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Thickness estimation using gradient of spectral amplitude from spectral decomposition
Sulistyoati T.W.A.a, Novitasari L.a, Winardhi S.a
a Geophysical Engineering Program, Faculty of Mining and Petroleum Engineering, Bandung Institute of Technology, China
[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]© 2011 SEG.This paper presents a novel approach for estimating thin bed thickness by using gradient of spectral amplitudes resulting from spectral decomposition. The gradient is calculated from the differences between amplitudes spectrum at two adjacent frequencies. The technique is based on the concept that seismic reflections from a thin bed have characteristic signatures in the frequency domain. Thicker beds have shorter period of spectral notches than thinner beds have. Consequently, steeper gradients of spectral amplitude representing thicker beds and lower gradients representing thinner beds. In this paper, the Discrete Fourier Transform (DFT) method is used for spectral decomposition. The application of the technique for mapping thin bed thickness distribution is presented. The gradient of spectral amplitude has been found to have better correlation to thickness than the conventional spectral amplitude to thickness.[/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]Characteristic signature,Frequency domains,Seismic reflections,Spectral amplitude,Spectral decomposition,Thickness distributions,Thickness estimation,Thin bed[/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]The authors would like to thank to the Faculty of Mining and Petroleum Engineering at the Bandung Institute of Technology for the computing facilities. Support and helps from assistants in the Seismic Laboratory at the Geophysical Engineering Program is unforgettable.[/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][/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]