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Comparison of Very Fast Simulated Annealing and Modified Particle Swarm Optimizaton Inversion Method for 1-D TDEM Data Modelling
Prabawa R.S.a, Warsaa
a Department of Geophysical Engineering, Faculty of Mining and Petroleum Engineering, Institut Teknologi Bandung, Bandung, 40132, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2019 IOP Publishing Ltd. All rights reserved.Time domain electromagnetic method (TDEM) is a geophysical method that can be applied to a wide range of problem. TDEM data requires non-linear inversion in its modelling because of the complex relationship between data and model. A global approach is an approach in nonlinear inversion calculation which is not sensitive to the initial model and capable of obtaining global minimums. Previous studies proved that one type of inversion method will not give the most satisfactory results for all different types of inversion problems. For this reason, this study was conducted to discuss the performance of global non-linear inversion methods for 1D TDEM data modelling so that future inversion process can be carried out more optimally. In this study, the performance of VFSA and MPSO inversion method in the modelling of synthetic and field 1D TDEM data is compared. The inversion modelling is done multiple times in order to consider the random factor present in both methods and also to compare the result’s variability of each method. From the result of synthetic data inversion, it can be seen that there is a variation of inversion performance between models which is caused by the ambiguity in 1D TDEM. Based on the comparison of the two methods, MPSO performs better in inversion of data with lower level of ambiguity, and vice versa. Overall, it is concluded that the VFSA method performs better than MPSO because it has lower variability and gives better inversion results for data with high ambiguity which is usually the case for real 1D TDEM data.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Complex relationships,Fast simulated annealing,Geophysical methods,Global approaches,Inversion methods,Inversion problems,Non linear inversion,Time domain electromagnetic methods[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1088/1755-1315/318/1/012045[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]