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Hydraulic conductivity modeling of fractured rock at grasberg surface mine, Papua-Indonesia
Cahyadi T.A.a, Widodo L.E.a, Syihab Z.a, Notosiswoyo S.a, Widijanto E.b
a Faculty of Mining and Petroleum Engineering, Bandung Institute of Technology, Bandung, 40132, Indonesia
b Surface Mine GeoEngineering, PTFI, Grasberg Surface Mine, Papua, 99930, 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]© 2017 Published by ITB Journal Publisher.Packer tests and slug tests were conducted at 49 points at the Grasberg surface mine, Indonesia to obtain hydraulic conductivity data. The HC-system approach, which relies on rock quality designation, lithology permeability index, depth index, and gouge content designation, was applied. Geotechnical drill holes in 441 locations, consisting of 4,850 points of information, were used to determine the K values using the equation K = 2×10-6x HC0.5571. The K values, which were within the range of 10-8and 10-5m/s, were distributed into five alternative 3D distributions using Ordinary Kriging (OK) and Artificial Neural Network (ANN). The result of the ANN modeling showed that some of the K values, with log K varying from -10.51 m/s to -3.09 m/s, were outside the range of the observed K values. The OK modeling results of K values, with log K varying from -8.12 m/s to -5.75 m/s, were within the range of the observed K values. The ANN modeled K values were slightly more varied than the OK modeled values. The result of an alternative OK modeling was chosen to represent the existing data population of flow media because it fits well to the geological conditions.[/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]Data population,Fractured rock,Geological conditions,HC-system,Ordinary kriging,Permeability index,Rock quality designation,System approach[/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]Artificial neural network (ANN),Fractured rock,HC-system,Ordinary kriging (OK),Spatial hydraulic conductivity[/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/10.5614/j.eng.technol.sci.2017.49.1.3[/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]