AUTHOR=Ben Ubong C. , Ekwok Stephen E. , Akpan Anthony E. , Mbonu Charles C. , Eldosouky Ahmed M. , Abdelrahman Kamal , Gómez-Ortiz David 

TITLE=Interpretation of Magnetic Anomalies by Simple Geometrical Structures Using the Manta-Ray Foraging Optimization

JOURNAL=Frontiers in Earth Science

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2022.849079

DOI=10.3389/feart.2022.849079

ISSN=2296-6463

ABSTRACT=In this paper, a geophysical strategy based on the recently proposed Manta-Ray Foraging (MRF) Optimization algorithm is adapted and presented for the blind computation of depth/shape defining parameters from magnetic anomalies due to buried geo-bodies. The model parameters deciphered are the coefficient of amplitude (K), the buried structure’s origin (x0), the depth (z), magnetization angle (α), and a shape factor (q). The method draws its merits from the three bio-inspired foraging strategies: cyclone, chain and saumasault which allow for deeper and more general search as well as improved quality of resolved parameters. After detailed and piecewise design, thee new inversion tool is originally trial-tested on anomaly data generated synthetically. The uncorrupted version of the test data is first analyzed, then - it is corrupted with noise varied at 5, 10, 15, and 20% corruption levels. Thereafter, it is experimented with magnetic profiles taken from exploration fields in the USA, Peru, and Egypt. From the evaluation of results obtained, the new procedure is observed as exhibiting outstanding stability and flexibility especially with noisy dataset and notable efficiency in the quantitative resolution of magnetic inversion problems. The results obtained for the field cases are also very consistent especially when compared with background results from similar studies conducted with other methods; further affirming the new tool as reliable for the geophysical investigation of buried minerals. The new method has also exhibited notable superiorities over other well-known and conventional techniques especially on the grounds of convergence rate, cost, and quality of the model parameters resolved.