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Rudarsko-geološko-naftni zbornik, Vol. 38 No. 3, 2023.

Original scientific paper

https://doi.org/10.17794/rgn.2023.3.6

HYBRID PARTICLE SWARM OPTIMIZATION AND GREY WOLF OPTIMIZER ALGORITHM FOR CONTROLLED SOURCE AUDIO-FREQUENCY MAGNETOTELLURICS (CSAMT) ONE-DIMENSIONAL INVERSION MODELLING

Wahyu Eko Junian orcid id orcid.org/0009-0000-8418-7893 ; Faculty of Mining and Petroleum Engineering, Institut Teknologi Bandung (ITB), Jalan Ganesha 10, Bandung 40132, Indonesia
Hendra Grandis orcid id orcid.org/0000-0001-5778-7711 ; Dept. of Geophysical Engineering, Institut Teknologi Sumatera (ITERA), Jalan Terusan Ryacudu, Way Hui, Lampung Selatan 35365, Indonesia

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Abstract

The Controlled Source Audio-frequency Magnetotellurics (CSAMT) is a geophysical method utilizing artificial electromagnetic signal source to estimate subsurface resistivity structures. One-dimensional (1D) inversion modelling of CSAMT data is non-linear and the solution can be estimated by using global optimization algorithms. Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO) are well-known population-based algorithms having relatively simple mathematical formulation and implementation. Hybridization of PSO and GWO algorithms (called hybrid PSO-GWO) can improve the convergence capability to the global solution. This study applied the hybrid PSO-GWO algorithm for 1D CSAMT inversion modelling. Tests were conducted with synthetic CSAMT data associated with 3-layer, 4-layer and 5-layer earth models to determine the performance of the algorithm. The results show that the hybrid PSO-GWO algorithm has a good performance in obtaining the minimum misfit compared to the original PSO and GWO algorithms. The hybrid PSO-GWO algorithm was also applied to invert CSAMT field data for gold mineralization exploration in the Cibaliung area, Banten Province, Indonesia. The algorithm was able to reconstruct the resistivity model very well which is confirmed by the results from inversion of the data using standard 2D MT inversion software. The model also agrees well with the geological information of the study area.

Keywords

CSAMT; nonlinear inversion; particle swarm optimization; grey wolf optimizer; hybrid algorithm

Hrčak ID:

307306

URI

https://hrcak.srce.hr/307306

Publication date:

14.8.2023.

Article data in other languages: croatian

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