case study case study article 2394–3750...

© 2017 Discovery Publication. All Rights Reserved. www.discoveryjournals.com OPEN ACCESS

Page

158

CASE STUDY ARTICLE

Geolectric and geochemical appraisal of Iron-ore deposit: Case study of Akunu-akoko, southwestern Nigeria

Cyril Chibueze Okpoli Department of Earth Sciences, Faculty of Science, Adekunle Ajasin University, PMB 1, Akungba-Akoko, Ondo State, Nigeria Corresponding Author: Department of Earth Sciences, Faculty of Science, Adekunle Ajasin University, PMB 1, Akungba-Akoko, Ondo State, Nigeria; E-mail: cyril.okpoli@ aaua.edu.ng Article History Received: 23 July 2017 Accepted: 12 September 2017 Published: July - September 2017 Citation Cyril Chibueze Okpoli. Geolectric and geochemical appraisal of Iron-ore deposit: Case study of Akunu-akoko, southwestern Nigeria. Science & Technology, 2017, 3(11), 158-180 Publication License

This work is licensed under a Creative Commons Attribution 4.0 International License. General Note

Article is recommended to print as color digital version in recycled paper.

ABSTRACT

Akunu-akoko is part of the Precambrian Basement Complex of Nigeria, which is made up of the following lithologies: Granite gneiss, Porphyritic granite, Charnockite, Iron Ore, Iron Concretions, Minor felsic and mafic component. The iron ore in Akunu occur within the subsurface and were found associated with granite gneiss and Charnockite. This research was carried out from the selected

CASE STUDY 3(11), July - September, 2017

Science & Technology ISSN

2394–3750 EISSN

2394–3769


Page

159

CASE STUDY ARTICLE

twenty (20) Vertical Electrical Sounding (VES) and five (5) samples of topsoil to depth of 50cm obtained randomly from the location using the atomic absorption spectrophotometer (AAS). These parameters were used to determine the subsurface layer, thickness and the grade/value of the probable metallic ore deposit. The research was carried out from the selected location because of evidences of surface occurrence that can be seen across the area which is as a result of erosional and tectonic activities. This evidence points to the fact that possible remains of the deposit can be found within the subsurface. The VES data obtained were interpreted manually by partial curve matching and quantitatively by computer iteration. The results of the VES investigation revealed six main sounding curves; these are HA, QH, H, KH, AA, and K, the dominant curve type is the HA (VES 11, 12, 14, 17, 18, 19, and 20) taken 35. The geo-electric section revealed three to four subsurface layers, which are the topsoil with thickness of 1.3-3.7meters (showing variable composition), the weathered layer zone (inferred as the zone of accumulation of the iron ore), and then the basement. The quantitative interpretation of the acquired data revealed that VES 2, 3, 11, 12, 13, 14, 15, 19, and 20, all showed very low resistivity and apparently high conductivity due to the presence of iron ore. Also, the range in thickness of the iron ore deposit was determined from the above listed VES stations to range between 10.0-12.8meters. The volume of the reserved deposit of iron ore within the surveyed region of Akunu was estimated to be approximately 71 million tonnes. Therefore, this region can then be considered for further exploration. The geochemical analysis also showed that the deposit contained a very good metal grade iron ore with an average composition of 2.55 PPM of magnetite and also an average composition of 1.6PPM. This result showed that the selected location for this study has been investigated to host magnetite and hematite ore of iron. Keywords: Geoelectric, geochemical, iron-ore, Precambrian Basement, Akunu-akoko.

1. INTRODUCTION Economic viability of any mineral deposit depends on the area and depth extent as well as chemical composition amongst other factors (Oladimeji et al, 2013). Iron is the fourth most abundant element in the Earth's crust, comprising about 5%. The vast majority is bound in silicate or more rarely carbonate minerals (Gordon and Robert 1996). Iron which is the world's most commonly used metal (steel), of which iron-ore is the key ingredient, representing almost 95% of all metal used per year (Ifaturoti, 1994). It is used primarily in structural engineering applications and in maritime purposes, automobiles, and general industrial applications (Ogbonnaet al., 1999). This study was carried out to determine whether their exist a zone of iron-ore deposit within the subsurface as surface evidence of the mineral occurrence can be observed around the region due to erosion and uplift. As part of the methodological approach, geophysical and geochemical explorations were carried out to determine the compositional trends of the iron ore mineral hosted within the basement rocks of AkunuAkoko area of Ondo State, southwestern Nigeria using two different approaches; Electrical resistivity method (VES) coupled with laboratory analysis of soil samples collected from the site; to ascertain the quality of the samples in terms of iron mineral compositions.

The need to explore these earth treasures with modern day techniques and equipment arises when considering the factors like cost, time waste, risk and destruction of ecosystems as well as land form. These minerals are distributed unevenly across the globe, some are exogenic (seen at the surface of the earth) while some are endogenic (buried underneath the earth surface)Kuzin, 1976. The surface area of Nigeria 923,768 sq. km is covered in nearly equal proportions by crystalline rocks and sedimentary rocks (Umar et al., 2011). Iron ores of diverse quality and origin are found in Nigeria. The deposits are abundant in Kwara, and Kogi States. Other States where iron ore occurrences have been discovered include Nasarawa, Sokoto, Kaduna, Oyo, Osun, Bauchi, Borno and Benue (Famuboni, 1990). There are over 3 billion metric tonnes of iron ore deposits in the country. Other deposits of iron ore in the country are still under investigation even as this study work is centered on investigating the possibility of iron-ore occurrence in AkunuAkokoOndo State. AkunuAkoko is part of southwestern part of Nigeria, which is underlain by the southwestern basement complex (Kroner et al., 2001). The basement complex rocks of the region have been studied and classified by Rahaman (1976, 1988); Odeyemi (1988); Adekoya et al, (2003) among others. Related research includes the investigation of bauxite ore deposit at Orin-Ekiti, using electrical resistivity method in conjunction with AAS sampling analysis to determine the grade of the ore deposit (Oladimeji, et al., 2013).

The purest ores occur in a series of basement ridges for example, the Itakpe Hills in Kogi State. The iron and steel industry, near Ajaokuta, exploits this deposit. In the Itakpe iron ore, magnetite and hematite are the main ore minerals (onlineNigeria.com, 2014). Proven Iron Ore reserves are at least 200 million tonnes with a life-span of over 100 years. The commercial ore grades range in ferrous (Fe) content from rich ores with over 50 per cent Fe, medium grade ores (30 - 50 per cent Fe), to poor ores (25 - 30 per cent Fe).OnlineNigeria.com, 2014.Primary steel billets are produced at Aladja from steel rolling mills at Katsina, Jos, Oshogbo and Eket. Large reserves of sedimentary iron ore are exposed at Agbaja Plateau in Kogi State, where oolitic and pisolitic iron-stones, rich in


Page

160

CASE STUDY ARTICLE

phosphorous and alumina, hold up to 30.5 million tonnes which assay 50 per cent Fe. Other major sedimentary iron deposits are found in the Nupe basin, Sokoto basin and at Enugu.OnlineNigeria.com, 2014. Prior to 1975, Nigeria was a major tin exporter with an annual production of tin concentrates which peaked at about 11,000 tonnes. This has now declined drastically to about 2,000 tonnes. Among the factors accounting for the collapse of the tin industry in Nigeria are the depletion of the readily accessible placer deposits and the prohibitive cost of mining the ores beneath the basalt flows on the Jos Plateau.OnlineNigeria.com.htm (2014).

This paper is aimed on using electrical resistivity and geochemical tools to determine the probable existence of ironore deposit, depth into the subsurface and areal extent. Hence, Vertical Electrical sounding (VES) and atomic absorption spectrophotometer (AAS) analysis were adopted in the research.

2. DESCRIPTION OF THE STUDY AREA Akunu-Akoko is located in Akoko North West Local Government area (LGA) of Ondo State, Southwestern Nigeria and lies within the Basement Complex of Nigeria Basement Complex (Figure 1). The area lies within longitude 7035’N - 7040’N and longitude 5055’E - 5060’E, within a scale of 1:1000000 from Owo (225) topographic sheet of the federal survey of Nigeria (1978). The major road from Ikare to IkakumoAkoko defines the major access to the town. Other major road networks are the roads running from Kaba, Kogi State towards Auga Akoko.

Figure 1 Topographic map of the study area and its environs


Page

161

CASE STUDY ARTICLE

2.1. Topography The study area exhibits different forms of topographic distinction which lies in the Precambrain complex of southwestern Nigeria. The north-eastern and the south-western part show a higher topography. The area is mostly undulating to holly due to the intense distribution and deposition of the basement rocks (Rahaman, 1988). 2.2. Geomorphology and drainage pattern AkunuAkoko is characterized by different but impressive physiographic features with varying lithology ranging from conspicuous highlands to older granite to fairly undulating terrain of ironstone (Rahaman, 1976). The drainage pattern of the study area is the combination of both trellis and dendritic type of drainage. They show the resistance of the underlying crystalline basement rock and displace structural features. Streams and main rivers are developed during major joint direction and foliation trend with generally straight courses. These factors also imposed the trellis and dendritic patterns. Most of the streams are seasonal.

Figure 2 Map showing the trellis and dendritic drainage pattern of the study area


Page

162

CASE STUDY ARTICLE

2.3. Climate and vegetation The study area belongs to the tropical rain forest and can be described as good and support agriculture activities due to the texture of the soil and nature of vegetation in the area. Rainy season occur between March and October while the dry season last from November to February. The mean annual rainfall is approximately 2000mm. The temperature in the area varies between and with high temperature between February and April.

AkunuAkoko is part of southwestern part of Nigeria, which is underlain by the southwestern basement complex. The Precambrian basement complex rocks of Nigeria are the oldest in Nigeria (Kroner et al., 2001) and they lie within the remobilized fringe of West African craton. The basement complex rocks have been studied and classified by Rahaman (1976, 1988); Odeyemi (1988); Adekoya et al., (2003) among others. The major rock types in the area as classified by Adekoya et al., (2003) are: (a) The Migmatite-Gneiss-Quartzite Complex; (b) The Schist Belt which are low to medium grained Supracrustals and Metaigneous rocks; (c) The Pan African Granitoids (Older granites) and other related rocks such as Charnockitic rocks and Syenites; and (d) Minor Felsic and Mafic Intrusives.

Figure 3 Map of Ondo State Showing the location of the study area. Source: Geological Survey Nigeria, Ondo State, 2001 2.4. Description of rock types The following lithological unit were found in the study area – Akunu-Akoko after taking into cognizance the field observations and thin section analysis;


Page

163

CASE STUDY ARTICLE

Granite gneiss Porphyritic granite Charnockite Iron Ore and Iron Concretions Minor felsic and mafic component e.g. Pegmatite, Quartz and Feldspathic veins

Figure 4 Geological map of AkunuAkoko showing cross section (after AkunuAkoko independent mapping AAUA, 2013).


Page

164

CASE STUDY ARTICLE

Iron ores are rocks and minerals from which metallic iron can be economically extracted. The ores are usually rich in iron oxides and varies in colour from dark to pink. They generally occur as ores in hematite, magnetite and goethite. A preliminary report by the Nigeria Geological Survey Agency (1980) shows that there are iron ore deposits in Itakpe, Ayere and Akunu. The iron ore in Akunu occur within the subsurface and were found associated with granite gneiss and charnockite. The ores were dug from the subsurface. It exhibit very high density as revealed by the heavy weight of samples recovered beneath the surface. There is little literature on the origin and reservoir capacities of the iron ore deposit. The origin of formation of the ore is controversial; however, a possible migration of the ore from the nearby Itakpe cannot be completely rejected.

3. METHODS OF STUDY 3.1. Field method and data acquisition The electrical resistivity method of geophysical prospecting is the most widely used geophysical method adopted for several investigations. It is used for investigating vertical variation in the earth’s electrical resistivity with depth this procedure is otherwise called the vertical electrical sounding (VES) and the lateral variation in the earth’s electrical resistivity with respect to a fixed depth otherwise called the lateral or horizontal profiling and such variation could be interpreted in terms of geology. In the basement complex, fractured zones within the bedrocks are characterized with relatively low resistivity values while the fresh bedrocks are characterized with low conductivity values.

Figure 5 Acquisition base map showing the VES stations of the study area

Twenty (20) VES stations were acquired in the study area and geo-referenced with an accurate Global Positioning System (GPS)


Page

165

CASE STUDY ARTICLE

recording device (Table 4). Current electrode separation (AB) with a minimum of 65meters and maximum of 100meter was maintained throughout the survey location. Other equipment deployed include; Steel Electrodes, Pre-marked Strings, Measuring Tapes, Electric cables, Calculator and Hammers. The geochemical analyses was also used to support the geophysical technique, this involves the laboratory test for five (5) soil samples collected from the study location using the atomic absorption spectrophotometer to analyze for the presence of magnetite or hematite. 3.1.1. The Vertical Electrical Sounding (VES) interpretation The VES was utilized to investigate the vertical variation in the earth’s electrical resistivity with depth. Vertical electrical sounding data were plotted as sounding curves i.e. apparent resistivity (Ωm) plotted against electrode spacing AB/2 (m) on a log- log graph sheet. Interpretation of vertical electrical sounding curves (resistivity curves) is based on four conventional sounding curves. Partial curve matching technique was employed for quantitative interpretation of the sounding data (Keller and Frischknecht, 1966) and finally the iteration (Vander Velpen, 1988).This is achieved by plotting the apparent resistivity values against the electrode spacing on a bi-log graph and plotting the resistivity values with respect to depth for each VES station.

The qualitative interpretation involves the inspection of geo-electric sections, maps and sounding curves, for signatures or pattern diagnostics of a particular target. The quantitative interpretations of field curves were initially carried out using the convectional partial curve marching technique of the auxiliary point methods. This process provides the estimates of resistivity and thickness of various geo-electric layers. These parameters were used as starting models for the computer iteration. Preparation of geophysical model always assumes the following Earth materials have distinct subsurface boundaries. The unit is isotropic (properties are independent of direction).

The interpretation of each VES curve were carried out in two steps. In the first step, an approximate interpretation was obtained by the curve matching method described by Orellana and Mooney (1966) which entails matching the sounding curves segment by segment with theoretical curves (Orellana and Moony, 1996).The technique is an empirical method by which a multi-layered case is progressively reduced to a simple two or three layer case. Each sounding curve is super-imposed on the master curve and with the axis kept parallel, it is moved about until a fit is obtained over as many as possible. The point of intersection of the master curve is marked on the field curve tracing paper where the resistivity and the thickness of the first layer are obtained. The value of K (which is the reflection coefficient at the interface between the first and second layer) on the master curve that fitted the first segment is noted. The auxiliary curve with the field reflection coefficient value was broken drawn on the field curve with broken lines with the axis kept parallel. The next segment of the curve was fitted to a two layer master curve and of the beast fit was obtained with the point of intersection of the master curve marked.

The results of partial curve matching were obtained and inputed into an automatic interpretation computer program (Zohdy, 1972). Based on this interpretation, the parameters ρ (resistivity) and h (depth) of a geo-electric model, thought to be closer to reality, were estimated and then substituted in a computer program known as WinRESIST Version 1.0. The results were then iterated and modified by trial and error until a very close match was attained between the calculated and observed resistivity curves. The Golden SURFER 10 software program was used to generate relevant geo-electric sections and also isopach and isoresistivty maps from the field curve and GPS data obtained. 3.2. Geochemical analysis Atomic absorption spectrophotometer (AAS) analysis was the method used for the determination of the elemental chemistry of soil samples collected from the field. The procedure for the extraction of iron from the soil sample can be carried out in two ways, though the method of exchangeable iron was employed for the extraction due to its accuracy. The methods employed are: Hydrochloric acid extraction Exchangeable Iron Hydrochloric acid extraction Reagents: Hydrochloric acid, 0.2N, HCL Procedure: Weigh 5g of soil into a 100ml plastic bottle (use no rubber stopper), Add 50ml of 1.0N HCL and shake for 30minutes, Filter through No. 42 filter paper, Determine Fe on atomic absorption spectrophotometer.


Page

166

CASE STUDY ARTICLE

Exchangeable Iron Apparatus Centrifuge and tubes Spectronic 20 or 70 Reagents: Ammonium Acetate NH4OAC, Adjust to PH 3.0 by the addition of conc. HCL. Procedure: Weigh 3g of soil into a 50ml centrifuge tube and add 30ml of the extracting solution, Shake for 1minute and centriguedecating the supernatant into 100ml volumetric flask, Repeat the extraction two (2) more times decanting the supernatant into the same volumetric flask. Make up to mark the solution into the volumetric flask, Determine Iron (Fe) in the extracts using C-phenanthrolineclorimeter method or atomic absorption spectrophotometer (AAS). Atomic absorption spectrophotometer The concentration of iron two and iron three in the oxidize and reduced state were determined in PPM using the atomic absorption spectrophotometer, (AAS 210vp model). The principle is based on the measurement of resonance source variation which is absorbed by unexpected ground state atoms of an analyte in a flame. The intensity of the partial pressure of the radiation absorbed is proportional to the concentration of the concentration of the absorbing atom in sample.

In order to analyze a sample for its atomic constituents, it has to be atomized. The sample should then be illuminated by light. The light transmitted is finally measured by a detector in order to reduce the effect of transmission from the atomizer or the environment, a spectrometer is usually used between the atomizer and the detector while the atomizer technique makes use of a flame to atomize the sample. When a flame is used, it is laterally long (usually 10cm) and not deep. The height of the flame above the burner head can be controlled by adjusting the flow of the fuel mixture. A beam of light passes through this flame at its longest axis (the lateral axis) and hit a detector.

4. RESULTS DISCUSSION 4.1. Data acquisition The field data acquired (Table 1) are presented as depth sounding curves (figure 6) and geo-electric sections. The curves were interpreted qualitatively and quantitatively. The qualitative interpretation involved evaluation of the sounding curves for lithology characterization of the area. The quantitative interpretation involves partial curve matching using two-layer Schlumberger master curve and the auxiliary curves. The outputs from the manual interpretation were modeled using computer iterations. Resist version 1.0 software was utilized for the iterations. The curve types obtained from the field data are 3-layer H (VES 2, VES 3, VES 13), 3-layer K (VES 6), 4-layer KH (VES 1, VES 4), 4-layer AA (VES 7, VES 10), 4-layer QH (VES 5, VES 8, VES 9, VES 15, VES 16), 4-layer HA (VES 11, VES 12, VES 14, VES 17, VES 18, VES 19, VES 20). 4.2. Data presentation and interpretation The field data collected from the study area was interpreted quantitatively and qualitatively. The quantitative results of this study are presented as depth sounding curves, tables, and geo-electric sections, isoresistivity maps of topsoil, weathered layer, and the overburden thickness. 4.3. Sounding curves In the study area, 6 curve types were identified; these are HA, QH, H, KH, AA, and K. This is represented with bar chart shown as in figure 6. The occurrence of these curve type are shown in table 1 where type curve HA has the highest percentage (35%) of occurrence, followed by QH curve type has (25%) while H, AA, KH, K, type curve have 15%, 10%, 10% and 5% respectively. The typical curve types are as shown in figure 7 and 8. The HA curve type thus suggest the probable occurrence of the homogenous unit which can be inferred as the metallic ore deposit. High RMS errors were recorded at some VES stations and this is mainly due to the anomaly caused by homogenous accumulation of the metallic mineral deposit occurring within the subsurface. The VES locations showing this unusual characteristic tend to also show low resistivity value variation between 10.6 – 96.5 Ωm. Previous investigation for metallic minerals in the subsurface has also revealed that the region of metallic mineral accumulation tends to produce high RMS error, due to the chemical composition of the mineral composition ( Badmus et al., 2013,Oladimeji et al., 2013).


Page

167

CASE STUDY ARTICLE

Table 1 Co-ordinate and summary of geo-electric data interpretation of VES at AkunuAkoko

Ves Points

LATITUDE (N)

LONGITUDE (E)

Ωm

ρ2 Ωm

Ωm

Ωm

h1

(m) h2

(m) h3 (m)

Curve type

1 7038’31.26’’ 5057’17.07’’ 428.5 1361.8 198.0 5183.7 1.5 4.0 13.7 KH

2 7038’32.7’’ 5057’17.89’’ 148.4 135.7 16.6 598.7 1.7 2.7 7.3 H 3 7038’33.72’’ 5057’19.55’’ 256.5 40.7 16374.4 1.2 2.8 H 4 7038’34.28’’ 5057’20.56’’ 519.9 606.3 273.7 2537.1 1.9 3.6 11.7 KH

5 7038’36.66’’ 5057’21.66’’ 1621.6 848.2 156.7 3335.7 1.1 3.5 9.0 QH 6 7038’37.44’’ 5057’23.14’’ 154.5 9645.2 2696 0.7 10.0 K 7 7038’38.28’’ 5057’25.58’’ 470.2 1714.4 2081.3 6146.1 0.9 2.0 9.5 AA 8 7038’42.36’’ 5057’27.07’’ 7419.8 2552.1 1484.4 1603.1 3.7 10.3 11.3 QH 9 7038’44.82’’ 5057’28.87’’ 192.3 110.4 109.0 1577.5 1.2 2.1 3.5 QH 10 7038’45.92’’ 5057’29.14’’ 107.5 481.3 1243.7 1695.9 1.1 2.1 13.3 AA 11 7038’46.92’’ 5057’29.74’’ 713.9 60.6 1736.7 18622.5 1.5 3.7 7.2 HA 12 7038’48.66’’ 5057’30.48’’ 840.9 67.6 698.6 10313.4 2.1 7.2 12.2 HA 13 7038’38.28’’ 5057’23.14’’ 1131.5 33.9 13748.1 1.5 4.0 H 14 7038’49.44’’ 5057’30.64’’ 1093.0 109.3 650.6 9363.3 1.8 4.6 7.6 HA 15 7038’51.48’’ 5057’31.12’’ 1063.4 394.6 57.7 1089.6 2.4 3.5 8.5 QH 16 7038’53.58’’ 5057’31.58’’ 826.7 180.3 158.8 5869.7 3.4 5.4 8.5 QH 17 7038’54.66’’ 5057’32.53’’ 1073.5 493.0 1918.6 2169.4 1.2 3.5 5.5 HA 18 7038’55.68’’ 5057’34.18’’ 652.8 79.4 262.6 7348.4 2.3 7.5 12.8 HA 19 7038’57.12’’ 5057’36.67’’ 463.5 66.2 625.7 13829. 1.5 4.0 5.4 HA

20 7038’59.22’’ 5057’37.69’’ 473.0 41.2 748.3 22015.4 1.6 3.5 6.0 HA

Table 2 Curve type distribution of the study area

Curve type Frequency percentage

HA 7 35%

QH 5 25%

H 3 15%

AA 2 10%

KH 2 10% K 1 5%


Page

168

CASE STUDY ARTICLE


Page

169

CASE STUDY ARTICLE


Page

170

CASE STUDY ARTICLE

Figure 6 Representative curve types of the study area. Table 3 Summary of the VES points and probably lithology for the sounded points (Corresponding to previous works by: Badmus B.S. et al 2013, Ehinola O.A., et al 2012, Oladimeji L.A., et al. 2013)

VES

LOCATION

LAYER

Resistivity (Ohm.m)

Thickness

Depth

Probable Lithology

Akunu VES 1

1 430.3 1.6 1.6 Top soil

2 1519.7 2.4 3.6 Consolidated sandstone

3 173.4 8.9 13.8 Clay saturated weathered layer

4 8632.7 - - Fresh basement Akunu VES 2

1 111.1 0.8 0.8 Top soil 2 226.7 0.9 1.7 Sandy clay 3 14.6 3.3 5.0 Iron ore


Page

171

CASE STUDY ARTICLE

4 266.9 - -

Clay saturated weathered layer

Akunu VES 3

1 258.2 1.2 1.2 Top soil 2 31.7 1.2 2.5 Iron ore

3 30155.8 - - Fresh basement

Akunu VES 4

1 3607.0 0.4 0.4 Top soil 2 519.0 1.6 1.9 Sandstone 3 413.4 16.9 18.8 Clayey sand 4 4308.0 - - Basement

Akunu VES 5

1 1569.8 1.4 1.4 Gravel laterite 2 670.9 2.2 3.6 Fissile grey shale 3 148.8 5.1 8.6 Clay 4 31953.2 - - Basement

Akunu VES 6

1 157.4 0.7 0.7 Clay top soil 2 8884.5 9.6 10.3 Basement 3 2906.7 - - Basement

AkunuVES 7

1 475.6 0.8 0.8 Gravel laterite 2 1595.3 1.5 2.4 Iron stone 3 2082.1 6.0 8.4 Basement 4 5704.2 - - Basement

Akunu VES 8

1 489.7 3.5 3.5 Iron stone top soil 2 3356.9 2.9 6.4 Fresh basement 3 1716.1 5.0 11.5 Fractured basement 4 1686.2 - - Fractured basement

Akunu VES 9

1 529.0 0.9 0.9 Top soil

2 1294.5 0.7 1.6 Sandstone

3 619.2 0.7 2.3 Fractured basement

4 4306.6 - - Basement

Akunu VES 10

1 108.4 1.2 1.2 Top soil

2 627.3 1.4 2.5 Weathered/Fractured layer

3 1306.8 6.3 8.9 Basement 4 1553.4 - - Basement

Akunu VES 11

1 713.0 1.6 1.6 Top soil 2 10.6 0.4 1.9 Iron ore 3 1328.5 2.5 4.4 Weathered layer 4 16848.5 - - Fresh basement

Akunu VES 12

1 839.0 2.1 2.1 Top soil 2 62.7 4.9 6.9 Iron ore 3 713.8 4.1 11.0 Weathered layer 4 9599.3 - - Basement

Akunu VES 13

1 1128.4 1.5 1.5 Top soil

2 29.4 2.2 3.7 Iron ore

3 15252.5 - - Basement Akunu VES 14

1 1088.0 1.9 1.9 Top soil 2 96.5 2.6 4.5 Iron ore 3 680.6 2.8 7.3 Fractured/Weathere


Page

172

CASE STUDY ARTICLE

d layer 4 13679.9 - - Fresh basement

Akunu VES 15

1 1060.5 2.5 2.5 Top soil 2 392.0 0.9 3.4 Sandy Clay 3 46.4 4.1 7.5 Iron ore 4 10746.0 - - Basement

Akunu VES 16

1 829.5 3.6 3.6 Topsoil 2 138.1 2.2 5.7 Clay 3 155.4 2.3 8.1 Fissile Shale 4 6948.1 - - Magnetite

Akunu VES 17

1 1089.4 1.3 1.3 Gravel laterite 2 378.0 1.6 2.9 Sandy Clay 3 2140.2 2.0 4.9 Magnetite 4 2301.5 - - Basement

Akunu VES 18

1 653.1 2.2 2.2 Gravel laterite top soil

2 109.7 8.1 10.3 Clay 3 220.7 6.4 16.7 Fissile grey shale 4 8315.7 - - Basement

Akunu VES 19

1 461.9 1.5 1.5 Top soil 2 55.4 2.1 3.6 Iron ore

3 693.5 2.1 5.7 Fractured/Weathered layer

4 14268.2 - - Fresh basement

Akunu VES 20

1 851.0 0.5 0.5 Top soil 2 37.3 1.1 1.6 Iron ore

3 918.3 1.5 13.0 Weathered/Fractured layer

4 24278.6 - - Fresh basement 4.4. Geo-electric section Figure 7 to 10 are four (4) geo-electric sections with each making up five (5) VES stations. The sections shows variations in resistivity and thickness values of layers within the depth penetrated in the study area at the indicated VES station. The geo-electric section revealed three to four subsurface geologic/geoelectric layers consisting of topsoil, fractured/weathered layer and the fresh basement with infinite depth.The iron ore mineral is found to be located sparsely within the region of very resistivity value ranging between 10.6 – 96.5 Ωm. The VES location showing this very low resistive iron ore mineral occurrence include VES 2 (14.6 Ωm), VES 3 (31.7 Ωm), VES 11 (10.6 Ωm), VES 12 (62.7 Ωm), VES 13 (29.4 Ωm), VES 14(96.5 Ωm), VES 15(46.4 Ωm), VES 19 (55.4 Ωm), VES 20 (37.5 Ωm). It was also observed that five of these VES station shared the HA type curves indicating similar subsurface lithology.The topsoil shows undulation of layer thickness between 1.3 - 3.7meters, relatively thin at some region and also appreciable thick at other location, while the resistivity values ranges from 111.1 – 3697Ωm. This indicates that the topsoil is of variable composition and contains predominantly clay, sandy clay, iron stone, and probable occurrence of the iron-ore mineral at some stations where the topsoil shows very low resistivity value. The weathered layer thickness ranges from 2.0 - 13.7m and the resistivity values ranges from 16.6 – 9645.2Ωm and composed of clayey soil, and also pockets of localized iron-ore mineral. The fresh basement is the last observable layer with resistivity values ranging between 1000Ωm to infinity. The iron ore deposit can therefore be inferred to be undulating between the topsoil and the fractured/weathered layer.


Page

173

CASE STUDY ARTICLE

Figure 7 Geo-electric section showing VES 1-5



Page

174

CASE STUDY ARTICLE


Figure 10 Geo-electric section showing VES 16-20 4.5. Isoresistivity map of overburden layer The interpreted depth to bedrock beneath all the VES stations were plotted and contoured as isopach or overburden thickness map. This was done to enable a general view of the different lithology across the surveyed area. The overburden is assumed to include the topsoil, the lateritic horizon and the clay/weathered rock. Figure 11 shows the depth to the top of the fresh bedrock beneath the sounding stations. The overburden is assumed to include the topsoil and the weathered layer. The depth to bedrock varies from 3.5 - 13.7m.The isopach map shows zones of relatively thick overburden (greater than 10m) and zones of relatively thin overburden (less than 0.9m).


Page

175

CASE STUDY ARTICLE

4.6. Isoresistivity thickness map of weathered layer The thickness and the resistivity map of the topsoil is presented in figure 12. The red painted region shows the highest thickness lithology of the weathered layer, these regions can be found at VES 7, VES 14, VES 15.At these locations, the weathered layer contains indicates variable composition of earth materials which include pockets of the iron-ore accumulation, and is generally with no hydrogeological significance. The iso-resistivity map of the thickness of the weathered layer across the study area is shown in figure 13. It shows that the thickness value ranges between 0.7 and 12.5meters, parts of the topsoil consist of low resistive materials and other parts have very high resistive materials.This revealed the high heterogeneous variation in the composition of the topsoil from clay, gravel laterite, shale, sandstone and probable iron-ore (migmatite). The weathered layer therefore contains the bulk of the probable iron-ore deposit found within the study area. 4.7. Isoresistivity map of weathered layer The weathered layers as defined in this work are materials constituting the regolith, straddled in between the topsoil or laterite and fractured or fresh bedrock. Figure 13, shows isopach thickness map of the weathered layer within the study area. The region of low resistivity can be seen on the map at VES 2, VES 3, VES 11, VES 12, VES 13, VES 14, VES 15, VES 19, VES 20 (the green colored region of the map explains these VES location better).

Figure 11 Isopach map of the overburden


Page

176

CASE STUDY ARTICLE

Figure 12 Isopach thickness map of the weathered layer


Page

177

CASE STUDY ARTICLE

Figure 13 Isoresistivity map of the weathered layer in the study area 4.8. Qualitative evaluation The result of the geochemical analysis for five (5) soil samples collected at the study area which was achieved with the atomic absorption spectrophotometer (AAS) equipment, revealed the metallic composition of the sample to be made up of two categories of iron oxide, these were iron three and iron two. The result showed that the samples contained greater proportion of magnetite when compare to hematite (Table 4). The oxides were represented as part per million (PPM). From the analysis, it was therefore justified that the deposit contained high grade iron (Fe) when compared with other grade of iron found in the Gove deposit (Ferenczi, 2001), iron ore deposit at Agbaja and Itakpe Hills of Kogi state.


Page

178

CASE STUDY ARTICLE

Table 4 Chemical analysis result for iron contained

Sample No Magnetite Fe3O4 (PPM) Hematite Fe2O3 (PPM)

1 2 3 4 5

2.72 2.35 3.81 2.15 1.22

0.94 1.45 1.70 2.05 1.84

4.9. Discussion of results The topsoil shows undulation of layer thickness between 1.3 - 3.7meters, relatively thin at some region and also appreciably thick at other locations, while the resistivity values ranges from 111.1 – 3697 Ωm. This indicates that the predominant composition of the topsoil is clay, sandy clay, iron stone, and probable occurrence of the iron-ore mineral at some stations where the topsoil shows very low resistivity value between 10.6 – 96.5 Ωm. The weathered layer thickness ranges from 2.0 - 13.7m and the resistivity values ranges from 10.6 – 9645.2Ωm which also indicates that the weathered layer material composition is clay, sandy clay, clayey sand, laterite and also pockets of localized iron-ore mineral. The fresh basement is the last observable layer with resistivity values ranging between 1000Ωm to infinity. The chemical analysis revealed the deposit is of good grade measured in ppm and that the initial mineral deposit magnetite has reacted with oxygen to become oxidized into hematite. The chemical analysis result shows that the ore deposit is of good grade, as VES has also made it possible to estimate a good tonnage up to 71 million from the surveyed area and thickness of the zone of interest. With this, the surveyed area can therefore be considered for further exploration. 4.10. Iron-ore reserve estimation The probable deposit of the iron-ore mineral was estimated from the thickness of the overburden, the density of iron and also the area of the surveyed field (Loke and Nawawi, 2004). The density of iron = 7.874g/cm3 = 7.874 tonnes/m3. The average thickness of the overburden is then determined from five (5) locations, which include VES 4 (11.7), VES 6 (10.0), VES 8 (11.3), VES 12 (12.2), and VES 18 (12.8). Thickness = = 11.6meters An outline of the reserve delineated is measured to determine the area extent of the field, the total length occupied by the twenty (20) VES station is 2600meters with a relative breadth of 300meters. Therefore, Area = Length Breadth Area = 2600 300 = 780,000m2 Volume of the reserve = Area Thickness Density = 780,000 11.6 7.874 = 71,243,952 Tonnes = 7x107 tonnes = 71 million tonnes

5. CONCLUSION Vertical electrical sounding technique of the electrical resistivity method employed in this study has proven the subsurface lithology of the study area to be likely fairly homogenous. From the quantitative interpretation, it has been confirmed that VES locations 2, 3, 11, 12, 13, 14, 15, 19, and 20, showed very low resistivity value ranging between 10.6 – 96.5Ωm. Iron is a conductive mineral, so it therefore permits current flow giving rise to high conductivity and low resistivity. Therefore, these zones were then inferred to contain the targeted iron ore accumulation. It was also observed that the interested VES location shared the HA curve type which is indicative of similar subsurface lithology. The potential thickness of the iron ore deposit was determined and estimated to range between 10.0 – 12.8 meters. The volume of deposit was also estimated from the average value of the deposit thickness, the relative area, and density of iron. The volume was then calculated to be approximately71 million tonnes. A multidimensional approach to


Page

179

CASE STUDY ARTICLE

this study (that was model curves and the resistivity maps presented for formation delineation) has made the study qualitative clarified. Also, the geochemical analysis that was achieved with the AAS equipment has proved the occurrence of magnetite and hematite of high grade within the study area. It can be concluded that the uneven distribution of regions with very low resistivity values, made up the zones of the iron-ore mineral accumulation. The result showed that the fractured/weathered layer (which is generally of thickness less than 15m) that constitute the iron ore mineral with very low resistivity value less than 96.5 Ωm will then be considered as the major host of the iron ore mineral in AkunuAkoko. Also, the chemical analysis showed that the deposit contains high proportion of magnetite and little amount of hematite. Also, the grade of the iron-ore deposit is sufficient enough to warrant further evaluation for economic development.

RREEFFEERREENNCCEE 1. Abdalla, H.M., and Mohamed, F.H., (1999). Mineralogical and

geochemical investigation of emerald and beryl mineralization, Pan-African belt of Egypt: genetic and exploration aspects. Jour. of Afr. Earth Sci. Vol. 28 No.3 PP. 581-598.

2. Adekoya, J.A, Kehinde Phillips O.O, and Odukoya, A.M. (2003) “Geological distribution of mineral resources in southwestern Nigeria”. In: A.A Elueze (Ed) Prospect for investment in mineral resources of southwestern Nigeria, PP 1-13.

3. Ademeso O.A. (2009) “Deformational traits in the Charnockitic rocks of Akure area, Southwestern Nigeria’’.Asian Journal of Earth Sciences 2(4).

4. Amigun J. O. (2009); “Application of 2-D Enhancement Analysis to Aeromagnetic data in mapping Iron Ore Mineralization” The Pacific Journal of Science and Technology Vol. 10 No. 3 PP. 733-741

5. Ajibade A.C.M and Rahaman, M.A., (1989).“Recent advancement in the study of the basement complex of Nigeria”. Elizabeth Publishing Co. Nigeria. PP. 41-58

6. An Integrated Reclamation Scheme to Ensure Good Mining and Mineral Processing Practices in the Niger Delta Area of Nigeria, (2012). Research Journal of Environmental and Earth Sciences 4(5): PP.492-499.

7. Annual Conference of Environmental Division of Nigerian Society (2005), PP: 31.

8. Annual Report, Geological Survey of Ethiopia (2014). Designed and Developed by ICT Directorate. New York, 43(3): 55-56.

9. BadmusB. S., Akinyemi O. D., Gbadebo A. M., Babatunde P., Olurin O. T. and Ganiyu S. A. (2013) “Compositional Trend in the Specks of Tantalite, Tourmaline and Beryl Hosted within Complex Basement Rocks Using Geophysical and Geochemical Methods of Exploration”,Journal of Applied Physics (IOSR-JAP), Vol. 3, Issue 4, PP. 24-33

10. Badmus B.S and Ayolabi E.A., (2005).Litho-facies changes in Ewekoro limestone using Schlumberger geoelectric sounding techniques: Journal of Applied Science and Technology (JAST), 10(1&2): 42-52.

11. Beus A. A. (1980) “Studies of Minerals Deposit,”4th edition, Mac Graw-Hill, London, PP. 19-45.

12. Bhattacharya, P. K. and Patra, H.P., (1968). Direct Current Geoelectric Sounding Principles and Interpretation. Elsevier, Amsterdam, pp: 139.

13. Bretherick L. (1981),Hazards in the Chemical Laboratory, 3rd Ed., Royal Society of Chemistry, London, UK. PP. 178-182

14. Daniel, F.B. and J.T., Walker(2004).The Geology of Southern

Nigeria. McGraw Hill Book Co., New York, PP: 50. 15. David, L.M., and Ofrey, O. (1989): “An indirect method of

estimating ground water level in basement complex regolith”. Water resources, Vol. 1, No. 2, PP. 34 -41.

16. David, R.G., (2001). Ecology, Flora and Fauna of Niger Delta Area of Nigeria, Agricultural Extension, John Willey and Sons, New York, 305(41): 45-46.

17. Douglas, S.R.,( 2002). The Nigerian Oil Economy. St Martins Press, New York 23(3), PP: 34-36.

18. Ebeniro, J. O. and C. N. Ehirim, (2006), “Gully Erosion in Southeastern Nigeria: An integrated geological and geophysical study” Global Journal of Geological Sciences, Vol. 1, PP. 21-28.

19. Ebeniro, J.O., (1994), Importance of Multiple Suppression in Seismic Exploration, Nigerian Journal of Mining and Geology, Vol. 29, No 2, PP. 183-193.

20. Ekwueme, B.N., and Matheis.G. (1995). Geochemistry and economic value of pegmatites in the Precambrian basement of southeast Nigeria: In Magmatism in relation to diverse tectonic settings (Eds. R.K. Srivastava and R. Chandra), New Delhi, Oxford and IBH Publishing Co.PP:375 – 392.

21. Ehirim, C. N., J. O. Ebeniroand O. P. Olanegan, (2009),A Geophysical Investigation of Solid Waste Landfill using 2-D Resistivity Imaging and Vertical Electrical Sounding Methods in Port Harcourt Municipality, Nigeria, Pacific Journ.Sc. And Tech.10(2), PP. 604-612.

22. Ertl, A., Hughes, J.M., Prowatka, S., Ludwig,T., Prasad, P.S.R., Brandstatter, F., Kὂrner, W., Schuster, R., Pertlik, F. and Zarschall, H., (2006). Tetrahedrally Co-ordinated boron in tourmalines from the Liddocoatite-elbaite series from Madagascar: Structure, chemistry and infra-red spectroscopic studies: American Mineralogist, Vol.91, 1847-1856.

23. Famuboni A. D (1990) “Sourcing of Raw Materials for the Nigerian Iron and Steel industries,” Distinguished lecture presented at Dept. of Mining Engineering, Kaduna Poly- technic, Kaduna.

24. Ferenczi, P. A. (2001). Iron ore, manganese and bauxite deposits of the Northern Territory. Northern Territory Geological Survey, Report

25. Furr, K., Ed. (1990),CRC Handbook of Laboratory Safety, 3rd Ed. The Chemical Rubber Co. Press, Florida, USA.

26. Gawu, S. K. Y., Amissah, E. E. and Kuma, J. S. (2012).The proposed Alumina Industry and how to mitigate against the red mud footprint in Ghana.

27. GowN. N. and Lozej G. P. (1993). Bauxite; Geoscience Canada, Vol.20, Number 1, PP: 9–16.


Page

180

CASE STUDY ARTICLE

28. Ifaturoti, E.A. (1995).“Stable Administration and Mineral Re-sources Development,” Nigerian Mining and Geo-sciences Society Newsmagazine, Vol. 94, No. 2, PP. 10-23.

29. Inventory of Nigerian Minerals, Mines and Miners, Publication of the Federal Ministry of Petroleum and Mineral Resources, 1993, PP. 1-29.

30. Jacobson, R., and Webb, J.S. (1946). The pegmatite of Central Nigeria: Goel. Surv. Nig. Bull. 17, 61P.

31. Jackson, D.T., (2003).The Inhabitants of the Niger Delta area of Nigeria. Macmillan Publishers, Lagos, PP: 46.

32. Keller, G.V., Frischknecht, F.C. (1966):Electrical methods in geophysical prospecting. PergamonPress.39: PP.87-97.

33. McNab B., Jankovic A., David D. and Payne P. (2009) “Processing of Magnetite Iron Ores” Iron Ore Conference Perth, WA, PP. 27 - 29

34. Mallam, A. and Ajayi, C. O. (2000); Resistivitymethod for groundwater investigation in sedimentary area. Nig. J. of Physics, 12, 34 – 38.

35. Mooney, H.M. and Orellana, E., (1966): Master tables and curves for vertical electrical sounding over layered structures, inter-ciencia, Madrid. Vo1. 24, Nos. 2, PP 21-30.

36. Multi-disciplinary Committee of the Techno-economic survey on base metal, iron andsteel and engineering services sector (4th update), 2003.

37. Odunaike, R.K., Ijeoma, G.C., Edigbe, R.O. and Babatope, A.H., (2009). Oil sand exploration in Ijebu-Imushin using magnetic and electrical resistivity methods.11th SAGA Biennial Technical Meeting and Exhibition Swaziland: 16-18 September 2009, pages 247-252.

38. Ogbonna A. I. Nwakaudu S.M. and Onyemaobi O.O.(1999) “Strategic Mineral Depositsin Nigeria: The Neglected case of Niobotantalates.” Proceedings of the 16th Annual Conference of the Nigerian Metallurgical Society, Abuja.

39. Ojelabi, E.A, Badmus, B.S., and Salau, A.A., (2002). Comparative Analysis of Wenner and Schlumberger Methods of Geoelectric Sounding in Subsurface Delineation and Groundwater Exploration- A case study: Journal of Geological Society of India,60,623-628.

40. Okwueze, E.E., J.O. Ebeniroand M. Mbogning, (1995), The Geo-electric structure of Lake Nyos dam, Cameroon and its geologic Implications, Nigerian Journal of Mining and Geology, Vol. 30 No. 1, PP. 1-5.

41. Omosuyi, G.O., A.O. Adegoke, and A.O. Adelusi. (2008). “Interpretation of Electromagnetic and Geoelectric Sounding Data for Groundwater Resources around Obanla-Obakekere, near Akure, Southwestern Nigeria”.The Pacific Journal of Science and Technology. 9(2):508-525.

42. Onwusiri, H.N., J.O. Ebeniro, and A.S. Ekine, (1995). The Computation of LVL parameters in the Western Niger Delta, Proc. Nigerian Mining and Geosciences Society, Calabar, Nigeria.Vol. 52, No. 12,PP. 17-44

43. Osemeikhian,J. E. A. and Asokhia, M. B. (1994); Applied Geophysics for engineers and geologists. 1 Ed. Samtos services Ltd., Lagos.

44. Owate, I. O., J.O. Ebeniro, O.E. Abumere, G.O. Avwiri, E.O. Chukwuocha and C.U. Okujagu, (1995), Rudiments of Physics (Mechanics and Properties of Matter),Rescue Publishers, Nigeria.PP. 73-76

45. Parasins, D.S., (1975).Mining geophysics, 2nd ed. Elsevier scientific publishing company Amsterdam/ oxford/New York. PP 17-19.

46. Plunkert, P.A. (2000). Bauxite and alumina: U.S. Geological Survey Mineral Commodity Summaries 2000, PP. 32-33.

47. Rahaman, M. A., (1973): The Geology of the District around Iseyin Western State, Nigeria. An Unpublished Ph.D Thesis, University of Ibadan, PP. 286.

48. Rahaman, M. A. and Ocan O.O., (1988): The Nature of the granulite facies Metamorphism Ikare Area, South Western Nigeria in Precambrian Geology of Nigeria, GNS, PP. 157 – 162.

49. Rahaman, M. A. and Ocan O. O., (1988): The basement complex of Nigeria and its mineral resources. Edited by O. Oshin.Petroe service LTD Ibadan, Nigeria PP. 143-147.

50. Rahaman, M. A. and Ocan O. O., (1978): Relationship in the Precambrian migmatitic gneisses of Nigeria. Nigeria Journal of Mining and Geology,Vol. 15 No 1, pp 23 - 32.

51. Rahaman, M. A. (1976): Review of the PrecambrainBasement Complex of Southwestern Nigeria. Geology of Nigeria (ED), C.A. Kogbe Elizabeth Publishing Cd. LagosPP. 41 – 58.

52. Raw Materials update, a bi-annual publication of the Raw Materials Research and Development Council, Vol. 6, No. 1, 2005, P. 9.

53. Udo E.J. and Ogunwale J.A (1978). Laboratory manual for the analysis of soil, plants, and water samples. University of Ibadan. PP. 76-79

54. Vander Velpen, B.P.A. (2004). “WIN RESIST”. Electrical resistivity inversion program.

55. Yakubu N. A., Damisa E. O and I. S. Amoka,(1999)“Resuscitation a Dying Hope: The Case of Ajaokuta Steel Project,” Nigerian Mining Journal, Vol. 3, No. 1, pp.54-57.

56. Zohdy, A.A.R., (1965). The auxiliary point method of electrical sounding interpretation and its relationship to the Dar-Zarrouk parameters: Geophysics, 30: 644 – 660.

case study case study article 2394–3750...

Documents