25 Apr 2023
 | 25 Apr 2023
Status: this preprint is currently under review for the journal NPG.

The joint application of metaheuristic algorithm and Bayesian Statistics approach for uncertainty and stability assessment of nonlinear Magnetotelluric data

Mukesh Mukesh, Kuldeep Sarkar, and Upendra K. Singh

Abstract. In this paper, we have developed the Matlab code for a weighted hybrid of particle swarm optimization (PSO) and gravitational search algorithm (GSA) known as wPSOGSA, GSA, and PSO algorithms to interpret one-dimensional magnetotelluric (MT) data for some corrupted and non-corrupted synthetic data, as well as two examples of MT field data over different geological terrains: (i) geothermal rich area, Island of Milos, Greece, and (ii) Southern Scotland due to the occurrence of a significantly high electrical conductivity anomaly under crust and upper mantle extending from the Midland Valley across the Southern Uplands into northern England. Even though the fact that many models provide a good fit in a large predefined search space, specific models do not fit well. As a result, we used a Bayesian statistical technique to construct and assess the posterior probability density function (PDF) rather than picking the global model based on the lowest misfit error. This is proceeded by 68.27 % confidence interval for selecting a region where PDF is more prevalent to estimate the mean model which is more accurate and close to the true model. For illustration, correlation matrices show a significant relationship among layer parameters. The findings indicate, the wPSOGSA is less sensitive to model parameters and produces well, more stable and reliable results with the least uncertainty in the model that is compatible with existing borehole samples. Furthermore, the present methods resolve two additional geologically significant layers, one highly conductive (less than 1.0 Ωm) and another resistive (300.0 Ωm) over the Island of Milos, Greece, characterized by alluvium and volcanic deposits, respectively, as corroborated by borehole stratigraphy.

Mukesh Mukesh et al.

Status: open (until 30 Jun 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on npg-2023-8', Anonymous Referee #1, 12 May 2023 reply
    • AC1: 'Reply on RC1', Mukesh Mukesh, 12 May 2023 reply

Mukesh Mukesh et al.

Mukesh Mukesh et al.


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Short summary
The wPSOGSA algorithm is compared with PSO and GSA in evaluating 1D resistivity models from MT data. MT data from various geological terrains are used to signify the relevance of these methods, generating a large number of models that fit the apparent resistivity and phase curves. The best-fitting models were then chosen for statistical analysis, including posterior PDF, correlation matrix, and stability analysis, to enhance the accuracy and efficacy of the mean model with the least uncertainty