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Steam and Brine Zone Prediction around Geothermal Reservoir Derived from Delay Time Seismic Tomography and Anisotropy Case Study: “pR” Geothermal Field
Hendrawan Palgunadi K.a, Nugraha A.D.a, Sule R.a, Meidiana T.a
a Undergraduate Program of Geophysical Engineering, Faculty of Mining and Petroleum Engineering, Institut Teknologi Bandung, 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]© Published under licence by IOP Publishing Ltd.Development of geothermal production can be conducted in several ways, one of them analyses the fracture or crack and structure within the reservoir. Due to low permeability and porosity value within the reservoir in geothermal field. This crack or fracture provide porosity for fluid storage and permeability for fluid movement and play a major role in production from this kind of reservoir. Structure and polarization direction can be derived from anisotropy parameter and seismic velocity parameter in geothermal field. In this study, we used micro-earthquake data of 1,067 events that were recorded by the average of 15 stations during almost 1-year measurement. We used anisotropy parameter using 3-D shear-wave splitting (SWS) tomography method to represent the distribution of anisotropy medium around the geothermal field. Two parameters produced from the S-wave analysis, which is polarization direction and delay time between fast S-wave and slow S-wave. To determine SWS parameters, we used a rotation of horizontal seismogram including N-S component and E-W component. Furthermore, we used short-time fourier transform (STFT) to calculate lag time and time window based on wave periods. Two horizontal components have been rotated from azimuth 0° to 180° with an increment of 1°. Cross-correlation coefficient used every azimuth of two horizontal components based on delay time with predetermined time window obtained by STFT. When cross-correlation coefficient is high, the corresponding value of delay time and azimuth are chosen as the polarization direction and delay time of SWS. Normalized time different divided by total ray length was used to determine the distribution of crack density. Through correlation of seismic velocity model, crack density, and 3-D anisotropy tomography, we can delineate a geothermal reservoir model. Our results show, high degree of anisotropy and crack density occur in the northern and eastern part of “PR” geothermal field for further development. The result had good correlation with high production of geothermal activities.[/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]Anisotropy parameters,Cross-correlation coefficient,geothermal,Micro-earthquakes,Polarization direction,Seismic velocity models,Shear wave splitting,Short time Fourier transforms[/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]geothermal,micro-earthquake,SWS,tomography[/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/10.1088/1755-1315/62/1/012027[/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]