Subsurface Characterization Based on Densities, Heat Sources and Thickness of Sediments Obtained From Inverse Modelling of Gravity Data

International Journal of Geoinformatics and Geological Science

© 2021 by SSRG - IJGGS Journal

Volume 8 Issue 2

Year of Publication : 2021

Authors : Anyadiegwu F. C, Aigbogun C. O, and Eze, M. O

10.14445/23939206/IJGGS-V8I2P106

How to Cite?

Anyadiegwu F. C, Aigbogun C. O, and Eze, M. O, "Subsurface Characterization Based on Densities, Heat Sources and Thickness of Sediments Obtained From Inverse Modelling of Gravity Data," SSRG International Journal of Geoinformatics and Geological Science, vol. 8,  no. 2, pp. 53-66, 2021. Crossref, https://doi.org/10.14445/23939206/IJGGS-V8I2P106

Abstract:

The gravity data over the Nsukka area, Igumale area, Ejekwe area, Udi area, Nkalagu area, and Abakaliki, was obtained from Nigerian Geological Survey Agency, NGSA. These sheets covered areas within latitude 6˚00΄N to 7˚00΄N and longitude 7˚00΄E to 8˚30΄E. The data were merged and modeled using Glabox and Bloxer software. The Gravity model result of the study area revealed thick sedimentation, in areas with a thickness of 8 Km, sedimentation uncovered in the region is likely a shale interspersed with sandstone with a medium density range of 2.30 - 2.75 g/cm3. In the areas with sedimentary thickness range of 10 Km to 15 Km, existing rocks are changed into rocks with a high density of 2.92 - 3.12 g/cm3, where the possibility of rocks uncovered is granite rocks that become reservoir cover rocks. Reservoirs revealed are, 2 large reservoirs located in the west and east with a high density of about 3.47 - 3.65 g/cm3 are interpreted as heat sources in the study area. Based on these results, the study area has high heat reservoir potential, which can be harnessed as geothermal energy. There is also a possibility of high temperature and pressure hydrocarbon reservoir potential due to areas interpreted as heat sources and density, which suggested shale intercalation.

Keywords:

Gravity Data, Densities

References:

[1] Encarta., Microsoft Encarta Student (2008). World Atlas.
[2] Fullagar PK, Pears GA, and McMonnies B (2008). Constrained inversion of geologic surfaces—pushing the boundaries. Lead Edge. 1:98–105.
[3] Hongzhu Cai, Bin Xiong, and Yue Zhu., 3D Modeling and Inversion of Gravity Data in Exploration Scale, Gravity - Geoscience Applications, Industrial Technology, and Quantum Aspect, Taher Zouaghi, IntechOpen, DOI: 10.5772/intechopen.70961., (2017).
[4] Pirttijärvi, M., GRABLOX 1.6, Gravity interpretation and modeling software based on a 3-D block model, User's guide to version 1.6, University of Oulu, Department of Physics, 60., (2008).
[5] Pirttijärvi, M., GRABLOX2, Gravity interpretation and modeling software based on a 3-D block model, User's guide to version 2.0, University of Oulu, Department of Physics, 62 (2009).
[6] Pirttijärvi, M., BLOXER, Gravity interpretation and modeling software based on a 3-D block models, User's guide to version 1.6, University of Oulu, Department of Physics, 54(2012).
[7] Witter, J.B., Siler, D.L., Faulds, J.E. and Hinz, N. H., 3D geophysical inversion modeling of gravity data to test the 3D geologic model of the Bradys geothermal area, Nevada, USA. Geothermal Energy 4: 14., (2016).