We discuss through synthetic and real data some the application of PSO in electromagnetic soundings. The suggested approach can be easily adapted to resistivity soundings (RS), time domain soundings (TDEM) , magneto-telluric (MT) and audio-magneto-telluric survey (AMT). We propose an overview on the PSO for solving 1D problems with a priori information and/or lateral constraints. The application of PSO on AMT data is suggested by the high speed of convergence to a problem’s solution respect other evolutionary methods. Application on the synthetic dataset allow us to analyze the relevance of the setting parameters, and to select the optimal solutions when a priori information or additional constraints are introduced. We demonstrate how PSO could be an effective approach in AMT data processing (1D). The results can be selected as starting model for a subsequent gradient-based inversion.


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