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Structural and geophysical constraint mapping for hydrocarbon resources within parts of the Bida Basin, Central Nigeria

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Abstract

Remote sensing (RS) and geographic information systems (GIS) play an important role in the exploration of geological resources and are most effective when used during reconnaissance scale surveys. In Nigerian frontier basins, the use of GIS-based spatial predictive mapping and regional scale evaluation of geological structures is regarded as the best tools for downscaling exploration targets. The Fry analysis and distance correlation analysis were used to infer structural control over hydrocarbon resources, whereas the prediction area plot analysis assessed the spatial relationship between the evidential and target data. A hydrocarbon prospectivity map for the Bida Basin was generated using a multi-criteria weighted sum model, and the hydrocarbon predictive model was discretized and classified using a multi-fractal analytical approach. ROC/AUC analysis was used to evaluate and assess the reliability of the hydrocarbon predictive model. According to evidence from Fry and distance correlation analysis, hydrocarbon manifestations is primarily controlled by the WNW-ESE tectonic trend. Based on the prediction area plot analysis, there is a significant correlation between hydrocarbon occurrences and spatial data on magnetic (0.67), gravity (0.68), and distances to the WNW-ESE lineaments (0.81). The weighted sum model was used to integrate spatial data, which revealed significant potential for hydrocarbon resources in the study location’s south-central and north-eastern regions. The hydrocarbon predictive model was discretized into four classes (very low, low, high and very high) using multi-fractal analysis, with percentile extents of 25.88%, 42.43%, 21.46%, and 10.23%, respectively. The ROC/AUC revealed an accuracy level of more than 80%. The reliable identification of exploration targets, demonstrated by a high level of accuracy, suggests that this approach could be ideal for supplementing exploration expeditions in the Bida basins and other sedimentary basins throughout Nigeria.

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References

  • Adejato KO, Adeyeri OE, Salubi O (2018) Use of remote sensing and geographic information system in accessing the spatial distribution of bitumen in Dahomey SubBasin, Southwestern Nigeria IOSR J. Appl. Geol. Geophys. (IOSR-JAGG) 6(1):20-31 https://doi.org/10.9790/0990-0601022031

  • Adeleye DR (1974) Sedimentology of the fluvial Bida Basin (Cretaceous). Nigeria Sedim Geol 12:1–24. https://doi.org/10.1016/0037-0738(74)90013-X

    Article  Google Scholar 

  • Aderoju AB, Ojo SB, Adepelumi AA, Edino F (2016) A reassessment of hydrocarbon prospectivity of the Chad basin, Nigeria, using magnetic hydrocarbon indicators from high-resolution aeromagnetic Ife. J. Sci. 18(2):503–520

    Google Scholar 

  • Afshari A, Mojahed M, Yusuff RM (2010) Simple additive weighting approach to personnel selection problem Int. J. Innov. Manag. Technol. 1(5):511–515

    Google Scholar 

  • Afshari AR, Nikolić M, Akbari Z (2017) Personnel selection using group fuzzy AHP and SAW methods. J. Eng. Manag. Compet. 7(1):3–10

    Google Scholar 

  • Aigbadon GO, Odoma AN, Obasi IA, Christopher SD, Nanfa CA, MaB Aminu, Akakuru OC (2022) Hydrocarbon prospectivity of the southern Bida and northern Anambra basins, Nigeria using palynological and geochemical studies Geosys. Geoenv. 1(4):1–11. https://doi.org/10.1016/j.geogeo.2022.100103

    Article  Google Scholar 

  • Ajama OD, Hammed OS, Falade SC, Arogundade AB, Olasui OM, Olayode FA, Olurin OT, Awoyemi MO (2017) Hydrocarbon potentiality of Bida basin from high resolution aeromagnetic data Pet. Coal 59(6):991–1007

    Google Scholar 

  • Akinsete OO, Abdulraheem TY, Naheem SB, Leke AS (2020) Integration and Interpretation of Aeromagnetic, 3D Seismic and Well Logs Data in Hydrocarbon Exploration in Niger Delta Basin Adv. Res. 21(18):28–42. https://doi.org/10.9734/air/2020/v21i830224

    Article  Google Scholar 

  • Akinwumiju AS, Olorunfemi MO, Afolabi O (2016) Automated lineament mapping from remotely sensed data: case study Osun drainage basin. Southwestern Nigeria Ife J. Sci. 8(1):177–201

    Google Scholar 

  • Aldana M, Costanzo-Alvarez V, Díaz M (2003) Magnetic and mineralogical studies to characterize oil reservoirs in Venezuela. lead. edge 22(6):526-529 https://doi.org/10.1190/1.1587674

  • Amiri MA, Karimi M, Sarab AA (2014) Hydrocarbon resources potential mapping using the evidential belief functions and GIS, Ahvaz/Khuzestan Province, southwest Iran Arab J Geoscihttps://doi.org/10.1007/s12517-014-1494-8

  • Amiri MA, Karimi M, Sarab AA (2015) Hydrocarbon resources potential mapping using evidential belief functions and frequency ratio approaches, southeastern Saskatchewan. Canada Can. J. Earth Sci. 52(3):1–14. https://doi.org/10.1139/cjes-2013-0193

    Article  Google Scholar 

  • Andongma WT, Gajere JN, Amuda AK, Digne Edmond RR, Faisal M, Yusuf YD (2020) Mapping of hydrothermal alterations related to gold mineralization within parts of the Malumfashi Schist Belt, North-Western Nigeria Egypt. J Remote Sens Space Sci 24(3):401–417. https://doi.org/10.1016/j.ejrs.2020.11.001

    Article  Google Scholar 

  • Annette JR, Banu A, Chandran PS (2016) Comparison of multi criteria decision making algorithms for ranking Cloud Renderfarm services Indian J. Sci. Technol. 9(31):3-5 https://doi.org/10.48550/arXiv.1611.10204

  • Aramesh AR, Afzal P, Adib A, Bijan Y, Amir, (2014) Application of multifractal modeling for the identification of alteration zones and major faults based on ETM+ multispectral data Arab. J. Geosci. 8:2997–3006. https://doi.org/10.1007/s12517-014-1366-2

    Article  Google Scholar 

  • Asadi HH, Kianpouryan S, Lu Y-J, McCuaig TC (2014) Exploratory data analysis and C-A fractal model applied in mapping multi-element soil anomalies for drilling: a case study from the Sari Gunay epithermal gold deposit, NW Iran. J. Geochem. Explor. 145:233–241. https://doi.org/10.1016/j.gexplo.2014.07.005

    Article  Google Scholar 

  • Atmaja RRS, Putra DPE, Setijadji LD (2019) Delineation of groundwater potential zones using remote sensing, GIS, and AHP techniques in southern region of Banjarnegara, Central Java, Indonesia Sixth Geoinf Sci Symp 11311https://doi.org/10.1117/12.2548473

  • Auduson AE, Onuoha KM (2020) Cretaceous Bida and Sokoto basins of Nigeria: deducing basin architecture and basement topography from aeromagnetic data analyses Int. J. Earth Sci. Geophys. 6(2):1-21 https://doi.org/10.35840/2631-5033/1843

  • Awoyemi MO, Ajama OD, Hammed OS, Arogundade AB, Falade SC (2017) Geophysical mapping of buried faults in parts of Bida Basin. North Central Nigeria Geophys Prospect 66(S1):40–54. https://doi.org/10.1111/1365-2478.12575

    Article  Google Scholar 

  • Awoyemi MO, Hammed OS, Falade SC, Arogundade AB, Ajama OD, Iwalehin PO, Olurin OT (2017) Geophysical investigation of the possible extension of Ifewara fault zone beyond Ilesa area, southwestern Nigeria Arab. J. Geosci. 10(2):1–14. https://doi.org/10.1007/s12517-016-2813-z

    Article  Google Scholar 

  • Aziz M, Saibi H (2014) Integrating gravity data with remotely sensed data for structural investigation of the Aynak-Logar Valley, Eastern Afghanistan, and the surrounding area IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(2):816 - 824 https://doi.org/10.1109/JSTARS.2014.2347375

  • Bahrami Y, Hassani H, Maghsoudi A (2022) Spatial modeling for mineral prospectivity using BWM and COPRAS as a new HMCDM method Arab. J. Geosci. 15(5) https://doi.org/10.1007/s12517-022-09630-1

  • Bassey NE, Barka J, Musa H (2017) Hydrocarbon prospect of Nigeria’s Gongola Basin based on gravity data interpretation IOSR. J. Appl. Geol. Geophys. 05(02):68–77. https://doi.org/10.9790/0990-0502016877

    Article  Google Scholar 

  • Bingham L, Zurita-Milla R, Escalona A (2012) Geographic information system–based fuzzy-logic analysis for petroleum exploration with a case study of northern South America Geographic Information System and Fuzzy-Logic Petroleum Exploration AAPG Bull. 96(11):2121-2142 https://doi.org/10.1306/04251212009

  • Braide SP (1990) Petroleum geology of the Southern Bida Basin, Nigeria AAPG Bulletin 74(5)

  • Burton EA, Machel HG, Qi J (1993) Thermodynamic constrain on anomalous magnetization in shallow and deep hydrocarbon seepage environments. SEPM Soc. Sediment. Geol. 49(15) https://doi.org/10.2110/pec.93.49.0193

  • Carranza EJM (2009) Controls on mineral deposit occurrence inferred from analysis of their spatial pattern and spatial association with geological features. Ore Geol. Rev. 35(3–4):383–400. https://doi.org/10.1016/j.oregeorev.2009.01.001

    Article  Google Scholar 

  • Carranza EJM, Wibowo H, Barritt SD, Sumintadireja P (2008) Spatial data analysis and integration for regional-scale geothermal potential mapping West Java. Indonesia Geothermics 37(3):267–299. https://doi.org/10.1016/j.geothermics.2008.03.003

    Article  Google Scholar 

  • Cheng Q, Agterberg FP, Ballantyne SB (1994) The separation of geochemical anomalies from background by fractal methods. J. Geochem. Explor. 51(2):109–130. https://doi.org/10.1016/0375-6742(94)90013-2

    Article  Google Scholar 

  • El Amine M, Pailhesa J, Perrya N (2014) Critical review of multi-criteria decision aid methods in conceptual design phases: application to the development of a solar collector structure Procedia CIRP 21:497 – 502 https://doi.org/10.1016/j.procir.2014.03.134

  • Emetere ME (2017) Thermal infrared remote sensing of hydrocarbon in Lagos- Southern Nigeria: application of the thermographic model Int. J. GEOMATE 13(39):33-45 https://doi.org/10.21660/2017.39.41553

  • Emujakporue G, Ofoha CC, Kiani I (2018) Investigation into the basement morphology and tectonic lineament using aeromagnetic anomalies of parts of Sokoto Basin, North Western Nigeria Egypt. J. Pet. 27(4):671–681. https://doi.org/10.1016/j.ejpe.2017.10.003

    Article  Google Scholar 

  • Garain S, Mitra D, Das P (2021) Mapping hydrocarbon microseepage prospect areas by integrated studies of ASTER processing, geochemistry and geophysical surveys in Assam-Arakan Fold Belt, NE India Int. J. Appl. Earth Obs. Geoinf. 102 https://doi.org/10.1016/j.jag.2021.102432

  • Genier F, Epard J-L (2007) The Fry method applied to an augen orthogneiss: problems and results. J. Struct. Geol. 29(2):209–224. https://doi.org/10.1016/j.jsg.2006.08.008

    Article  Google Scholar 

  • González DL, Rodríguez-Gonzálvez P (2019) Detection of geothermal potential zones using remote sensing techniques Remote Sens. 11(20) https://doi.org/10.3390/rs11202403

  • Gosh S, Carranza EJ (2010) Spatial analysis of mutual fault/fracture and slope control on rocksliding in Darjeeling Himalaya India. Geomorphology 122(1–2):1–24. https://doi.org/10.1016/j.geomorph.2010.05.008

    Article  Google Scholar 

  • Hamzeh M, Karimipour F (2020) Petroleum potential assessment using an optimized fuzzy outranking approach: a case study of the Red River petroleum system. Williston Basin Energy Explor. Exploit. 38(4):960–988. https://doi.org/10.1177/014459872091026

    Article  Google Scholar 

  • Hosmer D, W. Jr., Stanley L, X. SR (2013) Applied logistic regression John Wiley & Sons, Inc, 3rd Edition edn. https://doi.org/10.1002/9781118548387

  • Hung LQ, Batelaan O, De Smedt F (2005) Lineament extraction and analysis, comparison of LANDSAT ETM and ASTER imagery case study: Suoimuoi tropical karst catchment. Vietnam Proc. SPIE 5983:59830T. https://doi.org/10.1117/12.627699

    Article  Google Scholar 

  • Ike EC (1988) Late stage geological phenomena in the Late Zaria basement granite In Precambrian Geol. Niger. Publ. Geol. Surv. Niger.:329pp

  • Jones HA (1958) The oolitic ironstones of the Agbaja Plateau, Kabba Province Rec. Geol. Surv. Niger.: 20-43

  • Kamureyina E (2019) Determination of hydrocarbon potentials using high resolution aeromagnetic data over Sokoto Basin Northwestern Nigeria. Int. J. Geosci. 10(04):419–438. https://doi.org/10.4236/ijg.2019.104024

    Article  Google Scholar 

  • Kogbe CA (1983) Geological interpretation of Landsat imageries across Central Nigeria. J Afr Earth Sci 1(3–4):213–220. https://doi.org/10.1016/S0731-7247(83)80005-6

    Article  Google Scholar 

  • Kolo IA, Obaje N, Balogu DO, Sani YY, Panti H, Ibrahim SI, Musa MK, Dandi-Mumud N, Yusuf I, Idris-Nda A, Goro IA, Dantata SH (2015) Bida basin hydrocarbon research project in pictures an institutional research project of the IBBL University, through the Department of Geology and Mining in collaboration with the Niger State Gubernatorial Committee on Development of the Bida Basin:51pp

  • Likkason OK (1993) Application of trend surface analysis to gravity data over the middle Niger Basin Nigeria. J. Min. Geol. 29(2):11–19

    Google Scholar 

  • Liu L, Huang GH, Fuller GA (2001) A GIS-supported remote sensing technology for petroleum exploration and exploitation. J Can Pet Technol 40(11):9–12. https://doi.org/10.2118/01-11-TN1

    Article  Google Scholar 

  • Liu Q, Chan L, Liu Q, Li H, Wang F, Zhang S, Xia X, Cheng T (2004) Relationship between magnetic anomalies and hydrocarbon microseepage above the Jingbian gas field Ordos basin China. AAPG Bull. 88(2):241–251. https://doi.org/10.1306/09250303033

    Article  Google Scholar 

  • Mandrekar JN (2010) Receiver operating characteristic curve in diagnostic test assessment. J. Thorac. Oncol. 5(9):1315–1316. https://doi.org/10.1097/JTO.0b013e3181ec173d

    Article  Google Scholar 

  • Mbah D, Obiora DN, Oha AI, Terhemba BS, Ossai CO, Igwe EA (2017) Investigation of possible cause of gravity anomalies in parts of the Niger Delta Basin Nigeria. Int. J. Phys. Sci. 12(9):103–117. https://doi.org/10.5897/IJPS2017.4627

    Article  Google Scholar 

  • McLay K, Muggli R, Mazrui S (2003) ArcGIS in the oil and gas exploration workflow 23rd Annu. ESRI Int. User Conf. San Diego

  • Miller HG, Singh V (1994) Potential field tilt-a new concept for location of potential field sources. J. Appl. Geophys. 32(2–3):213–217. https://doi.org/10.1016/0926-9851(94)90022-1

    Article  Google Scholar 

  • Nabighian MN (1972) The analytic signal of two-dimensional magnetic bodies with polygonal cross-section; its properties and use of automated anomaly interpretation Geophysics 37(3):507-517 https://doi.org/10.1190/1.1440276

  • Nwajide CS (1990) Sedimentation and paleogeography of the Central Benue Trough, Nigeria In: Ofoegbu CO (ed) Benue trough struct. evol., Vieweg Braunschw.: pp 19–38

  • Obaje NG, Abdullahi B, Dabai MS, Ali M, Aweda A, Habu SJ, Idris-Nda A, Isah GA, Waziri S (2020) Updates on the geology and potential petroleum system of the Bida Basin in Central Nigeria Pet. Sci. Eng. 4(1):23-33 https://doi.org/10.11648/j.pse.20200401.13

  • Obaje NG, Balogu DO, Idris-Nda A, Goro IA, Ibrahim SI, Musa MK, Dantata SH, Yusuf I, Mamud-Dadi N, Kolo IA (2013) Preliminary integrated hydrocarbon prospectivity evaluation of the Bida Basin in North Central Nigeria Pet. Technol. Dev. J. 3(2):36–64

    Google Scholar 

  • Obaje NG, Idris-Nda A, Okoro AU, Akpunonu EO, Jatau SB, Goro IA, Dantata SH (2015) G&G Assessment of hydrocarbon new business opportunities in the Bida Basin of Central Nigeria Oil Gas J. 113(4):52-59

  • Obaje NG, Moumouni A, Goki NG, Chaanda MS (2011) Stratigraphy, paleogeography and hydrocarbon resource potentials of the Bida Basin in North-Central Nigeria. J. Min. Geol. 47(2):97–114

    Google Scholar 

  • Obaje NG, Wehner H, Scheeder G, Abubakar MB, Jauro A (2004) Hydrocarbon prospectivity of Nigeria’s inland basins: from the viewpoint of organic geochemistry and organic petrology AAPG Bull. 87(3):325–353https://doi.org/10.1306/10210303022

  • Ojo OJ, Akande SO (2012) Sedimentary facies relationship and depositionalenvironment of the Maastrichtian Enagi Formation, Northern Bida Basin Nigeria. J Geogr Geol 4(1):136–147. https://doi.org/10.5539/jgg.v4n1p136

    Article  Google Scholar 

  • Ojo SB (1984) Middle Niger Basin revisited: magnetic constraints on gravity interpretations. Abstract, 20th Conference of the Nigeria Mining and Geosciences Society, Nsukka, 52–53

  • Ojo SB (1990) Origin of a major aeromagnetic anomaly in the Middle Niger Basin Nigeria. Tectonophysics 185(1–2):153–162. https://doi.org/10.1016/0040-1951(90)90410-A

    Article  Google Scholar 

  • Ojo SB, Ajakaiye DE (1989) Preliminary interpretation of gravity measurements in the Mid-Niger Basin area, Nigeria. In: Kogbe, C. A. (Ed.), Geology of Nigeria, 2nd edition, Elizabethan Publishers, Lagos:347–358

  • Ouko C, Mutua F, Mwaniki M (2018) A Pre-exploration technique for mapping petroleum potential areas based on induced surface alterations and possible traps Univers. J. Geosci. 6(5):158-174 https://doi.org/10.13189/ujg.2018.060503

  • Prabaharan S, Ramalingam M, Subramani T, Lakshumanan C (2013) Remote sensing and GIS tool to detect hydrocarbon prospect in Nagapattinam Sub Basin India. Geotech. Geol. Eng. 31(1):267–277. https://doi.org/10.1007/s10706-012-9589-z

    Article  Google Scholar 

  • Putra DWT, Punggara AA (2018) Comparison analysis of simple additive weighting (SAW) and weighted product (WP) in decision support systems MATEC Web of Conferences 215, 01003 https://doi.org/10.1051/matecconf/201821501003

  • Rahaman MAO, Fadiya SL, Adekola SA, Coker SJ, Bale RB, Olawoki OA, Omada IJ, Obaje NG, Akinsanpe OT, Ojo GA, Akande WG (2019) A revised stratigraphy of the Bida Basin Nigeria. J Afr Earth Sci 151:67–81. https://doi.org/10.1016/j.jafrearsci.2018.11.016

    Article  Google Scholar 

  • Sabins FF (1998 ) Remote sensing for petroleum exploration, Part 1: overview of imaging systems The leading edge 17(4):467–470 https://doi.org/10.1190/1.1437991

  • Segal DB (1989) Successful use of Landsat thematic mapper data for mapping hydrocarbon microseepage induced mineralogic alteration, Lisbon Valley. Utah Photogramm Eng Remote Sens 55(8):1137–1145

    Google Scholar 

  • Shafieyan F, Abdideh M (2019) Application of concentration-area fractal method in static modeling of hydrocarbon reservoirs. J Pet Explor Prod Technol 9:1197–1202. https://doi.org/10.1007/s13202-018-0554-0

    Article  Google Scholar 

  • Sheng J, Sun J, Bai Y, Liu Z, Wei H, Li L, Su G, Wang Z (2020) Evaluation of hydrocarbon potential using fuzzy AHP-based grey relational analysis: a case study in the Laoshan Uplift, South Yellow Sea China. J Geophys Eng 17(1):189–202. https://doi.org/10.1093/jge/gxz107

    Article  Google Scholar 

  • Tende AW, Aminu MD, Amuda AK, Gajere JN, Usman H, Shinkafi F (2021a) A spatial reconnaissance survey for gold exploration in a schist belt Heliyon 7(11) https://doi.org/10.1016/j.heliyon.2021a.e08406

  • Tende AW, Aminu MD, Gajere JN (2021b) A spatial analysis for geothermal energy exploration using bivariate predictive modelling Sci. Rep. 11(1) https://doi.org/10.1038/s41598-021-99244-6

  • Tende AW, Mustapha T, Fru MIN, Gajere JN, Aminu MD (2022) Hybrid extraction of tectonic lineaments from digital elevation model. Appl Geomat. 14:163–180. https://doi.org/10.1007/s12518-022-00422-6

    Article  Google Scholar 

  • Vearncombe J, Vearncombe S (1999) The spatial distribution of mineralisation; applications of Fry analysis. Econ. Geol. 94(4):475–486. https://doi.org/10.2113/gsecongeo.94.4.475

    Article  Google Scholar 

  • Wang G, Pang Z, Boisvert JB, Hao Y, Cao Y, Qu J (2013) Quantitative assessment of mineral resources by combining geostatistics and fractal methods in the Tongshan porphyry Cu deposit (China). J Geochem Explor 134:85–98. https://doi.org/10.1016/j.gexplo.2013.08.004

    Article  Google Scholar 

  • Wei L, Qinyan (2010) The application of GIS technology in the petroleum exploration. Paper presented at the 2nd Conference on Environmental Science and Information Application Technology, Wuhan, China, 17-18 July 2010

  • Wormald RJ, Eckardt FD, Vearncombe JS (2003) Spatial distribution analysis of pans in Botswana: the importance of structural control S. Afr. J. Geol. 106(4):287–290. https://doi.org/10.2113/106.4.287

    Article  Google Scholar 

  • Yousefi M, Carranza EJM (2015) Fuzzification of continuous-value spatial evidence for mineral prospectivity mapping Comput. Geosci. 74:97–109. https://doi.org/10.1016/j.cageo.2014.10.014

    Article  Google Scholar 

  • Yousefi M, Carranza EJM (2016) Data-driven index overlay and Boolean logic mineral prospectivity modeling in Greenfields Exploration Nat. Resour. Res. 25(1):3–18. https://doi.org/10.1007/s11053-014-9261-9

    Article  Google Scholar 

  • Yousefi M, Carranza EJM (2017) Union score and fuzzy logic mineral prospectivity mapping using discretized and continuous spatial evidence values. J Afr Earth Sci 128:47–60. https://doi.org/10.1016/j.jafrearsci.2016.04.019

    Article  Google Scholar 

  • Zaborski PM (1996) A compilation of and a short literature review on the Cretaceous of Nigeria. Afr Geol rev 3:491–523

    Google Scholar 

  • Zaborski PM, Ugodulunwa F, Idornigie A, Nnabo P, Ibe K (1998) Stratigraphy and structures of the Cretaceous Gongola Basin, northeastern Nigeria Bull. cent. res. explor. prod. Elf-Aquitaine 21(1):153-185

  • Zhang N, Zhou K, Du X (2017) Application of fuzzy logic and fuzzy AHP to mineral prospectivity mapping of porphyry and hydrothermal vein copper deposits in the Dananhu-Tousuquan island arc, Xinjiang NW China. J Afr Earth Sci 128:84–96. https://doi.org/10.1016/j.jafrearsci.2016.12.011

    Article  Google Scholar 

  • Zou KH, O’Malley AJ, Mauri L (2007) Receiver-operating characteristic analysis for evaluating diagnostic tests and predictive models. Circulation 115(5):654–657. https://doi.org/10.1161/CIRCULATIONAHA.105.594929

    Article  Google Scholar 

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  1. Department of Geology and Mineral Sciences, University of Ilorin, Ilorin, Nigeria

    Serah Japhet Habu & Olabisi Adeleye Adekeye

  2. Department of Geology, Kano University of Science and Technology, Wudil, Nigeria

    Andongma Wanduku Tende

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Habu, S.J., Adekeye, O.A. & Tende, A.W. Structural and geophysical constraint mapping for hydrocarbon resources within parts of the Bida Basin, Central Nigeria. Arab J Geosci 15, 1760 (2022). https://doi.org/10.1007/s12517-022-11040-2

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