Articles | Volume 30, issue 4
Research article
10 Oct 2023
Research article |  | 10 Oct 2023

The joint application of a metaheuristic algorithm and a Bayesian statistics approach for uncertainty and stability assessment of nonlinear magnetotelluric data

Mukesh, Kuldeep Sarkar, and Upendra K. Singh

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Inversion, Assessment of Stability and Uncertainty of Geoelectric Sounding data using a New Hybrid Meta-heuristic algorithm and Posterior Probability Density Function Approach
Kuldeep Sarkar and Upendra K. Singh
Nonlin. Processes Geophys. Discuss.,,, 2022
Revised manuscript accepted for NPG
Short summary

Cited articles

Ai, H., Essa, K. S., Ekinci, Y. L., Balkaya, Ç., Li, H., and Géraud, Y.: Magnetic anomaly inversion through the novel barnacles mating optimization algorithm, Sci. Rep., 12, 22578,, 2022. 
Cagniard, L.: Basic theory of the magneto-telluric method of geophysical prospecting, Geophysics, 18, 605—635,, 1953. 
Colorni, A., Dorigo, M., and Maniezzo, V.: Distributed Optimization by Ant Colonies, Proceedings of the First European Conference on Artificial Life, Paris, France, 134–142 pp., 1991. 
Constable, S. C., Parker, R. L., and Constable, C. G.: Occam's inversion: A practical algorithm for generating smooth models from electromagnetic sounding data, Geophysics, 52, 289–300,, 1987. 
Dawes, G. J. K.: Magnetotelluric feasibility study: Island of Milos, Greece, Luxembourg, Edinburgh Univ. (UK). Dept. of Geophysics, Luxembourg, Report Number EUR-10674, Reference Number: ERA-13-007410, EDB-88-008365, 1986. 
Short summary
A hybrid weighted particle swarm optimization (wPSO) and gravitational search algorithm (GSA) is compared with individual PSO and GSA methods to assess 1-D resistivity models from magnetotelluric data across diverse geological terrains. This involved creating numerous models to match apparent resistivity and phase curves, selecting the best-fit models, and conducting posterior PDF, correlation matrix, and stability analysis to improve the mean model's accuracy with minimized uncertainty.