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Coupling seismic data with simulated annealing method improves reservoir characterization
Abdassah D.a, Mucharam L.a, Soengkowo I.a, Trikoranto H.a, Sumantri R.a
a Bandung Inst of Technology, 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]Limitation in quantity as well as distribution of reservoir data leads to unsatisfied realization of inter-well reservoir characterization. Recent development in seismic data processing and analysis, that is seismic inversion, has been able to furnish a footstep to define such physical reservoir data in inter-well vertical section. A stochastic `cloud transform’ method instead of deterministic ones has been applied to change the acoustic impedance to porosity. The present work integrated this stochastic procedure with Simulated Annealing Method (SAM) to optimize reservoir description. Due to strong relationship between impedance and porosity, semivariogram in lateral direction is derived from acoustic impedance data, whereas that in vertical direction is defined from log data in reference wells. A case study on one of Indonesian limestone reservoirs has been conducted. Results showed that seismic impedance-derived porosity is sensitive to lithologic changes. Coupling seismic data with a conventional simulated annealing method gave better simulation result. This work leads to improved understanding of the importance of seismic data in characterizing reservoirs. Detailed results will be presented and discussed.[/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]Petroleum reservoir characterization,Seismic inversion method[/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/10.2523/36968-ms[/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]