Articles | Volume 30, issue 4
https://doi.org/10.5194/npg-30-435-2023
https://doi.org/10.5194/npg-30-435-2023
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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Nonlin. Processes Geophys. Discuss., https://doi.org/10.5194/npg-2022-13,https://doi.org/10.5194/npg-2022-13, 2022
Revised manuscript accepted for NPG
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Cited articles

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Cagniard, L.: Basic theory of the magneto-telluric method of geophysical prospecting, Geophysics, 18, 605—635, https://doi.org/10.1190/1.1437915, 1953. 
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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, https://doi.org/10.1190/1.1442303, 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. 
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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.