bbeca","added_by":"auto","created_at":"2025-09-23 07:42:01","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":177026,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/2b6691b6ad81c2174099834c.png"},{"id":91958211,"identity":"9b809f91-38c9-4950-91d5-3b9e840959e7","added_by":"auto","created_at":"2025-09-23 07:34:01","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":105984,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/8a9f7f68ba9fd0a0ed00aa78.png"},{"id":91958204,"identity":"961b3736-dece-4c8b-822a-8220727f6b55","added_by":"auto","created_at":"2025-09-23 07:34:01","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":114749,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/08fe1eb82ab9d5befc65dca1.png"},{"id":91958218,"identity":"abb8f9fe-4a00-4976-86a5-37fe2dd64bf1","added_by":"auto","created_at":"2025-09-23 07:34:01","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":567602,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/bd0a2bc3574acc017d249469.png"},{"id":91958214,"identity":"06d7473c-4b33-4aef-9fe8-df76de953c51","added_by":"auto","created_at":"2025-09-23 07:34:01","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":112159,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/b8a828e4c9f7088491285ed8.png"},{"id":91958219,"identity":"e111f65b-45d1-4b6d-ab61-90622373f788","added_by":"auto","created_at":"2025-09-23 07:34:01","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":96537,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/372927a47832266391e5aa45.png"},{"id":91958215,"identity":"4b2ff485-5254-4d87-87e9-7c31453c320e","added_by":"auto","created_at":"2025-09-23 07:34:01","extension":"xml","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":99508,"visible":true,"origin":"","legend":"","description":"","filename":"198cfc56096f45218793ab22a309c1041structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/0a2f73fc57a3d9980b08b2b2.xml"},{"id":91960036,"identity":"e2d8ceb7-8912-4202-afb4-c864a3f4d8be","added_by":"auto","created_at":"2025-09-23 07:42:01","extension":"html","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":109317,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/98eed694e8645bcd0acdb840.html"},{"id":91958198,"identity":"3de213c9-f0c7-4e71-aa9f-6fe1d9f29e16","added_by":"auto","created_at":"2025-09-23 07:34:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":333112,"visible":true,"origin":"","legend":"\u003cp\u003eGeology of the Study Area\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/dc689b23898732cbe7c7c59c.png"},{"id":91958202,"identity":"a613850e-294b-4f60-b179-e592db08009b","added_by":"auto","created_at":"2025-09-23 07:34:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":571503,"visible":true,"origin":"","legend":"\u003cp\u003eRadio element ternary map\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/678d354972e3ba3734f8e779.png"},{"id":91958199,"identity":"c1284fa5-6214-4261-91b4-f235103af326","added_by":"auto","created_at":"2025-09-23 07:34:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":628373,"visible":true,"origin":"","legend":"\u003cp\u003ePotassium Thorium Ratio Map\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/e7469b2638322b12d1859d8f.png"},{"id":91958205,"identity":"bca3bbed-cfaa-464d-aba8-b2132f819136","added_by":"auto","created_at":"2025-09-23 07:34:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":930657,"visible":true,"origin":"","legend":"\u003cp\u003eF- Parameter\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/54806e8ecbaf0aff7d74ac5e.png"},{"id":91958207,"identity":"eccb8cd6-0d2b-48db-ad58-7a6b0134a1c7","added_by":"auto","created_at":"2025-09-23 07:34:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":617896,"visible":true,"origin":"","legend":"\u003cp\u003eK deviation\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/d796039bb5ffe62c3ae95886.png"},{"id":91961009,"identity":"99e5b6bd-0abc-4f70-ae57-19a83a17768e","added_by":"auto","created_at":"2025-09-23 07:50:01","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":50353,"visible":true,"origin":"","legend":"\u003cp\u003eA pie chart of sample of oxides used in geochemical analysis\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/3c3197ad15ca94bb9f366e53.png"},{"id":103881140,"identity":"8d7b676c-d36e-4a55-8229-dd85eae6828b","added_by":"auto","created_at":"2026-03-04 05:25:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3875128,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/625e99e9-be16-431a-96e8-2fb734e0efda.pdf"},{"id":91960030,"identity":"869b043e-34e5-4f05-8515-f0cb614726fd","added_by":"auto","created_at":"2025-09-23 07:42:01","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":617855,"visible":true,"origin":"","legend":"","description":"","filename":"Plate1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7464005/v1/c72f9b1c8ecf906f9ed22340.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of solid mineral potentials in north western parts of Nigeria using aero radiometric and geochemical data sets","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSolid minerals are naturally occurring substances derived from the earth which are of great value to man. This can also refer to as mineral deposit important to man and can be worked as a profit which includes native or pure element: Gold Au, copper Cu, diamond C, graphite C, manganese Mn, and silver Ag. Metalic ores such as: Hermite (Fe\u003csub\u003e2\u003c/sub\u003eo\u003csub\u003e3\u003c/sub\u003e) Magnetite (Fe\u003csub\u003e3\u003c/sub\u003eo\u003csub\u003e4\u003c/sub\u003e), Morundum (Al\u003csub\u003e2\u003c/sub\u003eo\u003csub\u003e3\u003c/sub\u003e). Sulfides: Galena Pbs, Sphalerite ZnS, Pyrite Fes\u003csub\u003e2,\u003c/sub\u003e Chalcopyrite CuFeS\u003csub\u003e2\u003c/sub\u003e. Sulfate such as: Gypsum CaSo\u003csub\u003e4 +\u003c/sub\u003e 2H\u003csub\u003e2\u003c/sub\u003eo, Anhydrite Caso\u003csub\u003e4,\u003c/sub\u003e Barite BaSo\u003csub\u003e4\u003c/sub\u003e. Carbonate Calcite CaCo\u003csub\u003e3\u003c/sub\u003e, Dolomite CaMg(co\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e. Halides such as: sodium chloride NaCl, Fluorite CaF\u003csub\u003e2\u003c/sub\u003e, Sylvite KCl and other silicate minerals that make up off 95% of all rocks \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNigeria as a nation is blessed with abundant solid minerals resources distributed fairly in all the states of the federation \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. According to the reports by the Nigerian Geological Survey Agency (NGSA), Nigeria has some 34 known major mineral deposits distributed in all locations across the country and offers considerable attraction for investors. Exploration in Nigeria for solid minerals, e.g. tin, niobium, lead, zinc and gold goes back for more than 90 years but only tin and niobium have ranked on a world wide scale.\u003c/p\u003e\u003cp\u003eZamfara state is among the northwestern part of Nigeria considered to be one of the richest in mineral resources, with more than 120 known solid minerals mining fields as identified by unofficial artisan miners in the country \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. These deposits are found in vein-type mineralisation (pegmatite veins) or as disseminated mineralisation hosted by different types of rocks ranging from schist, gneiss and granite intrusions \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, tectonic model stated that; solid minerals were deposited from the hydrothermal solution, which was produced in a deeper crustal level (upper mantle) due to magmatic processes \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe study area comprises three of the thirteen schist belts of Nigeria namely: Maru, Anka, \u0026amp; Wonaka Schists belt with a small sedimentary sequence of Sokoto Basin. Samples obtained from the explorational activities, mostly by the artisanal miners has found different varieties of solid minerals such as: Hornblende, Galena, Gold, Ruby, Zircon, Tantalite, Columbite, Monzonite, Green cast, Pebble, Lithium, Lepidolite, Kunzite, copper, Mica, Manganese, Coal, Quartz, Rutile, Iron ore, feldspar, Raw, Sun Stone, Cinnabar, Chromate, Morganite, within the study area \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Consequently, these have attracted a lot of interest for the area to be surveyed in the context of geological mapping, geochemistry, structural geology and geophysical survey \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eHowever, some mineralisation and hydrothermal alteration zones identified in the area may lack economically viable ore due to low-grade or dispersed minerals. Consequently, the indiscriminate activities of artisanal mining resulted into a lot of abandoned pits and trenches which facilitate the environmental degradation and loss of farmlands. Petrographic analysis as proposed by some researchers also reveals ambiguous mineral structures; compared X-ray fluorescence (XRF) that provides clearer insights by identifying and quantifying their elemental composition of the minerals. \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe fundamental objective of this prospecting is to discover mineral resources through a search in areas where mining has not been previously practiced by the multinational companies. The search process should result in obtaining the samples minerals that give reasonable percentage evidence of the existence of the commodity. Once the outcrop has been discovered, considerable further work is necessary in order to advance knowledge of the particular geologic aspects and the extent of the mineral deposit in the area. Solid mineral exploration is restricted here to activities and evaluations necessary to gather data for making decisions on such issues as the quantity and quality of the commodities so as to further decide on the economic feasibility. Geologic mapping is an important task in exploration. Mapping involves compiling detailed field notes, rock types, geologic structures, and man-made structures \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Good maps and mapping techniques provide a means for planning and accomplishing exploration \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSolid minerals occurrence in the study area is associated with veins, dikes, fractures, faults and any other structure that might serve as conduits for hydrothermal alterations and injections of mineralising fluid. Airborne radiometry provides important information about areas with a great influence of hydrothermal alteration as a result of distribution contents of the radioactive elements K, eU and eTh in rocks \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eDescription of study area and its mineralogical composition\u003c/h3\u003e\n\u003cp\u003eThe study area is in West Africa, and it falls entirely within north western Nigeria. It covers some parts of Zamfara basement complex and Sokoto sedimentary basin. Geographically, the study area is positioned between latitude 11°30'N and 13°00'N and longitude 5°30'E and 7°00'E which span to about (9 half-degree aero radiometric grids) as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The research area covered is 275,994.6 km\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Geologically, the study area is situated at the eastern part of the West African Craton \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, underlain by migmatite, granite, biotite, gneiss, diorite, muscovite schist, phyllite, banded iron ore formation, medium coarse grained, quartz-mica schist, biotite- hornblende granite and hornfels. On the other hand, the north western part of the study area is dominated by small exposure of Sokoto sedimentary basin underlain by sand stone, lignite, clay, shale, limestone, silt stone, gravel, mudstone and coal all in the northwestern region of Nigeria (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The area also consists of Proterozoic metasedimentary belts that are made up of schist (undifferentiated), phyllite, and slate. The schist belts within the study area include: Anka, Maru and Wonaka \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. The granitoids comprise fine-grained, coarse-grained, porphyritic granites and pegmatites of Pan-African age \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. It has been reported to host a variety of mineral resources, including limestone, iron ores, coal, gold, copper, lithium, manganese, galena, pyrite, gypsum and other silicate minerals \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Data and Methodology","content":"\u003cp\u003eAero radiometric data were acquired from The Nigerian Geological Survey Agency \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. High-resolution airborne radiometric data were obtained from the Nigerian Geological Survey Agency (NGSA). It was acquired using 512-channels gamma-ray spectrometers (NaI “Tl” crystal size of 2″ × 2″) attached to fixed-wing aircraft. The study area consists of sheets (30,31, 32,52,53, 54,75,76,77,) half degree aero radiometric data sheets of Zamfara basement complex and some part of Sokoto sedimentary basin. On the other hand geochemical data was used to validate the conclusions drawn from radiometric secondary field data. The data was analysed using Geosoft (Oasis Montaj) version 8.5, Arcgis and Microsoft excel software\u003c/p\u003e\u003ch3\u003eAero radiometric data\u003c/h3\u003e\u003cp\u003eRadiometric surveying measures gamma-ray emissions from radioactive minerals like uranium, thorium, and potassium \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. It detects radiation from Earth's crust's shallow layers and provides insights into rock chemical composition \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. It intersects geochemistry and geophysics, allowing high-resolution surveys to map lithological variations, identifies hydrothermal alteration zones, locate radioactive deposits, reveal surface structures, and quantify radioelement concentrations \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThis study focuses on interpreting radiometric data for mineralisation by integrating concentration channels of K, eU, and eTh with total count data. The ratios between these channels provide stronger indicators of lithological variations and hydrothermal alteration. The K/eTh ratio is particularly effective for detecting hydrothermal alteration and potassic alteration zones.\u003c/p\u003e\n\u003ch3\u003eGeochemical Data Analysis\u003c/h3\u003e\n\u003cp\u003eTo characterize the geochemistry of major elements in the research region, rock samples from the man-made dug wells and outcrops were collected in 11 different locations as identified from the aero radiometric and aeromagnetic data sets. The samples were put into nylon container in order to avoid oxidation, the containers were level specimen: (A - K) which were taken to the of geology laboratory of Bayero University Kano for XRF analysis. In order to determine elemental composition, the samples were crush and grinded into a powder form \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. After that, fused discs and pressed beads were created for analysis of main and minor elements. To ascertain the natural moisture contents of each prepared sample, they were oven-dried for an entire night at 105˚C. The samples were again roasted at 800˚C for a whole night in order to calculate the Loss on Ignition (LOI). The weight difference was then computed. In a platinum crucible, 1.5 g of powder from each sample for which LOI has been established was combined with 6 g of lanthanum oxide (La\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e) and lithium tetraborate (Li\u003csub\u003e2\u003c/sub\u003eB\u003csub\u003e4\u003c/sub\u003eO\u003csub\u003e7\u003c/sub\u003e). The mixture was then fused at 1200˚C to create melt beads for the main element analysis \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eRadiometric Concentration and Channel Ratio maps\u003c/h3\u003e\n\u003cp\u003eConcentrations of K, eU and eTh tend to be correlated in most rock types. Anomalous areas occur where this ‘normal’ situation breaks down owing to enrichment and/or depletion of one or more of the three radioelements, which can often be identified in the elemental channel data \u003csup\u003e18\u003c/sup\u003e \u0026amp; \u003csup\u003e30\u003c/sup\u003e. The individual channels show the absolute concentrations of the elements, whereas their ratios, i.e., eTh/K, eU/K, eU/eTh and their reciprocals, show their relative concentrations. Using amplified channel values increases the influence that variations in those channels have on the ratio and reduces the effects of variations in the denominator term. They are particularly effective for channels having low count rates with respect to the other channels, typically eU and eTh \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eTernary Map\u003c/h3\u003e\n\u003cp\u003eBy convention, K is assigned to red, eTh to green and eU to blue When all three elements are abundant the display tends towards white, and when all three are sparse it tends towards black. They allow (semi-)quantitative classification of the ground’s chemical signature and lithological discrimination based on colour. Consequently, they are by far the most common form of display for radiometric data \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eChannel Ratio maps\u003c/h2\u003e\u003cp\u003ePotassium Thorium Ratio map (K/eTh) was created through: Grid image bottom → Grid math and applying the expression in Eq.\u0026nbsp;(1)\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{G}\\)\u003c/span\u003e\u003c/span\u003e\u003csub\u003e0\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:=\\frac{\\text{G}1}{\\text{G}2}\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:.\\dots\\:\\dots\\:..\\left(1\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003ewhere G\u003csub\u003e0\u003c/sub\u003e = Potassium Thorium Ratio map while G\u003csub\u003e1\u003c/sub\u003e and G\u003csub\u003e2\u003c/sub\u003e are Potassium and Thorium concentration respectively. The same procedure is repeated for Uranium Thorium Ratio Map (eU/eTh) \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eTernary Maps\u003c/h3\u003e\n\u003cp\u003eTernary map was produced through grid and image tool → display → ternary image. Conventional combination of (RGB), (Red = Potassium, Green = Thorium and Blue = Uranium) were also used for this work.\u003c/p\u003e\n\u003ch3\u003eF Parameter\u003c/h3\u003e\n\u003cp\u003eF – Parameter map was created through: Grid image bottom → Grid math and applying this expression in Eq.\u0026nbsp;(2) below\u003c/p\u003e\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{F}0\\:=\\:\\left(\\frac{\\text{F}1}{\\text{F}2}\\right)\\text{*}\\:\\text{F}3\\dots\\:\\dots\\:\\dots\\:\\dots\\:..\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\left(2\\right)$$\u003c/div\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWhere F\u003csub\u003e0\u003c/sub\u003e = F - Parameter while \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\raisebox{1ex}{${F}_{1}$}\\!\\left/\\:\\!\\raisebox{-1ex}{${F}_{2}$}\\right.\\)\u003c/span\u003e\u003c/span\u003e is the Potassium Thorium Ratio and F\u003csub\u003e3\u003c/sub\u003e is equivalent of Uranium concentrations respectively.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eK - Deviation\u003c/h2\u003e\u003cp\u003eEquation (3) offered the formula for adjusting the potassium data for each surface or aerial gamma-ray spectral profile based on the thorium data.\u003c/p\u003e\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:\\:{\\text{K}}_{\\text{i}}=\\:\\left(\\raisebox{1ex}{${\\text{m}\\text{e}\\text{a}\\text{n}\\:\\text{K}}_{\\text{s}}$}\\!\\left/\\:\\!\\raisebox{-1ex}{${\\text{m}\\text{e}\\text{a}\\text{n}\\:\\text{T}\\text{h}}_{\\text{s}}$}\\right.\\right)\\:\\text{m}\\text{e}\\text{a}\\text{n}\\:{\\text{T}\\text{h}}_{\\text{s}}\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:\\dots\\:..\\left(3\\right)$$\u003c/div\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFor the location with actual thorium value, K\u003csub\u003ei\u003c/sub\u003e is the optimal thorium-defined potassium value. The mean values of potassium and thorium are K\u003csub\u003es\u003c/sub\u003e and Th\u003csub\u003es\u003c/sub\u003e, respectively. This method eliminates the need to prepare charts and use curve fitting by calculating the equations straight from the data and supporting quick field assessments. The expression in Eq.\u0026nbsp;(4) was used to determine the deviances of the real values from the determined ideal values for all location.\u003c/p\u003e\u003cdiv id=\"Equc\"\u003e\n \u003cdiv id=\"FileID_Equc\" name=\"EquationSource\"\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eKD% is the potassium relative deviations stated as a fraction of the location values.\u003c/p\u003e\n\u003cp\u003eK\u003csub\u003es\u003c/sub\u003e, is potassium measured values at the station \u003csup\u003e28\u003c/sup\u003e.\u003c/p\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \n \n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \n \n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \n \n\u003c/div\u003e\n\u003cdiv id=\"Sec15\"\u003e\n \n \n\u003c/div\u003e\n\u003cdiv id=\"Sec16\"\u003e\n \n \n \n \n \n\u003c/div\u003e\n\u003cdiv id=\"Sec17\"\u003e\n \n \n\u003c/div\u003e\n\u003cdiv id=\"Sec18\"\u003e\n \n \n\u003c/div\u003e\u003c/div\u003e"},{"header":"Interpretation of Results and Discussion","content":"\u003cp\u003eInterpreting geological and geophysical data is one of the most important steps in the analysis of geophysical data. Large-scale radiometric data can be used to find near surface geological structures and the latter can be used to develop a regional tectonic model. This study will primarily focus on the geological formations in Zamfara State and a portion of the Sokoto Basin that may contain solid minerals which could be validated using geochemical analysis.\u003c/p\u003e\u003ch2\u003eTernary map\u003c/h2\u003e\u003cp\u003eMultichannel gamma-ray spectrometry data can be enhanced and displayed in a single image with radiometric ternary maps. The colors blue, green, and red were blended with the eU, eTh, and K values, respectively. Significant amounts of the three radioelements—which are inputs from the granite granite, gneiss biotite, porphyritic granite, and migmatite rocks—are present in the white coloring. Conversely, sedimentary and low-grade metamorphic rocks are represented by the black coloring, which indicates low concentration levels of radioelements (Fig. 2). The ternary map's low radio element concentrations may be the consequence of banded iron formation. However, because thorium is released when other materials weather and concentrates in iron oxides, they may appear to be rich in thorium. Radioactive anomalies may target areas of depletion or enrichment of one or more of the three radio element. In case of investigation at hand, High concentration of potassium (HCK) as dominated by red colouration may indicate high potassium contents above uranium and thorium; while its boundaries demarcated by white or yellow lines are likely the product of high-level potassic hydrothermal changes. Whereas, High concentration of Uranium (HCeU) in blue colour represents zones with a greater concentration of uranium over potassium and thorium and its demarcated boundaries may serve as uranium alteration zones. High concentration of Thorium (HCeTh) in green colours represents zones with a higher concentration of thorium over potassium and uranium. For mining purposes, it is also crucial to identify the areas with large concentrations of radioactive elements and the minerals that are associated with them. However, since these elements are extremely hazardous to humans and the environment, care must be taken during exploration processes.\u003c/p\u003e\u003ch2\u003ePotassium Thorium Ratio Maps\u003c/h2\u003e\u003cp\u003eK/eTh ratio anomalies, which are characterized by K enrichment in Figure (3), have a proportion of roughly 0.1227 to 0.2204 and indicated in red to pink colours, can be identified as zones of high hydrothermal alteration. Owing to the fact that potassium is more mobile than thorium. As thorium is typically considered to be highly immobile, The K/eTh ratio map's regions with low potassium concentrations may also indicate that thorium was likely mobilized in systems that have undergone hydrothermal alteration. The boundaries of these highly hydrothermal altered zones are accompanied by highly deformed moderate concentration of K/eTh in green and yellow colours and can be indicative of high structurally altered zones. Owing to the fact that K/eTh enrichment generally builds up around fault structures, which could be a sign of hydrothermal alteration. The towns of Zurmi, Maradun, and Mafara in the northeast and centre of the map, as well as the towns of Maru, Bingi, Dansadau, and Gusau in the south and southeast, contain the hydrothermal alteration zones in the medium to coarse-grained biotite granite schist. The high K/eTh ratio map results indicate the possibility of magnetite, garnet, tourmaline, and chloride mineral resources in the vicinity. Low thorium patterns can also be a sign of alteration in different rocks and along lithologic boundaries; hydrothermal fluids that leach thorium concentration are found in faults and fractures within these zones.\u003c/p\u003e\u003ch2\u003eF-Parameter\u003c/h2\u003e\u003cp\u003eOn the F-parameter map figure (4), anomalies classified as high concentration (HC) accurately depict hydrothermal alteration zones devoid of lithologies and weathering that resulted in signatures. Significantly fractured and hydrothermally altered areas within the study region are identified by an abnormally high F parameter (0.433–0.743). The research area can be broadly divided into three regions based on the distinctive characteristics on these maps: the low hydrothermally transformed region (LC) in the northwestern portion of the map, highly transformed region (HC) in the southern and northeastern parts and moderately affected region (MD) in the north east and south west of the research area, the majority of the hydrothermal alteration zones align with places that have seen artisanal mining activity in either the recent or recent past. In the northwestern section of the research region, which is a portion of the Sokoto sedimentary basin, there are prominent indications of an extremely low F parameter iindicating that there may be less alteration and potentially no significant mineralisation.\u003c/p\u003e\u003ch2\u003eK Deviation\u003c/h2\u003e\u003cp\u003eK-deviation figure (5) refers to the amount by which potassium concentrations in the study area deviate from a reference or average level. Since the K deviation value (5) is mostly found in the bedrock or shallow subsurface, it might be less impacted by lithological differences and by factors like vegetation. Variations in the magnetic signature of highs and lows, ranging from (0.053% to.723%), are revealed by K deviation. The ore samples from (A to K) taking for geochemical analysis where indicated in K –deviation map Fig.\u0026nbsp;4.14, where (MSP) represent mineralised sample point and BSP represent barren sample point. High magnetic anomalies are depicted with pink to red colours, while medium magnetic anomalies are represented with yellow green and low magnetic anomalies are depicted in blue colours. In mineral exploration, high K-deviation areas might be targets for further study as they could be linked to potassic mineralisation. On the other hand, low K-deviation zones might indicate a lack of such mineral resources. Potassium is a major constituent in many minerals, including feldspar, mica, and clay minerals. High potassium levels may also be correlated with areas of potential mineralisation or hydrothermal alteration. In some cases, elevated potassium values can be associated with areas of potassic alteration, which is common in porphyry systems or certain types of ore deposits especially copper and gold. High K values can signify the manifestation of specific rock types, such as granitic or volcanic rocks, which typically have higher potassium content. In contrast, low K values may indicate sedimentary rocks or zones where potassium has been leached or altered.\u003c/p\u003e\u003cp\u003eThe table (1) and Fig. 6 below presents the various oxide samples collected from the field and analyzed using the XRF machine.\u003c/p\u003e\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eshows sample of minerals with their respective oxides in percentage\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\"\u003e\n \u003cp\u003eOxides (wt%)\u003c/p\u003e\n \u003c/th\u003e\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\"\u003e\n \u003cp\u003eSamples\u003c/p\u003e\n \u003c/th\u003e\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eE\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eJ\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eK\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eCrustal abundance (wt %)\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eCaO\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e18.29\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e1.66\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e4.46\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e81.81\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e4.24\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eSiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e65.2\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e41.73\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e43.06\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e41.08\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e35.86\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e38.87\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e47.92\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e67.90\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e8.18\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e75.68\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e76.08\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e66.8\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eAl\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e8.38\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e19.29\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e24.60\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e15.97\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e31.13\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e14.61\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e15.38\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e4.40\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e11.47\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e9.40\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e15.05\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eFe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e2.39\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e9.49\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e15.45\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e19.95\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e81.81\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e7.38\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e4.09\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eSO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eK\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e7.01\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e25.39\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e23.54\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e2.62\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e9.87\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e2.03\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e3.19\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eMn\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e5.65\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eP\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eMgO\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e2.56\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e2.30\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eCr\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eCuO\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0005\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eTa\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0002\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eBaO\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eCl\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e953\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eRb\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003cp\u003eThe oxides and minerals that are used in geochemical analysis include the following: coal, galena, hornblende, kunzite, lead oxide copper, lepidolite/mica, lithium and black mica, lead oxide copper, lithium, malachite copper, malachite, manganese, muscovite, quartz white and rutile as shown in the Plate 4.1, below.\u003c/p\u003e\u003ch2\u003eValidation of Aero radiometric data sets using Geochemical Analysis\u003c/h2\u003e\u003cp\u003eThe suggested interpretations are constrained by other geological and geochemical findings, but geological and structural mapping based only on the analysis of radiometric field data is insufficient for both geo-scientific and economic applications due to uncertainty in the potential field interpretation \u003csup\u003e24\u003c/sup\u003e. This method offers a thorough understanding of how geological data and underlying structures are distributed spatially. Finding high-potential mineralisation zones is crucial, particularly those connected to tectonics and hydrothermal activity. These studies are important, but their value goes beyond data analysis; on-the-ground validation is also necessary to support the conclusions drawn from possible field data. Eleven sample points were chosen for geological ground verifications in this respect, at a number of prospective locations spread over several magnetic and radiometric domains. These samples were validated using X- ray florescence. It has been discovered that, out of eleven (11) samples four (4) i.e. (36.36%) were barren due to absent or insufficient while the remaining seven (7) i.e. (63.64%) contain economic minerals that can mine for profit.\u003c/p\u003e\u003ch2\u003eRelationship between Hydrothermal Alteration and Geochemical Analysis\u003c/h2\u003e\u003cp\u003ePlagioclase, orthoclase, quartz, muscovite, amphibolite, pyroxene, and other primary igneous rocks that were altered by hydrothermal processes were chemically replaced with altered minerals that were enriched in iron oxides, manganese oxide, titanium oxide, chromium oxide, hornblende, and galena and lead oxide; other mineralisation include copper mineralisation such as chalcopyrite, malachite and lithium mineralisation, which included kunzite, lepidolite, and lithium oxide (Plate 1).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study effectively integrates geological, geophysical, and geochemical techniques to identify and characterize mineralisation zones in Zamfara and its surroundings. The combination of aeromagnetic and aero radiometric methods, supported by XRF analysis, provides detailed insights into the region's structural complexity, mineral distribution, and hydrothermal alterations. These findings not only classify the site into magnetic lithologic units and reveal depth to magnetic sources but also highlight key mineralized trends and mineralized barren zones. Finally, this study underscores the potential of these techniques as reliable tools for structural mapping and detecting alteration zones, offering a robust framework for mineral exploration in similar terrains.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAccess to data\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003c/strong\u003e The Nigerian Geological Survey Agency is the source of the high-resolution aero radiometric data, which are not publicly accessible. Geochemical analysis data was obtained from Bayero University Kano Geology laboratory. However, with reasonable request, the first author can be able to provide the data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors received no funding was for this work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbubakar Muhammad Narimi: research, formal analysis, software, validation, conception, methodology, and writing original draft. Resources, data correction, review, and editing, was done by\u0026nbsp;A. A. Rafiu and U.D. Alhassan\u0026nbsp;visualization, project management, and supervision are all handled by\u0026nbsp;A.Idris Nda , A.A Bagare and Fahad Abubakar\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no conflicts of interest. All individuals who meet the criteria for authorship have been appropriately included\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbbass, A. A., Fidelis, I. K. \u0026amp; Shakarit, B. A. Interpreting the magnetic signatures and radiometric indicators within Kogi State, Nigeria for economic resources. \u003cem\u003eGeosyst. Geoenviron.\u003c/em\u003e\u003cstrong\u003e2\u003c/strong\u003e, 100157 (2023).\u003c/li\u003e\n\u003cli\u003eAbu-Alarm, T., Grosch, E. \u0026amp; Monsef, M. A. Pan-African shear zone-hosted gold mineralization in the Arabian-Nubian shield. \u003cem\u003eEGU General Assembly\u003c/em\u003e (2013). https://ui.adsabs.harvard.edu/abs/2013EGUGA.15.9893A/abstract\u003c/li\u003e\n\u003cli\u003eAugie, A. I. \u0026amp; Ridwan, M. M. Delineation of potential mineral zones from aeromagnetic data over eastern part of Zamfara. \u003cem\u003eSavanna J. Basic Appl. Sci.\u003c/em\u003e\u003cstrong\u003e3\u003c/strong\u003e, 60\u0026ndash;66 (2021). http://www.sjbas.com.ng\u003c/li\u003e\n\u003cli\u003eBowell, R. J. fotibmx, Lagos, L., De Los, H. C. R. \u0026amp; Declercq, J. Classification \u0026amp; characteristics of natural lithium resources. \u003cem\u003eElements\u003c/em\u003e\u003cstrong\u003e16\u003c/strong\u003e, 259\u0026ndash;264 (2020). http://dx.doi.org/10.2138/gselements.16.4.259\u003c/li\u003e\n\u003cli\u003eBurke, K., Freeth, S. J. \u0026amp; Grant, N. K. The structure and sequence of geological events in the Basement Complex of the Ibadan area, Western Nigeria. \u003cem\u003ePrecambrian Res.\u003c/em\u003e\u003cstrong\u003e3\u003c/strong\u003e, 537\u0026ndash;545 (1976).\u003c/li\u003e\n\u003cli\u003eChardon, D., Grimaud, J. L., Beauvais, A. \u0026amp; Bamba, O. West African lateritic pediments: Landform-regolith evolution processes and mineral exploration pitfalls. \u003cem\u003eEarth Sci. Rev.\u003c/em\u003e\u003cstrong\u003e179\u003c/strong\u003e, 124\u0026ndash;146 (2018).\u003c/li\u003e\n\u003cli\u003eDada, S. S. Proterozoic evolution of the Nigeria\u0026ndash;Boborema province. \u003cem\u003eGeol. Soc. Lond. Spec. Publ.\u003c/em\u003e\u003cstrong\u003e294\u003c/strong\u003e, 121\u0026ndash;136 (2008).\u003c/li\u003e\n\u003cli\u003eDanbatta, U. A. Precambrian crystal development in the northwestern part of Zuru schist belt, northwestern Nigeria. \u003cem\u003eJ. Min. Geol.\u003c/em\u003e\u003cstrong\u003e44\u003c/strong\u003e, 45\u0026ndash;56 (2008a).\u003c/li\u003e\n\u003cli\u003eDentith, M. C., Frankcombe, K. F. \u0026amp; Trench, A. Geophysical signatures of Western Australian mineral deposits: an overview. \u003cem\u003eExplor. Geophys.\u003c/em\u003e\u003cstrong\u003e25\u003c/strong\u003e, 103\u0026ndash;160 (1994).\u003c/li\u003e\n\u003cli\u003eDentith, M. \u0026amp; Mudge, S. T. \u003cem\u003eGeophysics for the Mineral Exploration Geoscientist\u003c/em\u003e (Cambridge Univ. Press, 2014).\u003c/li\u003e\n\u003cli\u003eDzukogi, A. N., Sanusi, Y. A., Mohammad, S. B. \u0026amp; Roko, A. Application of aeromagnetic data analysis \u0026amp; interpretations to investigate solid mineral potential in part of Northwest Nigeria. \u003cem\u003eInt. J. Earth Sci. Geophys.\u003c/em\u003e\u003cstrong\u003e8\u003c/strong\u003e, 057 (2022). http://doi.org/10.35840/2631-5033/7557\u003c/li\u003e\n\u003cli\u003eDzukogi, A. N. \u0026amp; Mahmud, M. B. Mapping of potential lithium mineral deposits in some parts of Northwestern Nigeria using magnetic and gamma-ray spectrometry data. \u003cem\u003eAfr. J. Environ. Sci. Renew. Energy\u003c/em\u003e\u003cstrong\u003e10\u003c/strong\u003e, 91\u0026ndash;108 (2023).\u003c/li\u003e\n\u003cli\u003eEkwueme, B. N. \u0026amp; Matheis, G. Geochemistry \u0026amp; economic value of pegmatites in the Precambrian basement of southeastern Nigeria. (Oxford \u0026amp; IBH Publishing, 1995).\u003c/li\u003e\n\u003cli\u003eFugro Airborne Surveys. Aero magnetic survey specification. \u003cem\u003eFurgo Airborne Publishers\u003c/em\u003e 1\u0026ndash;5 (2006).\u003c/li\u003e\n\u003cli\u003eGalbraith, J. H. \u0026amp; Saunders, D. F. Rock classification by characteristics of aerial gamma-ray measurements. \u003cem\u003eJ. Geochem. Explor.\u003c/em\u003e\u003cstrong\u003e18\u003c/strong\u003e, 49\u0026ndash;73 (1983). https://doi.org/10.1016/0375-6742(83)90080-8\u003c/li\u003e\n\u003cli\u003eJenkins, R. \u003cem\u003eAn Introduction to X-Ray Spectrometry\u003c/em\u003e (Heyden, London, 1976).\u003c/li\u003e\n\u003cli\u003eJenkins, R., Gould, R. W. \u0026amp; Gedcke, D. \u003cem\u003eQuantitative X-Ray Spectrometry\u003c/em\u003e (Marcel Dekker, New York, 1981).\u003c/li\u003e\n\u003cli\u003eMichael, D. \u0026amp; Stephen, T. M. \u003cem\u003eGeophysics for the Mineral Exploration Geoscientist\u003c/em\u003e (Cambridge Univ. Press, London, 2015).\u003c/li\u003e\n\u003cli\u003eMinty, B. R. S. The fundamentals of airborne gamma-ray spectrometry. \u003cem\u003eAGSO J. Aust. Geol. Geophys.\u003c/em\u003e\u003cstrong\u003e17\u003c/strong\u003e, 39\u0026ndash;50 (1997).\u003c/li\u003e\n\u003cli\u003eMorrell, A. E., Locke, C. A., Cassidy, J. \u0026amp; Mauk, J. L. Geophysical characteristics of adularia-sericite epithermal gold-silver deposits in the Waihi-Waitekauri region, New Zealand. \u003cem\u003eEcon. Geol.\u003c/em\u003e\u003cstrong\u003e106\u003c/strong\u003e, 1031\u0026ndash;1041 (2011).\u003c/li\u003e\n\u003cli\u003eObaje, N. G. \u003cem\u003eGeology and Mineral Resources of Nigeria\u003c/em\u003e Vol. 120 (Springer, 2009).\u003c/li\u003e\n\u003cli\u003eObaje, N. G., Adukub, M. \u0026amp; Yusuf, I. The Sokoto Basin of Northwestern Nigeria: A preliminary assessment of the hydrocarbon prospectivity. \u003cem\u003ePetrol. Technol. Dev. J.\u003c/em\u003e\u003cstrong\u003e7\u003c/strong\u003e, 1\u0026ndash;15 (2013). https://doi.org/10.4236/ojg.2023.138038\u003c/li\u003e\n\u003cli\u003eOgah, A. J. \u0026amp; Abubakar, F. Solid mineral potential evaluation using integrated aeromagnetic and aeroradiometric datasets. \u003cem\u003eSci. Rep.\u003c/em\u003e\u003cstrong\u003e14\u003c/strong\u003e, 1637 (2024).\u003c/li\u003e\n\u003cli\u003ePortnov, A. M. Specialization of rocks towards potassium and thorium in relation to mineralization. \u003cem\u003eInt. Geol. Rev.\u003c/em\u003e\u003cstrong\u003e29\u003c/strong\u003e, 326\u0026ndash;344 (1987).\u003c/li\u003e\n\u003cli\u003eRibeiro, V. B. \u0026amp; Mantovani, M. S. M. Gamma spectrometric and magnetic interpretation of caba\u0026ccedil;al copper deposit in Mato Grosso (Brazil): implications for hydrothermal fluids remobilization. \u003cem\u003eJ. Appl. Geophys.\u003c/em\u003e\u003cstrong\u003e135\u003c/strong\u003e, 223\u0026ndash;231 (2016). https://doi.org/10.1016/j.jappgeo.2016.10.016\u003c/li\u003e\n\u003cli\u003eSalau, S. L., Danbatta, U. A. \u0026amp; Agunleti, Y. S. The interpretation of aeromagnetic \u0026amp; satellite imagery for structures coincident with gold mineralization in Anka Schist Belt, Northwestern Nigeria. \u003cem\u003eJ. Appl. Geol. Geophys.\u003c/em\u003e\u003cstrong\u003e4\u003c/strong\u003e, 29\u0026ndash;34 (2016). https://www.iosrjournals.org/iosrjagg/papers/Vol.%204%20Issue%205/Version-2/E0405022934.pdf\u003c/li\u003e\n\u003cli\u003eSani, A. A., Augie, A. I. \u0026amp; Aku, M. O. Analysis of gold mineral potentials in Anka Schist Belt, Northwestern Nigeria using aeromagnetic data interpretation. \u003cem\u003eJ. Niger. Assoc. Math. Phys.\u003c/em\u003e\u003cstrong\u003e52\u003c/strong\u003e, 291\u0026ndash;298 (2019). https://www.researchgate.net/publication/337951812\u003c/li\u003e\n\u003cli\u003eSaunders, D. F., Burson, K. R., Branch, J. F. \u0026amp; Thompson, C. K. Relation of thorium-normalized surface and aerial radiometric data to subsurface petroleum accumulations. \u003cem\u003eGeophysics\u003c/em\u003e\u003cstrong\u003e58\u003c/strong\u003e, 1417\u0026ndash;1427 (1993)\u003c/li\u003e\n\u003cli\u003eTawey, M. D., Adetona, A. A., Alhassan, U. D., Rafiu, A. A., Salako, K. A. \u0026amp; Udensi, E. E. Aeroradiometric data assessment of hydrothermal alteration zones in parts of North Central Nigeria. \u003cem\u003eAsian J. Geol. Res.\u003c/em\u003e\u003cstrong\u003e4\u003c/strong\u003e, 1\u0026ndash;16 (2021).\u003c/li\u003e\n\u003cli\u003eTelford, W. M., Geldart, L. P. \u0026amp; Sheriff, R. E. \u003cem\u003eApplied Geophysics\u003c/em\u003e (Cambridge Univ. Press, 1990).\u003c/li\u003e\n\u003cli\u003eUsman, M. A. \u0026amp; Ibrahim, A. A. Petrography \u0026amp; geochemistry of rocks of Northern Part of Wonaka Schist Belt, Northwestern Nigeria. \u003cem\u003eNiger. J. Basic Appl. Sci.\u003c/em\u003e\u003cstrong\u003e25\u003c/strong\u003e, 87\u0026ndash;99 (2017). http://dx.doi.org/10.4314/njbas.v25i2.10\u003c/li\u003e\n\u003cli\u003eUyanık, N. A., \u0026Ouml;nc\u0026uuml;, Z., Uyanık, O. \u0026amp; Bozcu, M. Determination of alteration zones and geological unit limits using natural radioactivity properties of Sandıklı-Suhut areas. \u003cem\u003eJ. Appl. Geophys.\u003c/em\u003e\u003cstrong\u003e196\u003c/strong\u003e, 104525 (2022).\u003c/li\u003e\n\u003cli\u003eWoakes, M., Rahaman, M. A. \u0026amp; Ajibade, A. C. Some metallogenetic features of the Nigerian basement. \u003cem\u003eJ. Afr. Earth Sci.\u003c/em\u003e\u003cstrong\u003e6\u003c/strong\u003e, 655\u0026ndash;664 (1987)\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Plate 1","content":"\u003cp\u003ePlate 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Solid minerals, hydrothermal alteration zones, Minerilisation zones, Barren Mineralisation","lastPublishedDoi":"10.21203/rs.3.rs-7464005/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7464005/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe study area covers Zamfara and its surrounding regions. It lies between latitude 11\u0026deg;00'N and 13\u0026deg;00'N and longitude 5\u0026deg;00'E and 7\u0026deg;00'E. Geologically, the region consists of Migmatite Gneiss Complex (MGC), Schist Belts and a portion of the Sokoto Basin. It is considered to be one of the richest in mineral resources in Nigeria, comprising of lithium, gold, zinc, copper, and lead. However, some mineralisation and hydrothermal alteration zones identified in the area may lack economically viable ore due to low-grade or dispersed minerals. Consequently, the indiscriminate activities of artisanal mining resulted into a lot of abandoned pits and trenches which facilitate the environmental degradation and loss of farmlands. Petrographic analysis as proposed by some researchers also reveals ambiguous mineral structures; compared X-ray fluorescence (XRF) that provides clearer insights by identifying and quantifying their elemental composition of the minerals.\u003c/p\u003e\u003cp\u003eAero radio metric method was used for mapping hydrothermal alteration zones and concentration of radio element related to solid minerals through, radio element ratio maps, ternary map, F-parameter and K deviation. Geochemical analysis was used to validate the chemical constituents and percentage of minerals present using X-ray florescence (XRF). Hydrothermally altered zones were indicated by an anomalously high F parameter (0.328\u0026ndash;0.723) and high K/eTh ratio of roughly (0.1153 to 0533). The radiometric ternary image reveals superior concentration of individual radioelement at their respective areas. On the other hand, X-ray florescence technique pointed out significant percentage concentrations of major oxides by weight, including CaO (18.29%), Al₂O₃ (31.13%), SiO (76.0) Fe₂O₃ (81.81%), SO₃ (0.18%), K₂O (25.29%), Mn₂O₃ (1.67%), P₂O₅ (0.91%), MgO (2.56%), Cr₂O₃ (1.28%), and CuO (0.04%) across multiple sampled locations. and other barred areas in some identified mineralisation zones. In conclusion, these findings highlight key mineralized trends and barren hydrothermal and mineralisation zones. The study underscores the potential of these techniques as reliable tools for structural mapping and detecting alteration zones, offering a robust framework for mineral exploration in similar terrains.\u003c/p\u003e","manuscriptTitle":"Evaluation of solid mineral potentials in north western parts of Nigeria using aero radiometric and geochemical data sets","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 07:33:56","doi":"10.21203/rs.3.rs-7464005/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4163016b-8482-4c3b-ba1f-b29058c3babd","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":55066210,"name":"Earth and environmental sciences/Environmental sciences"},{"id":55066211,"name":"Earth and environmental sciences/Solid earth sciences"}],"tags":[],"updatedAt":"2026-03-04T05:25:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-23 07:33:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7464005","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7464005","identity":"rs-7464005","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}