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Multi-ricker spectral modeling in the s-transform domain for enhancing vertical resolution of seismic reflection data
Winardhi S.a, Pranowo W.b
a Geophysical Engineering, Faculty of Mining and Petroleum Engineering Institut Teknologi Bandung, Indonesia
b Geophysical Engineering, Faculty of Exploration and Production Technology Universitas Pertamina, Jakarta, 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]© IJOG – 2019. All right reserved.A relatively straightforward methodology is presented for extending seismic bandwidth, and hence enhancing the seismic resolution by performing time-variant deconvolution. The generalized S-transform (GST) approach is used in order to properly compute the time-frequency components of the seismic reflection trace. In estimating the time-variant wavelet, a spectral modeling method is proposed, named multi-Ricker spectral approximation (MRA). After obtaining the estimated wavelet spectrum at each time sample, a deconvolution filter can then be built and applied in the S-transform domain. This proposed time-variant seismic enhancement method needs neither information on subsurface attenuation model nor assumption that the subsurface reflectivity is random. It is a data-driven methodology which is based on the seismic data only. This proposed method is validated on a noise-free and noisy synthetics and also applied to a field data. Results show that, after enhancement, overall seismic bandwidth can be extended resulting in a higher vertical resolution. Correlation with VSP corridor stack at well location ensures that the generated reflection details after enhancement are geologically plausible.[/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][/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]Generalized S-transform,Resolution enhancement,Time-variant deconvolution,Time-variant wavelet[/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]This research is in part supported by Program Penelitian Pengabdian kepada Masyarakat dan Inovasi (P3MI) 2017 grant funded by the Research and Community Services (LPPM), Institute of Technology, Bandung (ITB), Indonesia.[/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/10.17014/ijog.6.3.223-233[/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]