{"id":444,"date":"2023-10-06T18:18:18","date_gmt":"2023-10-06T18:18:18","guid":{"rendered":"https:\/\/books.gw-project.org\/fractures-and-faults-in-sandstone-and-sandstone-shale-mudstone-sequences\/?post_type=part&p=444"},"modified":"2023-11-23T22:21:10","modified_gmt":"2023-11-23T22:21:10","slug":"9-compaction-bands-and-permeability-upscaling","status":"publish","type":"part","link":"https:\/\/books.gw-project.org\/fractures-and-faults-in-sandstone-and-sandstone-shale-mudstone-sequences\/part\/9-compaction-bands-and-permeability-upscaling\/","title":{"raw":"9 Compaction Bands and Permeability Upscaling\u200c","rendered":"9 Compaction Bands and Permeability Upscaling\u200c"},"content":{"raw":"The compaction bands mapped in the field can be integrated into a model that may be used to create the permeability distribution required by a flow simulator. Deng and others (2017) presented a case that starts from an outcrop map of compaction bands in aeolian sandstone and in-situ measurements, then upscales the permeability to the aquifer or reservoir scale.\r\n\r\nFigure 28a and Figure 28b show idealized block diagrams of 40 m \u00d7 <\/span>40 m \u00d7 <\/span>5 m with multiple compaction band domains and the corresponding model configuration, respectively. The domains of compaction bands based on field data are color-coded in Figure 28a, and idealized compaction bands are represented in Figure 28b.\r\n\r\n \r\n\r\n\"image\"\r\n

Figure 28 \u2013 <\/strong>a) Domains of compaction band patterns based on field observations. <\/span>b) The average spacing of high-angle compaction bands and low-angle bed-parallel compaction bands are about 5 m and 2 m, respectively. The Cartesian coordinates provide orientation. From Deng and others (2017).<\/span><\/p>\r\n \r\n\r\nDeng and others (2017) used the permeability values and the spatial properties of deformation bands measured in outcrops of dunes of aeolian sandstone that are provided in the inset of Figure 29 to calculate and plot the 3D upscaled permeability shown in Figure 29. For this computation, they employed a discrete-feature model developed by Karimi-Fard and others (2004) and a permeability upscaling procedure for fractured rock developed by Wen and others (2003) and Flodin and others (2004).\r\n\r\n \r\n\r\n\"image\"\r\n

Figure 29<\/strong> - Table of permeability values (inset) used for flow simulation and calculated upscaled permeability for one case labeled Case 1. From Deng and others (2017).<\/span><\/p>\r\n \r\n\r\nDeng and others (2017) ran several upscaling cases with varying configurations (patterns) of deformation bands and varying petrophysical (porosity, permeability) and thickness properties. The model presented in Figure 29 is their base case model. Their results revealed the effect of the characteristic configuration of compaction bands on fluid flow when they calculated flow rates using the upscaled permeability components in the x <\/i>direction (normal to the dune trend), y <\/i>direction (parallel to the dune trend) and z <\/i>direction (vertical direction) for several cases.\r\n\r\nThe results suggest that the upscaled permeability of the compartmentalized compaction band arrays is significantly influenced by the permeability, orientations and distribution of compaction band sets. For example, the representative configuration shown in Figure 28 includes a combination of both high-angle domain bands and bed-parallel domain bands, consequently, the upscaled permeability normal to the dune trend (k*x<\/span>) is controlled primarily by the high-angle compaction bands because the flow in this direction crosses the high-angle compaction band domain. The orientation of the major permeability component (k*max<\/span>) remains essentially unaffected by the change in compaction band permeability because the preferred flow path crosses the minimum number of compaction bands. However, the orientation of the minimum permeability component (k*min<\/span>) changes significantly. These results suggest that the interplay between the spatial distributions of compaction band sets and their permeability exerts a significant influence on the orientation of the minimum permeability component (k*min<\/span>).\r\n\r\n ","rendered":"

The compaction bands mapped in the field can be integrated into a model that may be used to create the permeability distribution required by a flow simulator. Deng and others (2017) presented a case that starts from an outcrop map of compaction bands in aeolian sandstone and in-situ measurements, then upscales the permeability to the aquifer or reservoir scale.<\/p>\n

Figure 28a and Figure 28b show idealized block diagrams of 40 m \u00d7 <\/span>40 m \u00d7 <\/span>5 m with multiple compaction band domains and the corresponding model configuration, respectively. The domains of compaction bands based on field data are color-coded in Figure 28a, and idealized compaction bands are represented in Figure 28b.<\/p>\n

 <\/p>\n

\"image\"<\/p>\n

Figure 28 \u2013 <\/strong>a) Domains of compaction band patterns based on field observations. <\/span>b) The average spacing of high-angle compaction bands and low-angle bed-parallel compaction bands are about 5 m and 2 m, respectively. The Cartesian coordinates provide orientation. From Deng and others (2017).<\/span><\/p>\n

 <\/p>\n

Deng and others (2017) used the permeability values and the spatial properties of deformation bands measured in outcrops of dunes of aeolian sandstone that are provided in the inset of Figure 29 to calculate and plot the 3D upscaled permeability shown in Figure 29. For this computation, they employed a discrete-feature model developed by Karimi-Fard and others (2004) and a permeability upscaling procedure for fractured rock developed by Wen and others (2003) and Flodin and others (2004).<\/p>\n

 <\/p>\n

\"image\"<\/p>\n

Figure 29<\/strong> – Table of permeability values (inset) used for flow simulation and calculated upscaled permeability for one case labeled Case 1. From Deng and others (2017).<\/span><\/p>\n

 <\/p>\n

Deng and others (2017) ran several upscaling cases with varying configurations (patterns) of deformation bands and varying petrophysical (porosity, permeability) and thickness properties. The model presented in Figure 29 is their base case model. Their results revealed the effect of the characteristic configuration of compaction bands on fluid flow when they calculated flow rates using the upscaled permeability components in the x <\/i>direction (normal to the dune trend), y <\/i>direction (parallel to the dune trend) and z <\/i>direction (vertical direction) for several cases.<\/p>\n

The results suggest that the upscaled permeability of the compartmentalized compaction band arrays is significantly influenced by the permeability, orientations and distribution of compaction band sets. For example, the representative configuration shown in Figure 28 includes a combination of both high-angle domain bands and bed-parallel domain bands, consequently, the upscaled permeability normal to the dune trend (k*x<\/span>) is controlled primarily by the high-angle compaction bands because the flow in this direction crosses the high-angle compaction band domain. The orientation of the major permeability component (k*max<\/span>) remains essentially unaffected by the change in compaction band permeability because the preferred flow path crosses the minimum number of compaction bands. However, the orientation of the minimum permeability component (k*min<\/span>) changes significantly. These results suggest that the interplay between the spatial distributions of compaction band sets and their permeability exerts a significant influence on the orientation of the minimum permeability component (k*min<\/span>).<\/p>\n

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