Assessment of the mineral potentiality of Block (5) in the Hamisana Area, Red Sea Hills of Sudan: a remote sensing and geo-statistical approach

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1 Assessment of the mineral potentiality of Block (5) in the Hamisana Area, Red Sea Hills of Sudan: a remote sensing and geo-statistical approach Khalid A. Elsayed Zeinelabdein,Abdalla E.M. Elsheikhand Mohamed A. Hassan Faculty of Petroleum and Minerals, Al Neelain University, Khartoum, Sudan. s: kalsayed2001@yahoo.com; abdalla.elsheikh@gmail.com Abstract This study was conducted in the Hamisana area, which is located in the north-western flanks of the Red Sea Hills. It represents the Concession Block (5) of Orshab Mining Co., Sudan. The main objective of the present study; is to carry outgeneral prospecting on the remote sensing base, followed by theassessment and statistical analysis of the economic potentiality of gold and related mineral resources based on geochemical results ofthe analyzed samples. Band rationing technique has been utilized to map alteration zones, which are generally prospective target for gold. The prepared images singled out gold prospective sectors judged by their characteristic signals. Accordingly, the geochemical prospecting was directed in the field towards the target areas obtained from the results of the digital image processing. Close field study revealed that gold occurs in different forms such as: quartz veins and alteration zones. The auriferous quartz veins represent the most potential gold bearing lithology in the area. Most of the potential quartz veins are hypothermal to mesothermal in origin. The rocks alteration injected by quartz stringers and veins are impregnated with the highest gold concentrations.about 73 % of the analyzed chip samples were found to contain gold with contentsvarying from <0.001 ppm to 15.5 ppm. All the known gold occurrences in the investigated area are restricted in six localities showing considerableconcentrations of gold.the gold content taken from alteration zones varies from ppm to 11.4 ppm. Strong significant positive correlation exists between Au and As, which indicate that As can be used as pathfinder for gold in rock samples. Correlation between Cu, Fe, Zn and Mn may indicate the presence of sulphide minerals. Factor analysis was very effective technique and has delineated more than 70% anomalous gold values in chip samples, but was not effective in alteration samples. Key words: Gold, remote sensing; geo-statistical analysis; Hamisana, Red Sea Hills, Sudan. 1. Introduction The study area is located in the Red Sea Hills of NE Sudan (Fig. 1). The geology and tectonic setting of the study area is quite favourable for gold mineralization. The Hamisana Shear Zone (HSZ) is a broad zone of deformation approximately 50 km wide and at least 300 km long, making the area one of the largest basement structures in NE Africa. It has been interpreted as a Precambrian suture, with strike-slip displacement, or as a zone of crustal shortening, (Elsheikh et al., 2014, Stern et al., 1989, Vail, 1985 and Fitches et al., 1983). The study area is dominated 681

2 by meta-volcanosedimentarysequence and ophiolitic rocks. These sequences are intruded by the syn to late-orogenic and post-organic igneous intrusions. From this point of view, ample digital image processing was directed at exploring the study area via means of remote sensing, GIS and geo-statistical analysis. In the following sections, the different approaches used in assessing the potentiality of the project area will be discussed. Fig. 1. Location map of the study area 2. Remote sensing exploration Remote sensing techniques when used together with field mapping and professional ground truthing, it makes the geological mapping effective and efficient in all aspects of cost (Mshiu, 2011). Modern remote sensing systems record image data in a digital raster format that is suitable for computer processing using readily available software and personal computers (Sabins, 1997). Remote sensing advances in recent years have helped earth science researchers to identify and map the distribution of target minerals on the Earth s surface (Sadeghi et al, 2013). Moreover, the location of the project area in arid region make the use of remote sensing a powerful tool for general prospecting.four Landsat 7 ETM+ scenes: path 172 row 45; path 172 row 46; path 173 row 45; path 173 row 46 were mosaicked and subset to obtain a full coverage of the study area. 682

3 The band ratio TM5/7 separates lithologies containing hydroxyl-bearing minerals and carbonates with absorption features in the region 2.2 to 2.3µm. Ratio values of unaltered rocks approach the unity (1.00), whereas in altered rocks are much greater than unity ( 1.45; Sabins, 1999). TM5/4 ratio distinguishes rocks and soils from vegetation and in some cases enhances silicified or bleached zones of alteration and frequently used to highlight ferric oxides in vegetated areas.tm 3/1 shows high values for iron-stained hydrothermally altered rock and ferric oxides in general because iron minerals have low reflectance in band 1 and high reflectance in band 3(Sabins, 1999). The digital image processing was directed towards the mapping ofalteration zones through the band ratioing techniques.using the spectral characteristics of the iron oxide and hydroxylbearing mineral, described above, two ratio colour composite images were prepared. These ratio colour composites are intended to enhance the iron oxides and clay minerals which are common in alteration zones. The first ratio colour composite image was prepared by assembling the band ratios: 5/7, 3/1, 4/3 in RGB, respectively (Fig. 2.A). This image is termed the hydrothermal composite.the second one was prepared assigning the band ratios 5/7, 5/4, 3/1 to RGB guns,respectively. This image is termed the mineral composite(fig. 2.B). These images singled out gold prospective sectors judged by their characteristic signals. Accordingly, the geochemical prospecting was directed inthe field towards the target areas obtained from the results of the digital imageprocessing. 683

4 Fig. (2). band ratio color composite obtained by assigning the band ratios: A: 5/7, 3/1, 4/3; B: 5/7, 5/4, 3/1 to RGB,respectively. 3.Gold deposits in the study area The Hamisana area is of quite interestedwith respect to prospecting for gold mineralization. This area showsa variety of rock types and structures such as ophiolitic units, greenstoneand sheer zones suitable for gold mineralization. The gold depositsencountered in the studyarea are of two types: volcanogenic massive sulphides (VMS) andauriferous quartz veins. 3.1 Volcanogenic massive sulphides (VMS) Volcanogenic massive sulphides (VMS) are typically occur as lenses of poly-metallic massive sulphides that form at or near the seafloor in submarine volcanic environments. They form from metal-enriched fluids associated with seafloor hydrothermal convection. Their immediate host rocks can be either volcanic or sedimentary. VMS deposits are major sources of Zn, Cu, Pb, Ag, and Au, and significant sources for Co, Sn, Se, Mn, Cd, In, Bi, Te, Ga, and Ge.The VMS deposit found in Orshab area(photo 1), occurs as a lens elongated in the N-S direction and it was explored by OrshabMining Co. Photo (1).Volcanogenic massive sulphides (VMS) in Orshab area 3.2 Auriferous quartz veins Greenstone-hosted quartz veins deposits occur as quartz and quartz-carbonate veins, with valuable amounts of gold and silver, in faults and shear zones located within deformed terrains of ancient to recent greenstone belts commonly metamorphosed at the greenschist facies. This type of deposits was encountered in different areas such as Aberkateib, Kiaw and Blendalwateib. The indigenous mining is more extensive on these deposits. Geochemicalprospecting was 684

5 conducted to investigate the gold-bearing quartz veins.the potential quartz veinsare restricted in to two main directions of mineralization: N-S and NE-SW. Mineralized quartz veins in Blendalwateib area were found havingthe N-S direction (Fig. 3.a)hosted in granitoid rocks which intruded the Meta-volcanosedimentary sequence of the greenschist metamorphic facies. The Auriferous quartz veins were found in this direction are parallel to the N-S sheer zone (Fig. 3.b)or injected alongthe axial plain of tight upright isoclinal folds in NNW-SSE direction. Referring to the geochemical analysis results of twenty three samples of quartz veins in Blendalwateib area, the maximum values of gold is ppm and minimum value is ppm. The overall analysis of residual soil and quartz veins samples, collected during the regional survey, showed that the gold concentrations occur in the southwestern part of Blendalwateib area. This is attributed primarily to the effect of shearing. Mineralized quartz veinsin Kiaw area are found to have the NE-SW trend(fig.3.c) hosted by ophiolite complex and Meta-volcanosedimentary sequences which are metamorphosed to greenschist facies. The auriferous quartz veins were found in this direction parallel to the direction of the sutures in the Red Sea region in NE-SW trend. Gold determination of fifteen quartz vein samples in Kiaw area showed that the maximum value is ppmand the minimum value is ppm.analysis of residual soil and quartz vein samples revealed that the gold concentration occur at the northeastern part of Kiaw area, which is due to the effect of shearing that covers large areasalongthe Hamisana shear zone. It is worthmentioning that any quartz vein directed E-W or incline more than 60 to the shearing direction gave negative results (Fig. 3.d). Fig. (3.a).Direction of auriferous quartz veins Fig. (3.b). The main trend of shearing 685

6 in Blendalwateib area. Fig. (3.c). Direction of auriferous quartz veins in Kiaw area Fig. (3.d). Direction of non-auriferous quartzveins in Kiaw area. 4. Geochemistry for gold and trace elements 4.1 General The purpose of geochemical measurements is to discover the abnormal chemical patterns or geochemical anomalies related to mineralization (Hawkes and Webb, 1962). The principle of geochemical prospecting is closely linked with mobility and geochemical association of elements. Elements of similar relative mobility tend to occur together under a given set of environmental conditions and some retain characteristic association throughout a wide range of different geological conditions. The presence of one member of such an association can therefore be used as a probable presence of the other member that may be difficult to detect. Pathfinder is a term indicates one or more elements (or minerals) that can be closely associated and can constitute a halo, which assists in finding sought-after mineral deposits (Levinson, 1974). Pathfinder occurs in primary environment with the element being sought or otherwise be derived from it. There is a direct and interpretable relation between the geochemical distribution of the pathfinder and the mineralization. 4.2 Evaluation of geochemical data The geochemical analysis was carried out for gold and trace elements in both quartz veins and alteration zones,where some element show values below the detection limit in a few samples. The geochemical data have been evaluated using basic statistics, histograms, correlation matrix, multivariate analyses (factor and regressionanalysis) and geochemical mapping, using SPSS 17.0 software. Values below the detection limits are represented by criteria X =0.5 X Lower limit before statistical analysis (Kelley and Kelley, 1992). 686

7 For all elements, the threshold value was chosen as (M+2S) (Lepeltier, 1969; Nichol et al., 1994). To aid in the interpretation of the geochemical data and to compare it with the geology, the anomalous value of gold and related trace elements have been utilized for producing symbol plot maps, which are then superimposed over the satellite image of the study area. The basic statistical parameters for Au,Ag, As, Cuand Pbare discussed in the following paragraphs. 4.3 Evaluation of gold and related elements in quartz veins It is evident from the histogram (Fig. 4) and skewness that the gold is normally distributed in chip samples. Fig. 4. Histogram of Au in chip samples Fig. 5. Histogram of Ag in chip samples As Cu Pb Gold (Au) 72.9 % (N=59) of the chip samples contain gold values above the detection limit. Gold content in chip samples vary from <0.001 ppm (detection limit) to 15.5 ppm. The background value for Au was calculated to be ppm and the threshold value was 4.6 ppm. The dispersion of gold in the chip samples is erratic (inhomogeneous) as suggested by the very high coefficient of variation (CV), about 339.7%. The anomaly coefficient (AC) of Au in the chip samples is very low, about 5.1%. The distribution of gold in chip samples is shown in Fig. (5). It was found that the high gold content in the investigated area is restricted to six localities or targets. 687

8 Silver (Ag) The Silver contents in chip samples range between <0.01 ppm (detection limit) and 9.2 ppm.the CV of Ag is very high about 371 %, which suggests the inhomogeneous dispersion of silver. The background value for Ag in the chip samples is ppm and the threshold value are 2.8 ppm. The AC of Ag in the chip samples is very low about 3.4%.The distribution of Ag concentrations in chip samples is presented in Fig. (6). It shows that the distribution of Ag anomalous values conform to a large extent with that of gold. This is not a surprising result since silver has been widely used as pathfinder for gold. Fig. 5. Distribution and target zones of gold (Au_ppm) in chip samples. Fig.6. Distribution of Silver (Ag_ppm) in chip samples. Arsenic (As) The arsenic content in chip samples ranges between <0.2 ppm and 653 ppm. The CV of As is very high, about 327.9%, which suggest the inhomogeneous dispersion of arsenic. The background value for Asis 0.7 ppm and the threshold value is ppm. The AC of As in the chip samples is very low about 3.4%.The distribution of As concentrations in chip samples is presented in Fig. (7). It shows that the distribution of asanomalousvalues have delineated the known gold and silver occurrences. 688

9 Copper (Cu) The copper concentrations in chip samples range between 3.1 ppm and 217 ppm. The CV of this element is very high, about 195.3%, indicating that the distribution of the Cu in chip samples is inhomogeneous. The background value for Cu in the chip samples is 7.6 ppm and the threshold value is 81.5 ppm.the AC of Cu in the chip samples is very low about 5.1%.The distribution of Cu anomalousvalues in chip samples is shown in Fig. (8). It was found that the high copper content in the investigated area is restricted in nine localities. Fig. 7. Distribution of arsenic (As_ppm) in chip samples. Fig.8. Distribution of Copper (Cu_ppm) in chip samples. Lead (Pb) Lead concentrations in chip samples vary from < 0.5 ppm to 248ppm. The CV of this element is very high, about 375.7%, indicating the inhomogeneousdistribution of Pb in chip samples. The background value for Pb in the sediments is 1.2 ppm and the threshold value is 83.6 ppm. The AC of Pb in the chip is very low about 3.9%.The distribution of anomalous Pb in chip is shown in Fig. (9). The Pb content is rich in six localities in the investigated area. 689

10 Fig. 9. Distribution of lead (Pb_ppm) in chip samples. In an attempt to further definee areas of potential mineralization, factor analysis (Extraction: principal component) with varimax rotation is used. Five factor models have been chosen for the chip sample data set. Significant factor loadings are chosen greater than 0.7. After statistical evaluation of chip sample data, it is decided to consider all samples with scores between as moderately anomalous and those with score > 3.0 as strongly anomalous. 4.4 Evaluation of gold and related elements in alteration zones Elements such as B, Bi, Ge, Nb, Re, S, Se, Sn, Ta, Te, Ti and Ti show values below the detection limit in some samples. The other elements are above the detection limit in all samples. The basic statistics for gold and trace elements in alteration samples willl be discussed in the following paragraphs. The histogram (Fig. 10) and skewness shows that the gold is normally distributed in the alteration samples. 690

11 Fig. 10. Histogram of Au, in alteration samples in chip samples Ag& As Cu Pb Gold (Au) All the alteration samples contain gold values above the detection limit. Gold content in alteration samples vary from ppm to 11.4 ppm. The background value for Au is calculated to be ppm and the threshold value is 4.8 ppm. The dispersion of gold in the alteration samples is erratic (inhomogeneous) as suggested by the very high CV of 238.2%. The AC of Au in the alteration samples is very low, 8.6%. The distribution of gold in alteration samples is shown in Fig. (11). It was found that all the Au high concentrations in the investigated area are restricted in five localities or targets 1, 2, 3, 4 and

12 Fig. 11. Distribution of gold (Au in ppm) in alteration samples. Fig.12. Distribution of silver (Ag in ppm) in alteration samples. Silver (Ag) The Ag contents in alteration samples range between 0.01 ppm and 0.52 ppm. The CV of Ag is very high, about %, which suggest the inhomogeneous dispersion of silver. The background value for Ag in the alteration samples is 0.02 ppm and the threshold value is 0.23 ppm. The AC in the alteration samples is very low; about 5.7%.The distribution of Ag concentrations in alteration samples is presented in Fig. (12). It shows that the anomalous distribution of Ag is restricted in central and southern part of the area. Arsenic (As) The arsenic contents in alteration samples range between 2.5 ppm and 1660 ppm. The CV of As is very high, about %, which suggest the inhomogeneous dispersion of As. The background value for As in the alteration samples is 10.4 ppm and the threshold value is ppm. The anomaly coefficient AC of As in the alteration samples is very low, about 8.4%.The distribution of As concentrations in alteration samples is presented in Fig. (13). The As content is rich over the whole area and the anomalous contents have delineated the known gold and silver occurrences. 692

13 Fig. 13. Distribution of arsenic (As in ppm) in alteration samples. Fig. 14. Distribution of copper (Cu inppm) in alteration samples. Copper (Cu) The Cu concentrations in alteration samples range between 6.9 ppm and ppm. The CV of this element is relatively low, about 66.4 %, indicating that the distribution of the Cu in alteration samples is homogeneous. The background value for Cu in the alteration samples is 32.1 ppm and the threshold value is ppm. The AC in the alteration samples is very low; about 11.4%.The distribution of anomalous Cu in alteration samples is shown in Fig. (14). It was found that the Cu content is rich over the whole area. Lead (Pb) Lead concentrations in alteration samples vary from 0.3 ppm to 75.4 ppm. The CV of this element is very high, about 172.7%, indicating that the distribution of the Pb in alteration samples is inhomogeneous. The background value for Pb in the alteration samples is 2.12 ppm and the threshold value is 35.7 ppm. The AC of Pb is very low about, 5.7%.The distribution of anomalous Pb in alteration samples is shown in Fig. (15). It was found that the Pb content is rich in the central and southern parts of study area. 693

14 Fig. 15. Distribution of lead (Pbinppm) in alteration samples. The correlation coefficient for the alteration analyzed samples (N=35) coefficients of correlations Rs> 0.2 are significant. Weakly significant positive correlation exists between Au and Ba and Hg. Strong significant positive correlation exists between Au and Ag and As indicate that Ag and As can be used as pathfinders for gold. Au shows significant negative correlation with Hf and Zr.The high correlation between Cr, Ni and Co is due to the presence of mafic minerals. Correlation between Cu, Fe, Pb, Mn and Zn may indicate presence of sulphide minerals in alteration samples. 6. Conclusion The Hamisana Shear Zone (HSZ) is a broad zone of deformation approximately 50 km wide and at least 300 km long, making it one of the largest basement structures in NE Africa. The study area dominated by meta-sedimentary, meta-volcanic units mainly meta andesite with less common other volcanic varieties and ophiolitic rocks. These layered sequences are intruded by the syn- to late-orogenic and post-organic igneous intrusions, in which the granitic composition is dominant. The use of remote sensing and GIS techniques was found to be a powerful tool utilized in the geological mapping, structural elements delineation and mineral exploration. These different geological investigations were obtained through the application of different digital image processing techniques. 694

15 In the study area the gold had been detected in different forms such as; in quartz veins and alteration zones. The auriferous quartz veins represent the most potential gold bearing Lithology in the area. Most of the potential quartz veins are hypothermal to mesothernal in origin. The rocks alteration injected by stringers quartz veins are impregnated with the highest gold concentrations. The chip samples containing gold values vary from <0.001 ppm (detection limit) to 15.5 ppm. The background value for Au is calculated to be ppm and the threshold value is 4.6 ppm. It is found that all the known gold occurrences in the investigated area are restricted in six localities showing gold concentrations. All alteration samples containing gold values above the detection limit. Gold content in alteration samples vary from ppm to 11.4 ppm. The background value for Au in alteration zones is calculated to be ppm and the threshold value is 4.8 ppm. Strong significant positive correlation exists between Au and As, which indicate that As can be used as pathfinder for gold in chip samples. Correlation between Cu, Fe, Zn and Mn may indicate presence of sulphide minerals in chip samples. Strong significant positive correlation exists between Au and Ag and As indicate that Ag and As can be used as pathfinders for gold in alteration samples. Correlation between Cu, Fe, Pb, Mn and Zn may indicate presence of sulphide minerals in alteration samples. Factor analysis is very effective technique and has delineated more than 70% anomalous gold areas in chip samples, but not effective in alteration samples. References 1. Elsheikh, A.E.M., Elsayed Zeinelabdein, K.A.,Elkhidir, S.O.H. and Ibrahim, A.E., The geometrical configuration of the newly discovered Abu Deleig Sedimentary Sub-basin, Central Sudan, using remote sensing, structural analysis and geophysical survey. Arabian Journal of Geosciences.Arab J Geosci. 7: DOI /s Fitches,W.R., Graham, R.H., Hussein, I.M., Ries, A.C., Schackleton, R.M. and Price, R.C., The Late Proterozoic ophiolite of Sol Hamid, NE Sudan. Precamb. Res., 19: , Amesterdam. 3. Hawkes, H.K. and Webb, J. S., Geochemistry in mineral exploration. Harper and Row N. Y. pp Kelley, K.D. and Kelley, D.L., Reconnaissance exploration geochemistry in the central Brooks Range, northern Alaska: Implications for exploration of sediment-hosted zinc-lead-silver deposits. J. Geochem. Explor., 42:

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