Magnetic inversion modeling of subsurface geologic structures for mineral deposits mapping in southeastern Nigeria

Year 2024, , 85 - 105, 26.04.2024

Ema Abraham , Ayatu Usman Kelvin Chıma George-best Azuoko Iheanyi Ikeazota

https://doi.org/10.19111/bulletinofmre.1267876

Cited By: 3

Abstract

Magnetic inversion techniques have been implemented to infer the extension and geometry of magnetic structures and also evaluate its influence on mineralization within Abakaliki and its environs, southeastern Nigeria. The modeling approach considers the techniques of threedimensional (3D) magnetic data inversion, Euler deconvolution, analytic signal inversion, Enhanced Local Wavenumber (ELW) Technique and Particle Swarm Optimization (PSO) to estimate source parameters and compare results. Model solutions were interpreted to represent possible geologic
units with varying trends, housing mineralization within the study region. Results from inversion computation over some active mine locations show subsurface bodies with magnetic susceptibilities
>0.00188 SI. Model results also show structural sources with almost 5.5 km depth extension, stretching 18 km in the EW direction at Ngbo – Ekerigwe location. This could imply significant mineral deposits at the location. Inversion of both magnetic anomaly and analytical signal enabled derivation of the actual subsurface structures in the region, with most of the structures appearing as dykes with depths ranging from 0.2 – 1.8 km at most of the mining sites. Location and depths of some of the modeled intrusions have been corroborated with the active on-site mines. The delineation of mineralization structures by this study would guide systematic exploration in the region.

Keywords

Magnetic modeling, Aeromagnetic data, Particle Swarm Optimization (PSO), Minerals, Depths

Ethical Statement

We are grateful to the anonymous reviewers, including the editor, whose comments contributed to improve this manuscript. We also acknowledge Dr. Ben Earl Barrowes of Engineer Research and Development Center – U.S. Army for his advice on the programs. Dr. Harish Garg of Thapar Institute of Engineering and Technology, Patiala, School of Mathematics, is also recognized for his advice on the PSO program. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.We would like to declare that total compliance with ethical standards was observed in the preparation of this manuscript and the submitted manuscript posses no conflict of interest between the authors and any other party.

Thanks

We are grateful to the anonymous reviewers, including the editor, whose comments contributed to improve this manuscript. We also acknowledge Dr. Ben Earl Barrowes of Engineer Research and Development Center – U.S. Army for his advice on the programs. Dr. Harish Garg of Thapar Institute of Engineering and Technology, Patiala, School of Mathematics, is also recognized for his advice on the PSO program. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.We would like to declare that total compliance with ethical standards was observed in the preparation of this manuscript and the submitted manuscript posses no conflict of interest between the authors and any other party.

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