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All Journal Asian Journal of Science, Technology, Engineering, and Art
Charles, Ogunkoya Olubunmi
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Arts Computer Science & IT Engineering Social Sciences

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Advances in Magnetic Gradiometry for Aeromagnetic Surveys: Principles, Applications, and Future Directions – A Comprehensive Review Charles, Ogunkoya Olubunmi
Asian Journal of Science, Technology, Engineering, and Art Vol 3 No 3 (2025): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v3i3.5603

Abstract

Magnetic gradiometry has revolutionized aeromagnetic surveys, offering high-resolution mapping of subsurface structures and mineral deposits. This review explores the principles, instrumentation, data processing methods, and applications of the technique in geophysical exploration. Recent advancements in sensor technology, particularly the development of superconducting quantum interference devices (SQUIDs), have facilitated the implementation of full tensor magnetic gradiometry (FTMG), enabling higher-resolution subsurface characterization. The integration of these systems with unmanned aerial vehicles (UAVs) has significantly enhanced survey adaptability and spatial coverage. Furthermore, advanced data processing methodologies, such as multifractal singular value decomposition (MSVD) and optimized empirical mode decomposition (EMD) techniques, have substantially improved noise suppression and anomaly detection capabilities in geophysical datasets. Novel edge detection filters and 3D inversion algorithms have improved interpretation capabilities. Magnetic gradiometry has found applications in mineral exploration, hydrocarbon detection, geological mapping, and archaeological investigations. Its integration with other geophysical methods has proven effective for comprehensive subsurface characterization. While challenges persist in noise reduction and interpretation ambiguities, ongoing research in sensor technology, data processing, and integration with artificial intelligence promises to expand the capabilities of this powerful geophysical exploration technique.
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