The joint application of a metaheuristic algorithm and a Bayesian statistics approach for uncertainty and stability assessment of nonlinear magnetotelluric data
<p>In this paper, we have developed three algorithms, namely hybrid weighted particle swarm optimization (wPSO) with the gravitational search algorithm (GSA), known as wPSOGSA; GSA; and PSO in MATLAB to interpret one-dimensional magnetotelluric (MT) data for some corrupted and non-corrupted sy...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-10-01
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| Series: | Nonlinear Processes in Geophysics |
| Online Access: | https://npg.copernicus.org/articles/30/435/2023/npg-30-435-2023.pdf |
| _version_ | 1797662818338603008 |
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| author | Mukesh K. Sarkar U. K. Singh |
| author_facet | Mukesh K. Sarkar U. K. Singh |
| author_sort | Mukesh |
| collection | DOAJ |
| description | <p>In this paper, we have developed three algorithms, namely hybrid weighted
particle swarm optimization (wPSO) with the gravitational search algorithm (GSA),
known as wPSOGSA; GSA; and PSO in MATLAB 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) geothermally 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.
The study proceeds using a 68.27 % confidence interval for selecting a region
where the 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 that wPSOGSA is less sensitive to model parameters and produces
more stable and reliable results with the least uncertainty in the
model, compatible with existing borehole samples. Furthermore, the
present methods resolve two additional geologically significant layers, one
highly conductive (less than 1.0 <span class="inline-formula">Ωm</span>) and another resistive (300.0 <span class="inline-formula">Ωm</span>), over the island of Milos, Greece, characterized by alluvium and
volcanic deposits, respectively, as corroborated by borehole stratigraphy.</p> |
| first_indexed | 2024-03-11T19:04:37Z |
| format | Article |
| id | doaj.art-a9ed257f244b4ad990da51173da13be8 |
| institution | Directory Open Access Journal |
| issn | 1023-5809 1607-7946 |
| language | English |
| last_indexed | 2024-03-11T19:04:37Z |
| publishDate | 2023-10-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Nonlinear Processes in Geophysics |
| spelling | doaj.art-a9ed257f244b4ad990da51173da13be82023-10-10T09:23:22ZengCopernicus PublicationsNonlinear Processes in Geophysics1023-58091607-79462023-10-013043545610.5194/npg-30-435-2023The joint application of a metaheuristic algorithm and a Bayesian statistics approach for uncertainty and stability assessment of nonlinear magnetotelluric dataMukeshK. SarkarU. K. Singh<p>In this paper, we have developed three algorithms, namely hybrid weighted particle swarm optimization (wPSO) with the gravitational search algorithm (GSA), known as wPSOGSA; GSA; and PSO in MATLAB 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) geothermally 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. The study proceeds using a 68.27 % confidence interval for selecting a region where the 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 that wPSOGSA is less sensitive to model parameters and produces more stable and reliable results with the least uncertainty in the model, compatible with existing borehole samples. Furthermore, the present methods resolve two additional geologically significant layers, one highly conductive (less than 1.0 <span class="inline-formula">Ωm</span>) and another resistive (300.0 <span class="inline-formula">Ωm</span>), over the island of Milos, Greece, characterized by alluvium and volcanic deposits, respectively, as corroborated by borehole stratigraphy.</p>https://npg.copernicus.org/articles/30/435/2023/npg-30-435-2023.pdf |
| spellingShingle | Mukesh K. Sarkar U. K. Singh The joint application of a metaheuristic algorithm and a Bayesian statistics approach for uncertainty and stability assessment of nonlinear magnetotelluric data Nonlinear Processes in Geophysics |
| title | The joint application of a metaheuristic algorithm and a Bayesian statistics approach for uncertainty and stability assessment of nonlinear magnetotelluric data |
| title_full | The joint application of a metaheuristic algorithm and a Bayesian statistics approach for uncertainty and stability assessment of nonlinear magnetotelluric data |
| title_fullStr | The joint application of a metaheuristic algorithm and a Bayesian statistics approach for uncertainty and stability assessment of nonlinear magnetotelluric data |
| title_full_unstemmed | The joint application of a metaheuristic algorithm and a Bayesian statistics approach for uncertainty and stability assessment of nonlinear magnetotelluric data |
| title_short | The joint application of a metaheuristic algorithm and a Bayesian statistics approach for uncertainty and stability assessment of nonlinear magnetotelluric data |
| title_sort | joint application of a metaheuristic algorithm and a bayesian statistics approach for uncertainty and stability assessment of nonlinear magnetotelluric data |
| url | https://npg.copernicus.org/articles/30/435/2023/npg-30-435-2023.pdf |
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