Appraisal of geothermal potentials of some parts of the Abakaliki Anticlinorium and adjoining areas (Southeast Nigeria) using magnetic data

The Abakaliki Anticlinorium and its adjoining areas were appraised with the object of delineating high geothermal potential zones. Spectral depth analysis involving an improved centroid technique was used to analyze high-quality magnetic data. The obtained geothermal parameters were gridded to map various geothermal features within the investigated area. The obtained results varied from 4.99–9.35 km, 2.31–6.15 km, 6.11–16.28 km, 35.63°C–94.93°C/km, and 89.07–237.32 mW/m² for centroid depth, top depth, Curie point depth, geothermal gradient, and heat flow values, respectively. The delineated semioval structure in the central zone of the investigated region characterized by a shallow Curie point depth (< 8.5 km) correlates with the location of the high-heat flow (>191.0 mW/m²) and geothermal gradient (>74.0°C/km) region. The high geothermal potential of the region is triggered by the massive post-rift tectonic event of the Santonian period related to the Abakaliki Anticlinorium. Further geophysical exploration programs should be carried out before exploitation activities at anomalous geothermal regions.

1 Introduction

Due to challenging energy difficulties in Nigeria, where the demand for electrical power generated from hydropower and hydrocarbon plants exceeds the supply, alternative energy sources (preferentially renewable) are being extensively explored. On the whole, researchers (Nwachukwu, 1976; Avbovbo, 1978; Babalola, 1984) have previous reported the imprints of geothermal resources in the form of warm springs in Nigeria. The Abakaliki Anticlinorium, which is the main constituent unit of the Lower Benue Trough (LBT) like the Anambra Basin, Calabar Flank, and the Afikpo Syncline, is dominated by Santonian intrusions, hydrothermal modification, geologic features, brine fields, and related rift mineralization (Adewumi and Oladoyin, 2015; Ekwok et al., 2020a; Ekwok et al., 2020b; Ephraim et al., 2022).

For some decades, intense geophysical and geological investigations have been carried out in the LBT (Ofoegbu and Onuoha, 1991; Ekwok et al., 2019). Previous studies in the Abakaliki Anticlinorium and contiguous inland basins focused on the exploration for lead–zinc (Mackay, 1946; Bogue and Reynolds, 1951; Farrington, 1952; Dim, 2021; Ani et al., 2023), coal (Simpson, 1955; De Swardt and Casey, 1963), barites (Akpan et al., 2014), brine fields (Eseme et al., 2002; Tijani, 2004; Ekwok et al., 2022a), limestone (Akpan et al., 2004), and hydrocarbon (Ofoegbu and Onuoha, 1991). Recent studies in the Nigerian Benue Trough focused on reconnaissance exploration activities for geothermal energy (Abraham et al., 2015; Nwankwo, 2015; Abraham and Nkitnam, 2017; Chukwu et al., 2018; Abraham et al., 2019; Abdullahi and Kumar, 2020; Ejiga et al., 2022; Alfaifi et al., 2023; Ekwok et al., 2023). These contemporary geoscience studies involved the use of the magnetic surveying technique (Essa et al., 2021; Mehanee et al., 2021). Other geophysical procedures (such as electrical resistivity, gravity, bottom-hole temperature (BHT), seismic, transient electromagnetic, and magnetotelluric processes) are also applied in geothermal energy research and monitoring (Nwachukwu, 1975; Nwachukwu, 1976; Ndombi, 1981; Simiyu and Keller, 1997; Mariita, 2010; Coppo et al., 2015; Ars et al., 2019; Saibi et al., 2021). Nevertheless, high-resolution magnetic data and good geologic knowledge are frequently used in tandem to address uncertainties during the interpretation (Mariita, 2010). Largely, magnetic technology is the most cost-effective geophysical method for acquiring an adequate model for a geothermal structure (Mohammadzadeh-Moghaddam et al., 2016). Yet, this model can be nonunique, which is unexpected in the exploration of geophysics (Mehanee, 2022). Nevertheless, an inverse problem usually connected with magnetic data is often ill-posed, thus making the solution nonunique and unstable (Essa and Elhussein, 2017). However, a reliable solution for an ill-posed problem can be realized by having prior geologic knowledge or the application of some cutting-edge enhancement methods (Essa and Elhussein, 2018).

In this study, magnetic data, which probe different rock properties (Ross et al., 2013; Ekwok et al., 2019; Jackish et al., 2019; Ekwok et al., 2022b), were applied to obtain useful information on buried geothermal anomalies (Abraham et al., 2019) related to the Santonian Abakaliki Anticlinorium and surrounding regions. This geophysical method has been effective in locating faults and fracture zones related to geothermal reservoirs, defining a basement framework in a geothermal region (Nishijimaa and Naritomi, 2017; Witter et al., 2017), and intrusive bodies (Ekwok et al., 2021a) and magma chambers related to the heat source of a geothermal system (Represas et al., 2013). Moreover, the magnetic technique can be used in the mapping of zones with reduced magnetization caused by thermal activities (Georgsson, 2009). It is also a suitable method for hydrothermal system assessment and mapping of buried anomalies caused by magmatic and granitic bodies including geologic features (Ekwok et al., 2022c). Such regions are characterized by different magnetizations from the unaltered host rocks (Abraham et al., 2019). The power spectrum involving the improved centroid technique (Bhattacharyya and Morley, 1965; Lazarian and Esquivel, 2003; Bansal et al., 2011) was employed in the magnetic data to obtain the Curie point depth (CPD), geothermal gradient, and heat flow gridded maps. The computation of these three spectral parameters from the same magnetic data will considerably enhance the dependability of geothermal results. In regions like the Abakaliki Anticlinorium, where deep borehole data are lacking, Curie depth results from magnetic data can be used to map geothermal anomalies (Bansal et al., 2011; Bansal et al., 2013; Salem et al., 2014; Bansal et al., 2016; Abdullahi and Kumar, 2020).

Curie depth is commonly estimated from magnetic data using a spectral analysis approach based on randomly uncorrelated and fractal source distributions (Bansal et al., 2011; Bansal et al., 2016; Ravat et al., 2016). Bansal et al. (2011) presented a robust method for Curie depth estimation by incorporating a fractal parameter into the traditional method proposed by Bhattacharyya and Leu (1977). The improved centroid procedure involves the approximation of the top to the buried magnetic source and estimating the centroid depth to the magnetic anomaly (Bansal et al., 2011). This technique, which has a comparative advantage over conventional techniques (Bansal et al., 2016), allowed the calculation of the depth to the bottom of the magnetic sources. It provides better estimates from the power spectrum plots (log) (Lazarian and Esquivel, 2003; Bansal et al., 2011).

2 Location and geologic setting of the investigated area

The investigated area, which is part of the LBT, covers some parts of the Tertiary-Recent Benin Formation, and Abakaliki Anticlinorium (Figure 1). The study area is bordered in the west, southwest, and south by the Tertiary-Recent Benin Formation. The study location is positioned between longitudes 6,030′E and 8,000′E and latitudes 5,000′N and 7,000′N.

FIGURE 1

FIGURE 1. Geologic map of the study area.

The sequence of events that resulted in the development of the Benue Trough and its component units has been previously reported (Onuoha and Ofoegbu, 1988). A thick Cretaceous sedimentary sequence occupies the LBT and sits on the granitic and magmatic rocks of the Precambrian basement (Akpan et al., 2014; Akpan et al., 2018). The Albian Asu River Group (ARG), which is composed of bluish–black sandstone units, sits on the Precambrian basement. Overlying the ARG is the Eze-Aku Formation (EAF) composed of sandy and shelly limestones, calcareous shales and siltstones, and calcareous sandstones (Reyment, 1965). The Awgu Shales are marine fossiliferous, gray–bluish shales, limestones, and calcareous sandstones of the Coniacian age. They are covered by the Nkporo Shales (Campanian), which are mostly marine, with some arenaceous sandstone members. Generally, the sedimentary sequences are severely affected by large-scale tectonic events, which occurred in two stages and culminated in the folding of the sediments (Nwachukwu, 1972). The folding episode that occurred in the Santonian period is the main cause of the development of the Abakaliki Anticlinorium. The asymmetry and reversed faults relating to the folds that were formed during this period reveal that they were primarily compressional. Benkhelil (1988) described the Abakaliki Anticlinorium events as a complete orogenic cycle involving sedimentation, magmatism, metamorphism, and compressive tectonics. The associated magmatic events cause the injection of several intrusive bodies into the EAF and ARG.

The sediments of the Abakaliki Anticlinorium (that is, the folded EAF and the ARG) are unconformably placed on top by the Nkporo Shale (Whiteman, 1982). Overlying the Nkporo Shale is the Benin Formation, which consists primarily of porous sands and gravels of varying grain sizes intercalated with thin clay and shale beds (Akpabio and Eyenaka, 2008). Deposits of recent alluvium and beach ridge sands can be found along the shores and estuaries of the Imo and Kwa Ibo rivers, including the flood plains of the creeks (Akpabio and Ekanem, 2009).

3 Materials and methods

3.1 Data acquisition

Fugro Airborne Surveys, Canada, acquired high-quality aeromagnetic data between 2005 and 2010. The data were acquired using a Flux Adjusting Surface Data Assimilation System with a flight-line space of 0.1 km, tie-line space of 0.5 km, and terrain clearance ranging from 0.08 to 0.1 km. Moreover, Fugro Airborne Surveys, Canada, subtracted the regional field from the magnetic data using the 10th (10th) generation of the International Geomagnetic Reference Field (IGRF). The main benefit of the IGRF is the consistency they provide in magnetic field survey practice, which began when the IGRF was made available and widely accepted (Reeves et al., 1997). The data employed in this research were processed into total magnetic intensity (TMI) gridded data. Since the data were collected at low latitude, the magnetic data were reduced to the equator (RTE) (Figure 2). Jain (1988) and Leu (1981) reported that RTE creates more dependable results, particularly at the middle and lower latitudes. The high-quality data were characterized by mean inclination, declination, and total field values of −16.40°, −2.57°, and 32,865.96 nT, respectively.

FIGURE 2

FIGURE 2. Total magnetic intensity data reduced to the equator.

3.2 Spectral analysis involving the centroid depth method

Spectral analysis using the centroid method (or spectral peak technique) is an effective tool used in the determination of CPD all over the world (Tanaka et al., 1999; Tanaka, 2017). It is often applied using the azimuthally mean power spectrum of magnetic anomalies (Tanaka, 2017; Wang and Liu, 2018). At low wavenumbers, the spectral peak method is based on determining the precise wavenumber of the spectral peak (Ross et al., 2006). In practice, however, most logarithmic power spectra of magnetic anomalies do not exhibit spectral peaks (Bouligand et al., 2009). The centroid technique applied in this research, rather than locating the spectral peak, is based on fitting the slope of the high- and low-wavenumber bands to calculate the top and bottom depths of the magnetic layer (Tanaka et al., 1999). The technique applied here is similar to the technique proposed by Spector and Grant (1970). The top bound and the centroid of a magnetic source, Z_t and Z₀, respectively, are computed from the power spectrum of magnetic anomalies and applied to approximate the basal depth of a magnetic source Z_b.

Assuming that the layer extends infinitely in all horizontal directions, the depth to the top bound of a magnetic source is small compared with the horizontal scale of a magnetic source, and magnetization M(x,y) is a random function of x and y, Spector and Grant (1970) introduced the power–density spectra of the total field anomaly Φ_∆T:

${\mathit{\Phi }}_{\Delta T}\left(k_x,k_y\right)={\mathit{\Phi }}_M\left(k_x,k_y\right)\times F\left(k_x,k_y\right),(1)$

$F\left(k_x,k_y\right)=4{\pi }^2{C}_m^2{\left|{\mathit{\Theta }}_m\right|}^2{\left|{\mathit{\Theta }}_f\right|}^2{e}^{-2\left|k\right|Zt}{\left(1-e^{-\left|k\right|\left(Z_b-Z_t\right)}\right)}^2,(2)$

where ${\mathit{\Phi }}_M$ is the power–density spectra of magnetization, C_m is a proportionality constant, and ${\mathit{\Theta }}_m$ and ${\mathit{\Theta }}_f$ are factors for the magnetization direction and geomagnetic field direction, respectively. This equation can be simplified by noting that all terms, except ${\left|{\mathit{\Theta }}_m\right|}^2$ and ${\left|{\mathit{\Theta }}_f\right|}^2$, are radially symmetric. Moreover, the radial averages of ${\mathit{\Theta }}_m$ and ${\mathit{\Theta }}_f$ are constant. If $M\left(x,y\right)$ is completely random and uncorrelated, then ${\mathit{\Phi }}_M\left(k_x,k_y\right)$ is a constant. Hence, the radial average of ${\mathit{\Phi }}_{\Delta T}$ is

${\mathit{\Phi }}_{\Delta T}\left(\left|k\right|\right)=A{e}^{-2\left|k\right|Z_t}\left(A{e}^{-2\left|k\right|Z_t}\right){\left(1-e^{-\left|k\right|\left(Z_b-Z_t\right)}\right)}^2,(3)$

where A is a constant. For wavelengths less than about twice the thickness of the layer, Eq. 3 approximately becomes

$\mathit{ln}\left[{\mathit{\Phi }}_{\Delta T}{\left(\left|k\right|\right)}^{\frac{1}{2}}\right]=\mathit{ln}B-\left|k\right|Z_t,(4)$

where B is a constant. We could estimate the top bound of a magnetic source by the slope of the power spectrum of the total filed anomaly. On the other hand, Eq. 3 can be rewritten as

${\mathit{\Phi }}_{\Delta T}{\left(\left|k\right|\right)}^{\frac{1}{2}}=C{e}^{-\left|k\right|Z_0}\left(e^{-\left|k\right|\left(Z_t-Z_0\right)}-e^{-\left|k\right|\left(Z_b-Z_0\right)}\right),(5)$

where C is a constant. At long wavelengths, Eq. 5 becomes

${\mathit{\Phi }}_{\Delta T}{\left(\left|k\right|\right)}^{\frac{1}{2}}=C{e}^{-\left|k\right|Z_0}\left(e^{-\left|k\right|\left(-d\right)}-e^{-\left|k\right|\left(d\right)}\right)\sim e^{{-}^{\left|k\right|Z_0}}2\left|k\right|d,(6)$

where 2days is the thickness of the magnetic source. From Eq. 6,

$\mathit{ln}\left\{\frac{\left[{\mathit{\Phi }}_{\Delta T}{\left(\left|k\right|\right)}^{\frac{1}{2}}\right]}{\left|k\right|}\right\}=\mathit{ln}D-\left|k\right|Z_0,(7)$

where D is a constant. We could estimate the top bound and the centroid of the magnetic source by fitting a straight line through the high-wavenumber and low-wavenumber parts of the radially averaged spectrum of $\mathit{ln}\left[{\mathit{\Phi }}_{\Delta T}{\left(\left|k\right|\right)}^{\frac{1}{2}}\right]$ and $\mathit{ln}\left\{\left[{\mathit{\Phi }}_{\Delta T}{\left(\left|k\right|\right)}^{\frac{1}{2}}\right]/\left|k\right|\right\}$ from Eqs 4–7, respectively. From the slope of the power spectrum, the top bound and the centroid of a magnetic layer composed of a horizontal (equivalent) layer are estimated. The basal depth of the magnetic source is

$Z_t=2Z_0-Z_b.(8)$

The obtained basal depth of the magnetic source is assumed to be the Curie point depth. The obtained Curie point depth reflects the average value of the area. If magnetization in Earth’s crust is arbitrarily and uncorrelatedly distributed, the mean azimuthal power spectrum can be employed to compute Z_t and Z_b by Eqs 6–8.

$q=k\frac{dT}{dz}.(9)$

Fourier’s law is a central relationship when considering conductive heat conveyance [53]. Fourier’s law assumes the following form in the 1D case, supposing a vertical direction for temperature disparity and a constant temperature gradient dT/dz, where q is the heat flux and k is the coefficient of thermal conductivity.

The Curie temperature (θ) can be well defined as

$\theta =\left(\frac{dT}{dz}\right)z_b,(10)$

where Z_b is the CPD, supposing there are no heat sources or heat sinks between Earth’s surface and the CPD, dT/dz is constant, and the surface temperature is 0°C. Spector and Grant (1970) proved that any particular depth to a thermal isotherm is in reverse proportion to heat flow. Eqs 9, 10 were used to calculate HF and GG values, which were based on CPD estimates derived from magnetic computations. We utilize the Curie point (h) for magnetite (580°C) with an average thermal conductivity of 1.80 and 2.5 Wm^-1 k⁻¹ for regions of sedimentary shale formation and igneous rock/older granite (Abraham et al., 2019), respectively.

4 Results

Some geophysical techniques are powerful tools in mapping geological structures (Pham et al., 2022; Kamto et al., 2023; Pham and Prasad, 2023; Xayavong et al., 2023) and in the appraisal of the lateral extent of several high-temperature geothermal anomalies in young volcanic rocks (Ben et al., 2022a; Ben et al., 2022b). Analysis of magnetic data can offer models that indicate concealed paleo-permeability structures (that is, ancient geologic structures that have influenced the permeability of subsurface formations relating to the geological past) and the magnitude of hydrothermally demagnetized rocks (Ejiga et al., 2022). These paleo-permeable structures, such as fault zones, karst systems, fractures, joints, and shear zones, play a vital role in subsurface fluid migration and resource distribution (Johnson et al., 2016; Smith et al., 2018), as well as serve as weak zones for igneous intrusions (Alfaifi et al., 2023). To ensure that large and small geothermal anomalies are properly mapped, the magnetic data (Figure 2) of the investigated area were divided into 266 spectral blocks with a 50% overlap of each block. The power–spectrum plot was generated for each block, and the associated parameters like Zc, Zot, Zb, GG, and HF were obtained (Table 1), which were then gridded.

TABLE 1

TABLE 1. Geothermal parameters obtained from magnetic data.

Table 1 shows that the result of the centroid depth (Zc) varies from 4.99–9.35 km, with an average value of 6.49 km, whereas the top depth (Zot) ranged from 2.31 to 6.15 km, with a mean of 4.00 km. The Zot (2.31–6.15 km), which is like the depth to the basement (Lawal and Nwankwo, 2017), lies within the range of depth solutions reported by previous studies in the LBT (Ekwok et al., 2021b; Ekwok et al., 2021c). The CPD (or Zb) of the investigated area ranged from 6.0 to 15.28 km, and mean values were 8.96 km. The gridded results (Figure 3) indicate low CPD dominance (red) in the central area with a somewhat E–W trend. The geothermal gradient result (Table 1) varied from 35.63°C to 94.93°C/km, and the mean was 67.17°C/km. Furthermore, heat flow varied from 89.09–237.32 mW/m² with a mean of 168.94 mW/m². Semioval structures in the central part of the investigated area (Figure 4; Figure 5) reveal a region of high geothermal gradient and heat flow. In general, it was stated by previous research that CPD and other associated parameters rely on geological events (Lawal and Nwankwo, 2017; Ejiga et al., 2022).

FIGURE 3

FIGURE 3. Curie point depth map.

FIGURE 4

FIGURE 4. Geothermal gradient map.

FIGURE 5

FIGURE 5. Heat flow map.

5 Discussion

Potential field methods are effective procedures in mapping geothermal reservoirs (Nishijimaa and Naritomi, 2017; Abdelrahman et al., 2023; Ekwok et al., 2023) and related geothermal systems (Represas et al., 2013). One of the great advantages of the spectral analysis technique is that it does not require the average interface depth, magnetization vector, and low-pass filter compared with the magnetic inversion (Hang et al., 2019; Pham et al., 2019; Pham et al., 2020). The range of the CPD (6.11–16.28 km) obtained from the investigated area was detected to be lower than the CPD range (9–20 km) stated by Abraham et al. (2019). The GG result of 35.63°C–94.93°C/km observed in this study area is somewhat higher than the previous result (29.0°C–45.8°C/km) of the area (Onuoha and Ekine, 1999; Abraham et al., 2019). The shallow CPD region (Figure 3), which has somewhat E–W orientation, divides the investigated area into sections. The northwestern and northeastern flanks match with the Anambra Basin and Ogoja Syncline (Ekwok et al., 2022a), respectively, whereas the southern part correlates with the Afikpo Syncline. These regions are depocenters (Abraham et al., 2019) characterized by some pockets of relatively low GG and HF (Figure 4; Figure 5). Furthermore, the observed HF values (89.07–237.32 mW/m²) are considerably higher than the results obtained by Abraham et al. (2019) and Onuoha and Ekine (1999). Abraham et al. (2015) and Sharma (2004) reported that areas with HF values >80 mW/m² reveal a geothermal anomaly in the subsurface. The mapped semioval structure (Figure 4; Figure 5), which coincides with shallow CPD, corresponds to the high-HF (>195 mW/m²) and -GG (>80°C/km) region (red color). It shows the prolific nature of the geothermal resources (Abraham et al., 2019) of the investigated area triggered by Santonian intrusions associated with the Santonian AA (Ekwok et al., 2020b; Ekwok et al., 2021a; Ekwok et al., 2021b; Ekwok et al., 2022a). The 3D evaluations of CPD, GG, and HF (Figure 6) show spike regions dominated by high geothermal potentials. The shallow CPD zones (< 8 km) characterized by spikes (Figure 6A) coincide fairly well with the positions of high-GG (Figure 6B) and -HF regions (Figure 6C). According to Bansal et al. (2011), potential geothermal areas are dominated by high-temperature gradient, high HF, and shallow CPD. Additionally, the igneous-related hydrothermal fluids of the area are believed to be the main source of brine fields (Ekwok et al., 2022b; 2021c; 2020a; 2019) and lead–zinc mineralization of the LBT (Farrington, 1952; Akpan et al., 2014; Ekwok et al., 2022a).

FIGURE 6

FIGURE 6. (A) 3D Curie point depth, (B) geothermal gradient, and (C) heat flow models obtained from magnetic and gravity data, respectively.

Further investigations in the delineated high geothermal zone involving bottom-hole temperature (BHT), seismic, transient electromagnetic (TEM), or magnetotelluric methods should be carried out.

6 Conclusion

Magnetic data involving spectral depth analysis procedures were analyzed to delineate the geothermal resources of the Abakaliki Anticlinorium and surrounding zones. The centroid depth, top depth, Curie point depth, geothermal gradient, and heat flow values varied from 4.99 to 9.35 km, 2.31 to 6.15 km, 6.11 to 16.28 km, 35.63°C to 94.93°C/km, and 89.07 to 237.32 mW/m², respectively. The delineated geothermal anomalous zone (Figures 3–6) dominated by a semioval shape reveals the position of shallow-CPD (< 8.5 km), high-HF (>191 mW/m²), and high-GG (>74°C/km) areas. The CPD values are slightly lower, while GG and HF values are relatively higher than those in previous studies carried out in the Benue Trough. However, the top depth result matches very well with previous depth solutions of the studied area. On the whole, the shallow CPD zone is bordered by low geothermal areas of the Anambra Basin, Ogoja Syncline, and Afikpo Syncline in the northwest, northeast, and southern portions, respectively, of the investigated area.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding authors.

Author contributions

AE contributed to writing, scientific development, result interpretation, and review. SE contributed to writing, result interpretation, and data curation and performed the computations. UB contributed to writing and figure preparation and performed the computations. CU contributed to writing and scientific development. KA, DG-O, AA, and AG reviewed, provided critical feedback, and helped shape the research. LP contributed to scientific development, reviewed, provided critical feedback, and helped shape the research. All authors contributed to the article and approved the submitted version.

Acknowledgments

Deep thanks and gratitude to the Researchers Supporting Project number (RSP2023R351), King Saud University, Riyadh, Saudi Arabia for funding this research article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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