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Influence of coordination number and percolation probability on rock permeability estimation
Fauzi U.a, Hoerdt A.b, Neubauer F.M.b
a Earth Physics Laboratory, Department of Physics, Institute of Technology Bandung, Indonesia
b Institute of Geophysics and Meteorology, University of Cologne, Germany
[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]Copyright 2002 by the American Geophysical Union.Estimation of permeability from image sections can be conducted by means of Local Porosity Theory (LPT) and the effective medium approximation (EMA). Using these approaches, the coordination number that is important for rock modeling is included. In this paper, we extend the EMA approach by considering the percolation probability as an additional parameter. Both equations show that permeability will be higher as coordination number as well as percolation probability increases. The permeability increases most rapidly close to the percolation threshold. Several thin sections of sandstone were created by digital image analysis. Two Point Correlation Functions were applied to estimate porosity and specific surface area. Permeability distribution as an input to EMA was created from the local permeability. The effective permeability was then calculated from the EMA equation iteratively. The result shows that considering coordination number and percolation probability will improve permeability estimation.[/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]Digital image analysis,Effective permeability,Effective-medium approximation,Percolation probability,Percolation thresholds,Permeability distribution,Permeability estimation,Two point correlation functions[/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/10.1029/2001GL013414[/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]