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Shift-delay and stack microseismic event localization with application to a geothermal field in Indonesia
Hendriyana A.a,b, Jaya M.c, Bauer K.a, Sule R.b
a GFZ Potsdam, Germany
b ITB, Indonesia
c SGS Horizon, Netherlands
[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]Imaging techniques which provide the spatial distribution of microseismic events are increasingly used to monitor the behaviour of geothermal reservoirs during production. As seismometers are installed for longer time, the volume of recorded data volumes are getting too large to apply classical approaches of seismological event localization. We developed a seismic event localization method which is called “shift delay and stack” (SDS) which is based on the depth migration of a characterstic function (CF) derived from the recorded wavefield. The depth location of the event is determined based on the global maximum of a coherency function. We also introduce a new kurtosis-based CF which enhances the onset of the P-wave arrivals. No picking is needed to apply the SDS method for event localization, hence data preparation and processing time can be reduced. The SDS method is applied to the microseismic data recorded at a geothermal field in Indonesia. The results show that the SDS method is capable of producing reliable event locations. The location uncertainty can be deduced from the results. Two previously known N-S trending faults are successfully detected by the algorithm. Moreover, the extension of the productive reservoir volume can be identified by our investigation.[/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]Classical approach,Coherency function,Data preparation,Event localizations,Geothermal reservoir,Location uncertainty,Microseismic events,Reservoir volume[/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/10.3997/2214-4609.201413020[/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]