Integrated interpretation of ground magnetic (GM), electromagnetic very low frequency (EM-VLF), electrical resistivity (ER), and induced polarization (IP) data was carried out in this study to investigate the mineralization potentials of the Bangalela area, Central Benue Trough, Nigeria. The GM data was reduced to the equator (RTE), followed by the application of edge enhancement filtering such as first vertical derivative (FVD), to locate the contacts of linear geological features that may control mineralization in the study area, and also to isolate potential prospective exploration targets for lead-zinc deposits. Acquisition of EM-VLF and ER/IP survey were employed to further investigate the delineated zones of interest to ascertain their potentials for mineralization occurrence. The results revealed potential prospective mineralization zones, controlled by the identified conductive structures trending in directions that conforms with known tectonic orientations in the Benue Trough. These isolated mineral targets characterized by chargeability values greater than 15 msec were confirmed to be lead-zinc ore deposits on fresh core samples obtained from two drill points along the interpreted geoelectrical profiles. Probable ore reserve computation showed that the lead-zinc deposit in the Bangalela area contain mineralization volumes of high economic value.
Research Article
Exploratory assessment of Lead-Zinc mineralization in Bangalela area Central Benue Trough Nigeria using integrated ground geophysical data
https://doi.org/10.21203/rs.3.rs-4616375/v1
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Lead-zinc mineralization
Ground geophysical data
Bangalela area
Central Benue Trough
The current global energy transition trends which promote low-carbon emissions towards attaining carbon neutrality by 2050, has triggered increased growing demands for critical minerals that will power the global sustainable industrial future. This has rekindled renewed interests to revamp Nigeria’s solid mineral sector, which is believed to be the promising frontier that will drive the nation’s sustainable economic development (Eboh 2023; Tomori 2024).
Nigeria is endowed with abundant solid mineral enrichment, especially lead-zinc ores which often occur together, in association with copper and silver. Commercial quantities of these critical metals are known to occur in the northeastern and central parts Nigeria, with estimated reserves potentials greater than 10 million tons of lead, and 80,000 tons of zinc reported by the Federal Ministry of Solid Minerals Development in 2015. Unfortunately, Nigeria is yet to reach full potentials in solid mineral exploration and development compared to countries with huge mineral endowments like Australia, South Africa, and Chile, due to unavailability of well-documented and accessible geoscience/mineral exploration data that will attract investments and drive development of these precious metals (Okunlola 2005). Furthermore, poor implementation and enforcement of policies on environmental, safety, and health, as well as the country’s inability to checkmate illegal activities of artisanal miners are some other reasons contributing to low outputs from Nigeria’s solid mineral sector. There is need to gather detailed geoscientific prospecting data to guide exploration and exploitation of these critical mineral deposits.
Geophysical techniques like the ground magnetic surveys, electromagnetic very low frequency (EM-VLF), electrical resistivity (ER), and induced polarization (IP) methods can be used to assess the potentials of an area for metallic sulphide ore deposits (Nabighian et al. 2005; Janos 2011; Moreira et al. 2012; Lui 2012; Yusuf et al. 2022). These viable geophysical tools have been deployed in prospecting for mineralization zones in the Benue Trough and other parts of Nigeria (Okunlola 2005; Offor et al. 2020; Osinowo et al. 2020; Adebiyi et al. 2021; Sikakwe and Amah 2021; Amigun et al. 2022). The magnetic method is an economical geophysical technique used to delineate near-surface and deep-seated structural features that are capable of hosting metallic sulphide deposits in mineral prospecting projects (Agagu and Adighije 1983; Mohammadzadeh-Moghaddam et al. 2016; Ejiga et al. 2022; Eldousoky et al. 2022; Elem and Anakwuba 2022; Alfaifi et al. 2023). The EM-VLF method is a fast, low-cost technology for detecting mineralized faults and fractures systems (Yusuf et al. 2022). It is a powerful tool for mapping ore-filled geological structures located at shallow depth intervals within the subsurface (Zhang et al. 2007), and has proven successful in identifying mineralization zones in weathered basement terrains (Victor et al. 2015). The ER method measures the subsurface resistivity/conductivity contrasts, and is an effective technique for easy detection of highly conductive metallic ore minerals (Park et al. 2009; Goto et al. 2013; Ishizu et al. 2019; Batista-Rodríguez and Pérez-Flores 2021). The IP method records changes in the chargeability of subsurface materials (Dusabemariya et al. 2020). The technique has been found effective for locating metallic sulphide deposits because of its capability to discriminate conductive or semi-conductive bodies disseminated within the host rock (Gurin et al. 2019; Dusabemariya et al. 2020; Ali et al. 2020a, 2020b; Mashhadi 2022). By combining the attributes from ER and IP measurements, mineralized bodies distributed within the country rocks can be isolated with some confidence (Heritiana et al. 2019).
Lead-zinc mineral deposits in the Benue Trough is known to occur as lodes and vein fillings along a narrow NE-SW trending structural belt that stretches from Ishiagu in the south to Gombe in northeast (Fischer et al. 1983; Ezepue 1984; Akande et al. 1992). In the Central Benue Trough, Akande et al. (1988) and Ogundipe (2017) reported lead-zinc-fluoride mineralization within carbonate sequences of the Asu River Group in Arufu and Akwana areas. These ore bodies exist as stratiform, vein-type or porosity infillings that cross-cuts the main orientation of the carbonate country rocks (Fig. 3). The nature of these widely disseminated ore bodies is an indication that their origin can be linked with the tectonic history of the Benue Trough (Akande et al. 1988). Knowledge of the subsurface distribution of these economic minerals in other parts of the Central Benue Trough are yet to be fully established. Detailed information on the quantity and reserves estimates of these highly sought-after metallic materials are lacking. There is need for detailed geophysical studies to ascertain the mineralization potentials of the Central Benue Trough to identify areas with high exploration prospectivity.
The present study utilizes ground magnetics, EM-VLF, ER, and IP data to assess the potentials of lead-zinc mineralization in Bangalela area, Central Benue Trough Nigeria. The integrated geophysical approach adopted in this study will be vital to establish the presence lead-zinc deposits and also uncover the geometry of the mineralized ore bodies distributed within the host rocks. The study will also serve as guide for mineral exploration projects in the region and other adjoining areas.
Location and geology of the study area
The study area lies within the Central Benue Trough (Fig. 1), which is the middle sub-division of the Benue megarift structure that stretches over 800 km from the northern part of Niger Delta Basin to the southern part of Chad Basin in northeastern Nigeria. Tectonic evolution of the Benue Trough has been linked with the Early Cretaceous block movements that created the South Atlantic Ocean, as Africa and South America Continents pathed ways (Burke 1976; Akande et al. 1989; Benkhelil 1989; Obaje 2009). Geoscientists have argued the mechanisms behind the formation of this complex rift system due to sparse data availability for regional studies (Benkhelil 1989). However, it is widely accepted that the Benue Trough is the third failed arm (or aulacogen) of a triple rift junction (RRR) that resulted from tensional movements associated with the Late Mesozoic break-up of the Gondwana Supercontinent (Burke et al. 1972; Olade 1975; Benkhelil 1989). Subsequent re-organization and re-orientation of the African crustal blocks resulted in short-lived compressional episodes responsible for crustal shortening of the stretched subsiding basin, and folding of the sediments (Maurin et al. 1986; Benkhelil et al. 1988).
Tectonostratigraphic framework of the Benue Trough includes sediments of Cretaceous age that overly the crystalline basement rocks in an unconformable manner (Fig. 2). Sediments of Tertiary age can be found in the Northern Benue Trough and the Niger Delta Basin (Benkhelil 1989). Detailed description of the lithostratigraphic successions and sequences in the Benue Trough have been provided in classical works (e.g., Nwachukwu 1972; Benkhelil 1989; Akande et al. 1989; Obaje 2009).
The study involved field geophysical and geological studies to acquire ground magnetic, EM-VLF, ER and IP data over the study area along selected profiles, using field equipment including Overhauser MAG/VLF, ABEM SAS 1000 Terrameter, Global Positioning System (GPS), Compass, etc. The measurements and readings were recorded on a field notebook. The acquired dataset was processed using software packages including Oasis Montaj, ArcGIS, RES2DINV, and 3DMine. Core samples were extracted from a borehole drill point to validate our findings on the identified zone characterized by high resistivity and chargeability response in the study area.
Ground magnetic (GM) data
The basics of the magnetic method of geophysical exploration is centered on identifying variations in the magnetic field of the Earth due to subsurface causative sources (Bevan 2006; Scott 2014). High magnetic susceptibility bodies like ultra mafic rocks, metallic sulphide minerals, metal pipes, electric cables, etc., buried deep underground can cause observable changes in the Earth’s magnetic field (Scott 2014; Cozzolino et al. 2018; Yusuf et al. 2022). Earth materials that are rich in magnetite content (ferromagnetic minerals) are characterized by high magnetization sensitivity, and can be easily detected with the magnetic method (Sandgren and Snowball 2002; Evans and Heller 2003; Cullity and Graham 2011; Babker 2019).
In ground magnetic surveys, high precision magnetometers are utilized to measure the total magnetic field intensity of the Earth. Usually, a base station with fixed magnetometer instrument is set-up to record the daily changes in magnetic field of the Earth which is often affected by solar activity and diurnal variations. Measurements taken with a roving magnetometer can be corrected using the base station readings at the end of the survey (Scott 2014).
In this study, the total magnetic field measurements were taken at 10 m station interval along a 3 km profile. The data was acquired in real time using a portable Overhauser magnetometer, with in-built GPS receivers in the rover unit, at 3 m height clearance and 200 m profile spacing. At every interval of 1 s, the instrument digitally recorded the coordinates, total magnetic field intensity, and the time of each measurement. The traditional stop and measure mode which provides full sensitivity obtainable with a proton magnetometer was employed in the data acquisition process. Readings from the base station magnetometer situated outside the survey area was used to conduct diurnal corrections of the data acquired from the rover unit. The area selected for base station was magnetically quiet, hence, free from moving automobiles and is not located close to or on top of any major outcrop (Fig. 4). The final database was geo-referenced to the WGS-84, UTM-Zone 32N datum, and the values were gridded using the kriging algorithm in Oasis Montaj software. The obtained total magnetic intensity (TMI) grid was reduced to the equator (RTE), before the application of polynomial filtering technique to eliminate long wavelength (or regional) anomalies and enhance shorter wavelength signatures emanating from near-surface geological features. The resultant residual magnetic intensity (RMI) map was further subject to structural enhancement filtering like the first vertical derivative (FVD) derivative to located the contacts of linear geological features that may control ore mineralization in the area.
Electromagnetic very low-frequency (EM-VLF) data
Electromagnetic very low frequency (EM-VLF) surveys are based on the principles of the electromagnetic (EM) method where a transmitter is used to trigger primary fields that generate small time-varying voltages in the earth. These voltages cause small current flows that vary with time where the earth is conductive, creating secondary electromagnetic fields of their own (Haldar 2013; Scott 2014). The primary and secondary fields combine to detect the presence of subsurface conductive bodies, and also shed light on their geometry and electrical properties (Yusuf et al. 2022). The EM-VLF frequencies are typically within the ranges of 15 and 30 kHz.
The EM-VLF survey readings for this study was acquired using the Overhauser magnetometer (VLF option) at 10 m station spacing along the profile of 3km width, covering a total of 300 stations. The survey was designed to measures the field strength and phase displacement across suspected fracture zones or conductive bodies in the subsurface that were targeted by the magnetic profiles (Telford et al. 1990). The VLF transmitter HWU located in La Blanc, France, operating at a frequency of 18.3 kHz with coordinates 46N37-001E05, was selected as the source for the entire VLF survey because it provided a field which is approximately perpendicular to the strike direction of the envisaged geological structure beneath the ground surface in the study area. The newly acquired EM-VLF data was processed using the Oasis Montaj and KHFFILT software. The results were presented as plots of stacked VLF profiles and 2D contour maps, and were compared to the interpreted magnetic structures for mapping of conductive zones.
Electrical resistivity (ER) and induced polarization (IP) data
Electrical resistivity (ER) method, which measures the resistance properties of the earth to the passage of electric current, is a geophysical exploration technique that have found wide applications in environmental science, foundation studies, archaeology, etc. (Daily et al. 2004; Zhou and Kanl 2018; Ducut et al. 2022). This technique is based on the principle of electrical resistivity differences of subsurface materials due variations in geological properties. The ER method produces better images of the subsurface by utilizing electrical resistivities measurements of different rock materials. Usually, ER survey is conducted by introducing electric current into the ground via two current electrodes, and measuring the potential difference due to the flow of current through a pair of potential electrodes. This set-up enables enhanced measurement of the electrical resistivity distributions in the subsurface (Ali et al. 2023).
On the other hand, induced polarization (IP) data can be obtained in the time domain or frequency domain. However, the time domain acquisition was used in this study. This technique records the voltage decay between two non-polarizable electrodes induced when the direct current passing through them is switched off (Dahlin et al. 2002; Gazoty et al. 2012; Dakir et al. 2019). After the current supply is cut-off, the voltage slowly decays and takes some time to before it gets to zero (Gazoty et al. 2012). This suggests that charge is stored up in the rocks. This property is known as of the chargeability (M), given in milliseconds or in millivolt/volt (mV/V) (Ali et al. 2023).
In this study, the ER/IP surveys were combined to obtain detailed information on the rock types, geological features, and chargeability of subsurface materials, which translates to the identification of mineralized ore bodies in the study area. The data were acquired using ABEM SAS 1000 Terrameter, a GPS to record the coordinates of the profiles. Five (5) ER/IP measurements were carried out along E - W profiles that cuts across two major N - S trending linear features delineated from the magnetic and EM-VLF data interpretation. The acquired ER/IP data were inverted using RES2DINV and 3DMine software, to provide 2D and 3D imaging for improved modeling of the subsurface geology (Gourdol et al. 2021; Hasan et al. 2021).
Ground magnetic (GM) survey interpretation
The total magnetic intensity (TMI) and residual magnetic intensity (RMI) maps of the study area are presented in Fig. 5. The maps showed variations in magnetic susceptibilities of different rocks beneath the study area. The TMI anomalies range from 33851 nT to 33865 nT, while the RMI anomalies vary from 116 nT to 126 nT. Major trends of the anomalies are in the NW-SE, NE-SW and E-W directions, depicting the dominant structural trends in the Benue Trough. High amplitude (red) anomalies trending in the NW-SE direction are observed in the northcentral part of the two maps, while low amplitude (blue) anomalies dominate the southwestern and eastern portions of the study area. The anomalies show sharp gradients, suggesting that they may be emanating from high-angle linear subsurface discontinuities like fractures or lineaments (Okoro et al. 2022). The higher amplitude responses observed in the study area were interpreted to correspond with conglomerate ironstones, while the lower amplitude responses correlated with shale units. In general, the high magnetic responses suggested the presence of rocks rich in magnetite mineral content that are associated with hydrothermal mineral alterations in the study area.
Figure 6 is the FVD map of the study area. The map highlighted the edges of linear geological features that may influence the formation of metallic sulphide mineralization in the study area. The linear features were observed as faults on highly fissile shale outcrop exposures in the study area (Fig. 7). These faults may have acted as conduits or path ways for the flow of hot mineralized hydrothermal waters from deep underground, that altered the composition of the rocks and deposited lead-zinc minerals in the study area (NGSA 2008). A major striking feature in the area is the regional NE - SW trending lineament located at the southeastern part of the FVD map. Lineaments with similar orientation have been mapped from aeromagnetic data over the Middle Benue Trough by Anudu et al. (2019). NE – SW trending lineaments in the Benue Trough are believed to form the major boundaries of smaller structural basins (mini-basins) and are mostly dominate the edges (margins) of the trough, where they exerted large control on the development of mini-basins due to basement re-organizations in response to tectonic movements during the evolutionary stages of the Benue Trough (Anudu et al. 2019). These lineaments have also been identified as NE – SW striking faults on seismic sections in the adjoining Chad Basin in northeastern Nigeria, where they occur as major basin bounding faults (Avbovbo et al. 1986; Suleiman et al. 2017).
Electromagnetic very low frequency (EM-VLF) survey interpretation
Stacked profile plots of the raw data (In-Phase and Quadrature components), Fraser filtered and the Karous-Hjelt (K-H) filter for each of the survey lines are presented in Fig. 8. Interpretation of these plots gave insights on the location of potential prospective conductive bodies beneath the study area.
The In-Phase data showed crossovers with the horizontal axis, with prominent negative peaks over suspected conductive zones. Negative inflections were also observed on the Quadrature component at points of In-Phase crossovers, suggesting the presence of a good conductor enclosed in a lesser conductive body (Abdullahi and Osazuwa 2010). The Fraser filter plot also showed peak amplitude signatures over zones along the profiles that are underlain by anomalous steep dipping features or large-sized causative source bodies. Low frequency broader amplitudes, suggests causative sources located deeper in the subsurface. The spatial distribution of subsurface current density with pseudo-depth is displayed on the Karous-Hjelt filter plot, which revealed that positive peaks in the Fraser filtered plot coincided with positive current densities, while negative peaks aligned with negative current densities. In general, the higher current density values are related to conductive structures (Karous and Hjelt 1983). Conductive zones appeared as red or yellow color, while resistive zones were displayed as blue color on the Karous-Hjelt model.
Generally, the basic principle in EM-VLF interpretation is that the higher the In-Phase values of the anomaly, the greater the conductivity of the underlying structures in relation to the surrounding rock. Some of the anomalies were characterized by sharp amplitudes and high intensity, while others exhibited broad amplitudes and lower intensity. Suspected mineralized veins were delineated on the gridded survey area using characteristic coincidence of positive inflections on filtered In-Phase anomaly and were further interpreted on current density maps (Becken and Pedersen 2003). Because the host rocks were characterized by poor conductivity signatures, it was easier to interpret the EM-VLF anomalies caused by the mineralized veins. Brief explanation of the profiles is given below.
Profile line 1
This traverse covered a total length of 3000 m, on an E - W orientation straddling the suspected alteration zones and structures mapped from the ground magnetic data interpretation. Inversion of the acquired data points yielded current density (conductivity) values ranging between − 10 to + 10%, with optimum depths of about 45 m (Fig. 8a). Six (6) zones of high conductivity (current density) signatures were identified along this profile on the horizontal distance between 0–250 m, 300–900 m, 875–1500 m, 1300–1750 m, 1750–2375 m, and 2500–2750 m. These anomalous zones were designated a, b, c, d, e, and f. The high conductive zone a at the distance between 0–250 m displayed anomalously high amplitude In-Phase signatures, indicating high potentials for the presence of conductive minerals which may occur in the highly fractured non-conductive shale host rocks. This zone is delineated in this study for further detailed mineral exploration studies.
Profile line 2
This profile covered a total length of 3000 m, and 300 data points which were inverted to produce current density (conductivity) ranges of -10 to + 10% with optimum depths of about 48 m (Fig. 8b). Three (3) anomalous zones of high conductivity were identified and designated a, b, and c, at the horizontal distances of 200–1100 m, 1250–1800 m, and 2190–2300 m. Zone a is interpreted to be hosted by highly indurated shales that has imprints of associate minerals such as pyrite, siderite and chalcopyrite, along with veinlet of lead and quartz. Zone b is interpreted as conductive zone with relatively high amount of gange minerals like quartz; while Zone c is interpreted as altered shale consisting of associated minerals of lead deposits and veinlets.
Profile line 3
Inversion of the 300 data points acquired over a horizontal distance of 3000 m yielded current density (conductivity) values ranging between − 10 to 10%, with optimum depths of around 45 m (Fig. 8c). Three zones of high conductivity were identified and designated a, b, and c. Zone a was observed along the profile between 1150–2750 m, with depths extending beyond 45 m. Zone b is interpreted as an indurated shale with associate minerals such as pyrite, siderite and chalcopyrite, along with veinlet of lead and quartz. Zone c is interpreted as altered shales consisting of low percentage of associated lead mineral deposits and veinlets, and high concentration of gange mineral.
Profile line 4
This profile covered a total length of 2580 m, over which 258 data points were acquired. The inverted data produced current density (conductivity) ranges of -10 to + 10%, with optimum depths of around 40 m (Fig. 8d). Four (4) zones of high conductivity (a, b, c, and d) were identified along this profile. These conductive zones were interpreted as indurated shales with associated ore minerals like pyrite, siderite and chalcopyrite, along with veinlet of lead and quartz, and gange minerals.
Profile line 5
This profile has a total length of 2960 m. The inversion of 296 data points acquired over this profile produced current density (conductivity) ranges of -10 to + 10%, with optimum depths of around 40 m (Fig. 8e). Four zones of high conductivity (current density) were identified along this profile (a, b, c, and d). Anomaly a is interpreted as having a thick conductive body that is surrounded by the broader anomaly b, which has lower intensity. The same way, anomaly c is enclosed in the lower intensity anomaly d. Anomaly a is interpreted to be an indurated shale with associate minerals such as pyrite, siderite and chalcopyrite, along with veinlet of lead and quartz. Anomaly b is interpreted to be a conductive zone with relatively higher amounts of gange minerals. The same interpretation is given for anomaly c and d. The low current density zones (blue color) are interpreted to be fresh shale units with no mineral alteration.
Profile line 6
This profile has a total length of 3000 m. A total of 300 data points was used for the inversion and has produced current density (conductivity) ranges of -10 to + 10% with optimum depths of around 45 m (Fig. 8f). The identified anomalous zones a and b were interpreted to be an indurated shale with conductive bodies associated with minerals such as pyrite, siderite and chalcopyrite, along with veinlet of lead and quartz. The low current density zones were also interpreted to be as fresh shale units.
Profile line 7
This profile has a total length of 2970 m. The 297 data points used for the inversion produced current density (conductivity) ranges of -10 to + 10%, with optimum depths of around 45 m (Fig. 8g). Four high conductivity (current density) zones were identified along this profile. Anomaly a is interpreted to be highly conductive and could have resulted from conductive minerals and/or water that percolate to the subsurface through surface fault systems observed around that area. Anomaly b, c, and d are surrounded by current density range of 0 to 2.5%. This surrounding zone is interpreted as the contact aureole formed by the hydrothermal fluid that filled the faults and fractures. They may consist of associate minerals. Anomaly d is interpreted as conductive zone with relatively higher amount of conductive body than gange mineral. The low current density zones are interpreted as fresh shale units.
Profile line 8
This profile covered a total length of 2980 m. Inversion of the acquired 298 data points produced current density (conductivity) ranges of -10 to 10%, with optimum depths of around 45 m (Fig. 8h). Four zones of high conductivity (current density) were identified along this profile. The anomalies (a, b, c, and d) were interpreted as highly conductive zones with relatively higher amount of conductive body than gange mineral. The anomalous zones are surrounded by lower current density typical of the contact aureole formed by the hydrothermal fluid that filled the faults and fractures. The lowest current density zones were interpreted as fresh shale units.
Frasier filter 2D map
Figure 9 shows the 2D Fraser filter map of the study area. The map revealed variations in high and low amplitude anomaly values ranging from − 10.7 to 9.1, reflecting differences in conductivities of the underlying geological units and structures. The high amplitude zones aligned with the delineated linear features in the study area, which trend predominantly in the NE – SW, N – S, and NW – SE directions. These structural orientations conform with major tectonic trends in the Middle Benue Trough (Ajakaiye et al. 1986; Olasehinde et al. 1990; Yusuf et al. 2022). The linear features displayed different degrees of conductivity, depicting ore-filled fractures and/or mineralized zones in the study area. A total of nine (9) conductive linear features were identified and designated AEM-1 to AEM-9. The longest conductive linear feature is AEM-1, which has a length of about 2330 m, trending NE - SW and stretches from Profile line 1 to Profile line 6. AEM-1 has a very strong conductive response (> 0.9 to 9.1), and was also observed within the Karous-Hjelt filter model section of Profile lines 1, 4, 5 and 6. This feature was delineated as a potential lead-zinc mineralized target in the study area. AEM-2 conductive structure cuts across Profile lines 2, 3 and 4. This feature has a total length of about 1080 m, trending in the NE-SW, with a broad conductive anomaly towards its northern end. AEM-3, located to the west of AEM-1, has a length of 1500 m. This feature cuts across Profile lines 3, 4, 5, 6 and 7. AEM-4 is a Y-shaped conductive linear feature that has a length of 1300 m, extending through Profile lines 4, 5, 6 and 7. Another Y-shaped conductive feature is AEM-5. It has a higher conductivity level than AEM-4. AEM-5 has a length of about 1400 m and cuts across Profile lines 5, 6 and 7. AEM-6 has a length of 1320 m, cutting through Profile lines 3, 4, 5 and 6. The conductivity across this structural feature is interpreted as truncated, hence forming some sought of a pinch and swell structure. Similar conductive feature are AEM-7 and AEM-8 which has lengths of 612 m and 1000 m, respectively. AEM-7 cuts across Profile lines 1 and 2, while AEM-8 cuts across Profile lines 1, 2 and 3. They are both located to the south of AEM-6. AEM-9 has a broad anomaly with a length of about 500 m. The anomalies from the identified linear features may be attributed to the presence, as well as architectural geometry, of mineralized veins, fissures, fractures, or fault systems beneath the study area. However, the two main anomalies of interest (AEM-1 and AEM-3) formed the basis for the ER-IP survey in the study (Fig. 10).
Electrical resistivity and induced polarization (ER/IP) survey interpretation
Res/IP line 1
The 2D resistivity and chargeability models revealed several significant chargeable bodies, with chargeability > 140 msec and resistivity values ranging from 13.2 to 434 Ωm (Fig. 11). The chargeable bodies were grouped into high chargeability – high resistivity anomalies, and high chargeability – low resistivity anomalies. The identified bodies designated A, B, C, D, E, F, G, and H showed high chargeability with varying resistivity values. Chargeable bodies A, C, F, G and H are characterized by low resistivity (21.7 to 59 Ωm) and high chargeability signatures (40 to < 100 msec); while the chargeable bodies B, D, E and K are characterized by moderate to high resistivity (80 to 263 Ωm) and high chargeability values (> 100 msec).
In electrical imaging surveys, mineralization zones are generally characterized by high chargeability with low resistivity signatures. Hence, the anomalous bodies of major interest delineated along this profile include A, C, F, G and H. Lead-zinc ore bodies occur with associated minerals like quartz, siderite etc., which are generally highly resistive minerals. Therefore, the chargeable bodies B, D, E and K were equally identified to be of potential interest because their high chargeability values suggest mineralization presence, while the corresponding moderate to high resistivity signatures could be attributed to their associate minerals.
Res/IP line 2
The resistivity and chargeability models for this profile revealed the presence of conductive structures interpreted to be mineralized targets, with optimum depths of around 48 m (Fig. 12). Two distinct zones were observed on the resistivity model, each segregated by a relatively flat boundary. The structural discontinuities (fault zones) showed resistivity values ranging from 29.2 to 143 Ωm.
The imaged chargeable bodies A, B, E, G and H were interpreted to be the lateral continuity of the anomalies identified in Res/IP line 1. Chargeable bodies E, G, H is characterized by high chargeability with low resistivity values, while A, B, I, and J is characterized by moderate to high resistivity and high chargeability values. Chargeable bodies D, C, F, and K in Fig. 11 combined to form the chargeable body I in Fig. 12, while the new chargeable body J appear larger and closer to the surface than in Res/IP line-1. The increase in resistivity of the bodies A and I indicate an increase in associate minerals like quartz.
Res/IP line 3
Figure 13 shows the geoelectrical section of this profile across the identified target conductive structures. The resistivity model highlighted eight zones of discontinuities (Faults) with resistivity values ranging from 63.4 to 237.0 Ωm. The delineated chargeable bodies I, J and E were observed to be laterally continuous from Res/IP line 2. The chargeable body B reflected low mineralization potential due to its low chargeability value when compared to other bodies across the profile. Chargeable bodies I and J exhibited low resistivity and high chargeability signatures, while the chargeable body E showed moderate resistivity and high chargeability values. A new chargeable body of interest Z highlighted along this profile depicted a very high resistivity value (> 882.0 Ωm) and high chargeability (> 96.0 msec), suggesting potential mineralized zone with high percentage of highly resistive gange minerals.
Res/IP line 4
The geoelectrical section of this profile is presented in Fig. 14. The model highlighted six zones of weakness (faults) with resistivity ranges of 9.2 to 121.0 Ωm. The identified chargeable bodies B, I, J and Z were interpreted to be continuous from Res/IP line 3. The anomalous chargeable bodies B, I and J are characterized by high chargeability with low to moderate resistivity signatures, while the chargeable body Z displayed high chargeability and very high resistivity. Chargeable bodies at the western part of the Res/IP line 4, at 50 m and 150 m were not highlighted because they have chargeability < 12 msec.
Res/IP line 5
Figure 15 is the resistivity and chargeability model for this profile, which cuts across the northern end of the interpreted conductive structures AEM-1 and AEM-3. Six zones of weakness (faults) were highlighted across this resistivity section. The faulted zone showed resistivity variations from 28.1 to 122.0 Ωm. A broad high resistivity body is observed at the western end of this profile.
The observed chargeable bodies B, I, J and Z are interpreted to be continuous from Res/IP line 4. Chargeable bodies B, I and J are characterized by moderate chargeability with low to moderate resistivity values, while the chargeable body Z which recorded high chargeability and very high resistivity across Res/IP lines 3 and 4, showed moderate chargeability value of about 16.8 msec and moderate resistivity value of about 256.0 Ωm. The reduction in chargeability response may be attributed to a decrease in chargeable minerals within the interpreted faults.
Fresh core samples acquired at potential mineral target areas along Res/IP lines 2 and 3 (Figs. 12 and 13) were used as ground-truthing to buttress our findings in this study. The cored mineralized zones were characterized by high chargeability and low resistivity values. The cored interval from Drill Point 1 revealed numerous faulting within target depth. The faults were filled with quartz mineral and chalcopyrite. Lead-zinc minerals were identified on a fresh cut surface the quartz mineral, suggesting that the ore mineral was enclosed within the quartz rock (Fig. 16). The cored interval from Drill Point 2 revealed fault surfaces of highly indurate shale samples. The fault plane has no filling. However, a small spec of chalcopyrite is seen (Fig. 16c and d).
The chargeability values obtained from the 2D inversion of the chargeability data formed the basis for three-dimensional (3D) gridding using the kriging algorithm. The obtained 3D voxel model isolated chargeable bodies (potential mineralization) with chargeability values > 15 msec, which were regarded as anomalies of interest (Fig. 17). Quantification of the ore reserve was achieved by evaluating the volume (V) of the chargeable voxel, and multiplying the obtained value with a density (ρ) value of 6.4 g/cm3 to compute the tonnage of the mineralized body and also ensure that error in computation is kept at the barest minimum.
The volume (V) of chargeable body was calculated to be 853,250 m3.
Hence, the tonnage of the mineral deposit was determined using the equation:
$$Tonnage=V*\rho$$
1
$$Tonnage=\text{853,250}\times 6.4$$
$$=\text{5,460,800} tonnes$$
Loke and Baker (1996) and Marescot et al. (2003) have shown that the size of a chargeable anomaly is generally about half of the causative structure/bodies. Therefore, half of the computed tonnage is the nearest estimate to the true tonnage of the interpreted mineralization. This is given as;
$$Nearest estimate=\frac{\text{5,460,800}}{2} tonnes$$
2
$$=\text{2,730,400} tonnes$$
Using the price of lead at Indiamart ($467.1), the estimated value of the deposits for the surveyed area is calculated to be:
$$Estimated value=467.1\times \text{2,730,400}$$
3
Integrated interpretation of ground geophysical data acquired over the Bangalela area of the Central Benue Trough, northcentral Nigeria revealed the presence of linear geological features like fractures, faults, veins, etc., which controlled the formation of hydrothermal mineralization in the study area. The 2D Fraser filter map highlighted the presence of conductive structures which were designated as potential mineralization targets. The orientation of these structures conforms with the dominant tectonic trends in the Benue Trough which are known to host potential mineralization in this Cretaceous megarift structure. Interpretation of the ER/IP data across to two major conductive structures of interest (AEM-1 and AEM-3) revealed the presence of chargeable bodies with varying resistivity values, suggesting the presence of ore minerals like lead and the associate gange mineral such as quartz. The mineralized bodies occurred as ore infillings in the identified fractures beneath the study area. Fresh core samples obtained from two Drill Points along the geoelectrical profiles (Res/IP lines 2 and 3) confirmed the chargeable body to be chalcopyrite. 3D voxel modeling of the chargeable bodies (potential mineralization) which exhibited chargeability values > 15msec enabled evaluation of the ore reserve which was computed to nearest estimate of about 2.7 million tonnes, valued at about $1.3 billion. Hence, lead-zinc mineral reserve in Bangalela area is considered to be of economic significance. Further studies (including laboratory analysis of the core samples) are recommended to ascertain the ore grade.
Author Contribution
S.A. acquired and analyzed the geophysical data. S.I. supervised the work. S.A. and I.O. wrote the main manuscript text. H.T. and S.C. edited the manuscript and E.M. prepared the figures. All authors reviewed the manuscript.
Conflict of Interest: The authors declare no conflict of interest.
Competing Interests: Authors declare that there are no financial or non-financial interests that are directly or indirectly related to this research work.
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No competing interests reported.