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• W2883186120 abstract "Measuring and modelling the permeability of tight rocks remains a challenging task. In addition to the traditional sources of errors that affect more permeable formations (e.g. sample selection, non-representative specimens, disturbance introduced during sample acquisition and preparation), tight rocks can be particularly prone to solid–fluid interactions and thus more sensitive to the methods, procedures and techniques used to measure permeability. To address this problem, it is desirable to collect, for a single material, measurements obtained by different methods and pore fluids. For that purpose, a benchmarking exercise involving 24 laboratories was organized for measuring and modelling the permeability of a single low-permeability material, the Grimsel granodiorite. The objectives of the benchmark were: (i) to compare the results for a given method, (ii) to compare the results between different methods, (iii) to analyse the accuracy of each method, (iv) to study the influence of experimental conditions (especially the nature of pore fluid), (v) to discuss the relevance of indirect methods and models and finally (vi) to suggest good practice for low-permeability measurements. To complement the data set of permeability measurements presented in a companion paper, we focus here on (i) quantitative analysis of microstructures and pore size distribution, (ii) permeability modelling and (iii) complementary measurements of permeability anisotropy and poroelastic parameters. Broad ion beam—scanning electron microscopy, micro-computerized tomography, mercury injection capillary pressure (MICP) and nuclear magnetic resonance (NMR) methods were used to characterize the microstructures and provided the input parameters for permeability modelling. Several models were used: (i) basic statistical models, (ii) 3-D pore network and effective medium models, (iii) percolation model using MICP data and (iv) free-fluid model using NMR data. The models were generally successful in predicting the actual range of measured permeability. Statistical models overestimate the permeability because they do not adequately account for the heterogeneity of the crack network. Pore network and effective medium models provide additional constraints on crack parameters such as aspect ratio, aperture, density and connectivity. MICP and advanced microscopy techniques are very useful tools providing important input data for permeability estimation. Permeability measured—orthogonal to foliation is lower that—parallel to foliation. Combining the experimental and modelling results provide a unique and rich data set." @default.
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• W2883186120 date "2018-07-25" @default.
• W2883186120 modified "2023-10-15" @default.
• W2883186120 title "KG²B, a collaborative benchmarking exercise for estimating the permeability of the Grimsel granodiorite—Part 2: modelling, microstructures and complementary data" @default.
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• W2883186120 cites W1970614936 @default.
• W2883186120 cites W1976113824 @default.
• W2883186120 cites W1978535220 @default.
• W2883186120 cites W1983669509 @default.
• W2883186120 cites W1992742620 @default.
• W2883186120 cites W2007021286 @default.
• W2883186120 cites W2007305535 @default.
• W2883186120 cites W2012842247 @default.
• W2883186120 cites W2026657109 @default.
• W2883186120 cites W2027065708 @default.
• W2883186120 cites W2027349613 @default.
• W2883186120 cites W2031312534 @default.
• W2883186120 cites W2047305972 @default.
• W2883186120 cites W2055295936 @default.
• W2883186120 cites W2056309858 @default.
• W2883186120 cites W2057950781 @default.
• W2883186120 cites W2059870673 @default.
• W2883186120 cites W2072613134 @default.
• W2883186120 cites W2075244986 @default.
• W2883186120 cites W2078638796 @default.
• W2883186120 cites W2081225088 @default.
• W2883186120 cites W2086011236 @default.
• W2883186120 cites W2089956973 @default.
• W2883186120 cites W2091308044 @default.
• W2883186120 cites W2091975395 @default.
• W2883186120 cites W2094624295 @default.
• W2883186120 cites W2100106626 @default.
• W2883186120 cites W2115923359 @default.
• W2883186120 cites W2121241273 @default.
• W2883186120 cites W2123634595 @default.
• W2883186120 cites W2124038023 @default.
• W2883186120 cites W2129330467 @default.
• W2883186120 cites W2141709634 @default.
• W2883186120 cites W2144473622 @default.
• W2883186120 cites W2148148230 @default.
• W2883186120 cites W2154379047 @default.
• W2883186120 cites W2210006880 @default.
• W2883186120 cites W2253332740 @default.
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• W2883186120 doi "https://doi.org/10.1093/gji/ggy305" @default.
• W2883186120 hasPublicationYear "2018" @default.
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