ABSTRACT
Coal is considered as a vital energy mix that build the bedrock of energy access and bridge the energy demand gaps between different countries of the world. The search for Coal at an old mine working in Odagbo village is being carried out by artisan miners who indiscriminately dig underground tunnels in search of Coal. This approach is imprecise, laborious, and harmful to miners and may create geohazards that affect the community and potential coal resources. Electrical resistivity imaging was carried out at a mining site in Odagbo village Kogi state, Nigeria. The research aimed to characterize Coal seam within the study area. The study was targeted at determining the resistivity value associated with the Coal seam and the probable depth of the Coal seam. The LUND imaging system consisting of the ABEM Terrameter SAS 4000, electrode selector ES 464, stainless-steel electrodes, multi-core cables, and jumpers were used to acquire the data in this study. The protocol chosen was the dipole-dipole array because of its supreme sensitivity to; resistivity variation below the electrode in each dipole pair, horizontal variation of resistivity, and to 3D structures. Data processing was done using RES2DINV software. The result of the resistivity imaging revealed three layers of earth materials closely related to resistivity values at a depth of about 30 m from the ground surface. The first layer had resistivity values averagely greater than 700 Ωm. The second layer had resistivity values lower than 2200 Ωm. This layer is probably the host of the coal seam. The third layer had resistivity values greater than 700 Ωm. Coal seams are probably more at the North-East of the survey area and the coal seam is suspected to have resistivity values ranging from about 67 Ωm to 549 Ωm and depth varying from 12 m to 25 m.
TABLE OF CONTENTS
TITLE PAGE
DECLARATION ii
CERTIFICATION iii
ACKNOWLEDGEMENT iv
DEDICATION v
ABSTRACT vi
TABLE OF CONTENTS vii
LIST OF FIGURES x
LIST OF TABLES xiii
LIST OF PLATES xiiii
CHAPTER ONE 1
INTRODUCTION 1
1.1 Background to the Study 1
1.2 Statement of the Problem 5
1.3 Justification of the Study 5
1.4 Aim and Objectives 6
1.5 Location of the Study 7
1.6 Geology of the Study Area 8
CHAPTER TWO 11
LITERATURE REVIEW 11
2.1 The Coal Industry 11
2.2 Previous Work 15
2.3 Resistivity Imaging 19
2.3.1 Theory of the Electrical Method 23
2.3.2 Electrical Resistivity of Earth Materials 28
CHAPTER THREE 31
MATERIALS AND METHODS 31
3.1 Materials 31
3.2 Methodology 31
3.2.1 Reconnaissance Survey 31
3.2.2 Instrumentation: The ABEM LUND Imaging System 32
3.3 Choice of Array Configuration for the Survey 36
3.4 Data Acquisition 37
3.4.1 Field problems 41
3.5 Data Processing 42
CHAPTER FOUR 46
RESULTS AND DISCUSSION 46
4.1 Results and Geological Interpretation 46
4.2 Correlation of 2D Tomography with Lithological Borehole Data 47
4.3 Result of Processed Field Data 49
4.3.1 Profile 1 49
4.3.2 Profile 2 50
4.3.3 Profile 3 51
4.3.4 Profile 4 52
4.3.5 Profile 5 53
4.3.6 Profile 6 54
4.3.7 Profile 7 55
4.3.8 Profile 8 56
4.3.8 Profile 9 57
4.4 Correlation of Profiles for the Detection of Continuity of the Subsurface Structures 59
4.5 Discussion 61
CHAPTER FIVE 64
CONCLUSION AND RECOMMENDATION 64
5.1 Conclusion 64
5.2 Recommendations 64
REFERENCES 65
LIST OF FIGURES
Figure 1.1: Location Map showing the Study Area and its environs 7
Figure 1.2: Geological Map of Anambra Basin Showing Study Area modified from (Bankoleet al., 2016). 10
Figure 2.1: Coalification stages during coal generation (Langenberg, et al., 1990) 11
Figure 2.2: Coal specification and uses (Courtesy, www.UKMinerals.com) 15
Figure2.3:Distortion of current flow lines in (A) high and (B) low conductive anomaly (Joneset al., 2014). 20
Figure 2.4: General four-electrode configuration with Current (C1, C2) and Potential (P1, P2) Distributions within Homogeneous Isotropic ground (Telford et al., 1990; Arjwech & Everett, 2015). 21
Figure 2.5: 2D data collection using multi-electrode resistivity system (Lokeet al., 2013). 22
Figure 2.6: Popular electrode arrangements modified from Samouolian, et al. (2005) 28
Figure 2.7: Resistivities of Rocks, Soils and Minerals adapted from Palacky, (1988). ----- 30
Figure 3.1: A Schematic diagram of an automated multi-electrode resistivity system ( (Stummer & Maurer, 2001). 33
Figure 3.2: The dipole-dipole array configuration (Zhou et al., 2000) 36
Figure 3.3: Google earth image illustrating the ERI layout in the study area (courtesy Google earth software). 39
Figure 3.4: An example of a profile showing data set with a few bad data points. (Loke, 2010). 42
Figure 3.5: (a), (b) are two possible arrangements of the blocks used in a 2-D model together with the datum points in the pseudosection (Edwards, 1977) 44
Figure 3.6: 2D Imaging data processing flow chart 45
Figure 4.1: Stratigraphic Column of Odagbo Coal seam 48
Figure 4.2: Inverse Resistivity Model of Profile 1 49
Figure 4.3: Inverse Resistivity Model of Profile 2 50
Figure 4.4: Inverse Resistivity Model of Profile 3 51
Figure 4.5: Inverse Resistivity Model of Profile 4 52
Figure 4.6: Inverse Resistivity Model of Profile 5 53
Figure 4.7: Inverse Resistivity Model of Profile 6 54
Figure 4.8: Inverse Resistivity Model of Profile 7 55
Figure 4.9: Inverse Resistivity Model of Profile 8 56
Figure 4.10: Inverse Resistivity Model of Profile 9 57
Figure 4.11: 3D pseudo-sections horizontal slice of Study Area 58
Figure 4.12:2D Resistivity inversions of two profiles in NW – SE direction merged together, located near open pit mine site. 60
Figure 4.13: 2D Resistivity inversions of five profiles in NW – SE direction merged with two profiles in E – W direction, located in an unexcavated land 61
LIST OF TABLES
Table 3.1: Coordinates of start points, midpoints and end points along the profiles 40
Table 4.1: Lithological units of Odagbo Coal seam adapted from (Umeji, 2005) 47
LIST OF PLATES
Plate I: Old mine workings (Left) and artisanal mining activities (Right) in Odagbo Area.-- 5
Plate II: Excavation of coal by Dangote Company in Unupi village (Left) and by artisan miners in Odagbo Area (Right). 6
Plate III: ABEM LUND Imaging System and accessories. 35
Plate IV: ERI data acquisition in the study Area. 41
CHAPTER ONE
INTRODUCTION
1.1 Background to the Study
Energy is an essential facet of development, yet, the world is faced with twin energy-related challenges: one of energy insufficiency and affordability, and the other of energy inefficiency and environmentally friendly to meet economic development and population growth. As an effect, many countries use different types of energy mix such as crude oil, natural gas, coal, nuclear, hydroelectricity, and alternatives such as solar radiation and wind to meet an increasing trend of global energy demand. Hence, there is a growing search for sustainable energy access targets that balances the crisis between development and the environment.
Coal is considered as a vital energy mix that build the bedrock of energy access and bridge the energy demand gaps between different countries of the world (Board, 2009; Khatib, 2012) This is because, it is readily combustible organic rock (Schopf, 1956), and is one of the earth‟s resources found in abundance and widely distributed around the world with reserves of about 990 billion tons for all types of coal available for consumption (Brown, 2012). Its attractive attributes stimulated man‟s principal research interest in Coal (Aja & Emeribe 2000; Ward, 2003; Gupta, 2007; Tsikritzis et al., 2008) for exploitation and usage domestically and globally. Coal consumption has grown to fuel 42% of global electricity production (Birol, 2008). Countries like Poland, South Africa, China, and Australia rely on Coal for over 94%, 92%, 77%, and 76% of their electricity respectively (Board, 2012). Coal is probable to remain an indispensable component of the energy mix to complement a range of energy sources such as oil and gas reserves and nuclear energy for sustainable energy future, especially in developing countries (Board, 2009; Miller, 2011; Oji et al., 2012; Schnapp& Smith, 2012; Mills, 2014; Cozzi & Gould, 2015; Oberschelpet al., 2019).
In Nigeria, Coal was first discovered in Udi near Enugu in 1909 (Borishade et al., 1985; Famuboni, 1996; Obaje et al., 1996; Obaje & Hamza, 2000; Ogala et al., 2005;Michael et al., 2008; Olayande et al., 2012; Ogala, 2018), and its extensive exploration reported an economic estimate of about 639 million tons proven reserves and about 2.8 billion tons inferred reserves distributed over some States (MMSD, 2006; Obaje, 2009; Mallo, 2012; Sada 2012; Christine, 2015), but mostly within the Benue Trough geological province (Kogbe, 1976). Onakoyaet al., (2013)stated that Nigerian coal consists of about 49% sub- bituminous, 39% bituminous, and 12% lignite coals within coalfields of two main groups: the Turonian-Coniacian and the Campano-Maastrichtian coals. According toAgagu & Ekweozor, (1982), Orajaka et al., (1990), Akande et al., (1992), and Ogala (2011), the Cretaceous-Tertiary Anambra sediments contain coal reserves of different ranks occurring within formations. In the Lower Benue Trough, lignite and sub-bituminous coals occur within the Mamu and Nsukka Formations (Middle Campanian–Late Maastrichtian). These two distinct formations (called the Lower Coal Measures and the Upper Coal Measures) are separated by a great thickness of sandstone (Ajali sandstone) (Tattam, 1944). Lignite deposits occur in the Oligocene-Miocene Ogwashi-Asaba Formation. The Middle Benue Trough contains high-volatile bituminous coals found within the Awgu Formation (Middle Turonian–Early Santonian). The Upper Benue Trough contains lignites and sub-bituminous coals occur in the Gombe Sandstone Formation (Early Campanian–Late Maastrichtian) (Felix &Yomi, 2013). Together, the coal and lignite resource potentials are estimated at 1.5 billion tons and 300 million tons respectively.
However, the discovery of oil at Oloibiri in Bayelsa State in 1956 and the total dependence on oil and oil-derived foreign exchange in planning the nation‟s economy resulted in a steady decline of coal production and complete neglect of the coal industry with all its great economic potentials in the last few decades (Nwaobi, 2012; Odesola et al., 2013). But, with increasing demand for more sustainable energy resources to meet economic growth and national development, the revitalization and further development of the coal industry regardless of the issues of acid mine drainage (AMD), infrastructural challenges, and lack of current geophysical data in coal sector can meet the energy demands of Nigeria‟s growing population (Ibitoye & Adenikinju, 2007; C.I.A.B., 2008; Board, 2009; World Coal Institute, 2009; Oguejiofor, 2010; Akujor et al., 2011; Board, 2012; Ohimain, 2014; Chukwu et al., 2016).
Geologically, Coal occurs in strata and exhibits significantly different petrophysical parameters in comparison to its surrounding rocks typically found in sedimentary basins (Hatherly, 2013), and requires advanced prospecting to provide necessary data for its exploration. Different techniques ranging from geological, geochemical, geophysical to drilling are been employed to evaluate coal deposits. However, its electrical properties have been suggested to be important for proper characterization during mining (Tiwary, 1993). The geophysical technique is very useful in many areas of environmental studies and conventional geotechnical testing as it uses non-invasive, cost-effective methods to probe the Earth (Anderson, et al., 2008; Arjwech et al., 2013; Arjwech & Everett, 2015). In Coal investigation, it is advantageous before coal mining begins (Lei, 2015).
Geophysics applies the principles of physics to study the Earth (Kearey et al., 2002) by detecting and analyzing variation in physical properties that are response to anomalous bodies in the Earth. Measurements are done from above or below the Earth's surface at aerial, orbital, or marine platforms with comprehensive areal coverage at reduced prospection work time using a great variety of non-destructive sensing instruments. Different geophysical methods ranging from gravity, magnetics, seismic, resistivity, ground-penetrating radar, radiometric to electromagnetic are distinctively sensitive to contrasts in physical properties in the subsurface (Chalikakis et al., 2011). However, the most informative data of the subsurface can be obtained following a combination of these methods. The results of geophysical exploration when combined with borehole data provide reliable data for future prospecting.
Of these methods, the resistivity method was employed for this research. The reason for the choice of this survey method is that rock materials show wide variation in resistance to electrical current flow and such contrast forms the basis for the application of the electrical resistivity method in coal exploration. Accordingly, the Electrical Resistivity Imaging (ERI) technique with a multi-electrode system was adopted to obtain imagery of the subsurface as most geological structures are not one-dimensional (1D). This technique has proven effective when routinely used in environmental engineering under a variety of field conditions and geological settings (Dahlin, 2001; Tselentis & Paraskevopoulos, 2002; Beresnev et al., 2002; Godio & Naldi, 2003; Vickery & Hobbs, 2000; Wu, et al., 2016; Nwafor et al., 2017). Some studies (Ewing et al., 1936; Verma & Bhuin, 1979 and Singh et al., 2004), have confirmed that the electrical resistivity imaging (ERI) survey methods respectively can successfully be used to study coal deposits. Ewing et al., (1936) revealed coal to have high resistivity to the surrounding formation when detected from borehole logs and DC resistivity surveying. Verma & Bhuin, (1979) and Singh et al., (2004), in their report, confirmed this proposition using 1D and 2D electrical resistivity methods respectively for coal investigation.
1.2 Statement of the Problem
Coal occurs in strata with surrounding rocks and is explored and mined through scientific approaches. However, the search for Coal at an old mine working in Odagbo village is being carried out by artisan miners. These miners indiscriminately dig underground tunnels in search of Coal (see Plate I).This approach is imprecise, laborious, and harmful to miners and may create geohazards that affect the community and potential coal resources. These prompted the need for geophysical research, to obtain coal‟s subsurface data for mining within the area.
Plate I: Old mine workings (Left) and artisanal mining activities (Right) in Odagbo Area.
1.3 Justification of the Study
The increased demand for energy to meet the energy crisis in Nigeria has resulted in the search for more sustainable energy sources. Coal is one of the most important minerals in Nigeria that offer a major energy mix for electric power generation and feedstock for chemicals, fuels, and steel production for a developing country (see Plate II). It is a strategic resource that is widely attractive because of its abundance in many countries of the world. Hence, the need for the development of Coal resources following proper exploration methods to meet sustainable development and attain the world standard.
To the best of my knowledge, no published work on geophysical research has been carried out in the study area. This geophysical research will provide vital information on coal resources that may serve as an incentive to potential investors and future researchers on coal in the area.
Plate II: Excavation of coal by Dangote Company in Unupi village (Left) and by artisan miners in Odagbo Area (Right).
1.4 Aim and Objectives
The aim of this research was to characterize Coal bearing layer at Odagbo Village, Kogi State, Nigeria using electrical resistivity imaging method.
The objectives of this research were to;
i. generate subsurface geoelectric sections of the study area,
ii. estimate the range of resistivity values associated with the subsurface rich in Coal seam,
iii. estimate the depth to the subsurface layer that is rich in the Coal seam
1.5 Location of the Study
Odagbo is a rural settlement in Ojoku district towards the northeastern part of Ankpa Local Government Area of Kogi State.It lies between latitudes 7º 28´ 30´´ N and 7º 29´ 00´´ N and longitudes 7º 43´ 30´´ E and 7º 44´ 0´´ E (see Figure 1.1).
Figure 1.1: Location map showing the Study Area and its environs.
1.6 Geology of the Study Area
Odagbo is underlain by two geological formations, the Mamu Formation (coal-bearing) and Ajali Formation which form part of the Anambra Basin (Umeji, 2005) (see figure 1.2). The Anambra Basin is one of the intracratonic basins in Nigeria resulting from the deformation of the major depositional axis of the Benue Trough (Murat, 1972; Weber & Daukoru, 1975; Benkhelil, 1987). It is located in the southeastern part of Nigeria and lies between longitudes 6.30E and 8.00E, and latitudes 5.00 N and 8.00 N. It trends NE - SW obliquely across Nigeria with origin linked to the tectonic processes of separation of the African and South American plates in the Early Cretaceous (Murat 1972; Burke et al., 1972). It is bounded in the west by the Okitipupa Ridge, in the south by the Niger Delta Basin, to the northwest, it directly overlies the Basement Complex and interfingers with the Bida Basin. The basin is delimited in the north by the Basement Complex, the Middle Benue Trough, and the Abakaliki Anticlinorium. The basin covered an area of about 40,000 square kilometers with sediment thickness increasing southwards to a maximum thickness of 12,000 m in the central part of the Niger Delta. The sedimentary rocks are a Cretaceous depo-center that received Campanian to Tertiary sediments (Short & Stauble, 1967; Murat, 1972; Weber & Daukoru, 1975; Benkhelil, 1989; Nwajide, 1990; Obi et al., 2001; Nfor et al., 2005) such that strongly folded Albian-Coniacian succession (Pre-Santonian sediments) is overlain by nearly flat-lying Campanian-Eocene succession. It has enormous lithologic heterogeneity in both lateral and vertical extension (Agagu & Adighije, 1983; Akande et al., 2007; Akinyemi et al., 2013).
The sequence of depositional events suggests a progressive deepening of the basin from the lower coastal plain and shoreline deltas to the shoreline and shallow marine deposits (Adeleye, 1989; Anyanwu &Arua 1990; Fayose &Ola 1990; Akande & Mocke 1993; Adetona& Abu, 2013). This resulting succession comprises the Nkporo Group, Mamu Formation, Ajali Sandstone, Nsukka Formation, Imo Formation, and Ameki Group. Detailed stratigraphic description of these formations has been reported (Petters 1982; Agagu et al., 1985; Reijers 1996). However, the Asu-River Group is the oldest facies (in the basin) dated Albian to Lower Cenomanian. This is overlain by Eze-Aku Formation dated Upper Cenomanian to Turonian age; further overlain by the pre-Santonian sediment deposit referred to as Awgu Formation dated Coniacian in age (Ola-Buraimo, 2013). Nkporo Group is overlain by Mamu Formation. It was deposited in Early Maastrichtian and comprises a succession of siltstone, shale, coal seam, and sandstone (Kogbe, 1976& Obi, 2004). The Mamu Formation (Lower coal measures) consists of siltstones, mudstones, grey carbonaceous shales, sandstones, and coal seams at several horizons (Ameh, 2013). The shales and mudstones are alternated with thin bands of siltstones. The rich coal deposits of Middle – Early Maastrichtian ages suggest brackish marshes during their deposition (Ogala et al 2012). Ajali sandstone (Maastrichtian) overlies Mamu Formation (Reyment, 1965 & Nwajide, 1990) which is mainly unconsolidated coarse-fine grained, poorly cemented; mudstone and siltstone (Kogbe, 1976). Ajali Sandstone is overlain by the diachronous Nsukka Formation (Maastrichtian-Danian) which is also known as the Upper Coal Measure (Reyment, 1965). Imo Shale (Paleocene) overlies Nsukka Formation (Nwajide, 1990). It comprises clayey shale with occasional ironstone and thin sandstone in which carbonized plant remains may occur (Kogbe, 1976). The Eocene stage was characterized by the regressive phase that led to the deposition of the Ameki Group.
Figure 1.2: Geological Map of Anambra Basin Showing Study Area modified from (Bankole, et al., 2016).
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