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Q. Hu

Publications and source records attributed to Q. Hu.

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KG²B, a collaborative benchmarking exercise for estimating the permeability of the Grimsel granodiorite - Part 1: measurements, pressure dependence and pore-fluid effects

Measuring 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 collaborative benchmarking exercise involving 24 laboratories was organized for measuring the permeability of a single low permeability material, the Grimsel granodiorite, at a common effective confining pressure (5 MPa). 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 analyze 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. In total 39 measurements were collected that allowed us to discuss the influence of (i) pore-fluid, (ii) measurement method, (iii) sample size and (iv) pressure sensitivity. Discarding some outliers from the bulk data set (4 out of 39) an average permeability of 1.11 × 10 −18 m² with a standard deviation of 0.57 × 10 −18 m² was obtained. The most striking result was the large difference in permeability for gas measurements compared to liquid measurements. Regardless of the method used, gas permeability was higher than liquid permeability by a factor approximately 2 ( k gas = 1.28 × 10 −18 m² compared to k liquid = 0.65 × 10 −18 m²). Possible explanations are that (i) liquid permeability was underestimated due to fluid-rock interactions (ii) gas permeability was overestimated due to insufficient correction for gas slippage and/or (iii) gases and liquids do not probe exactly the same porous networks. The analysis of Knudsen numbers shows that the gas permeability measurements were performed in conditions for which the Klinkenberg correction is sufficient. Smaller samples had a larger scatter of permeability values, suggesting that their volume were below the Representative Elementary Volume. The pressure dependence of permeability was studied by some of the participating teams in the range 1–30 MPa and could be fitted to an exponential law k = k o .exp(– γP eff ) with γ = 0.093 MPa −1 . Good practice rules for measuring permeability in tight materials are also provided.

Geophysical Journal International

KG²B, a collaborative benchmarking exercise for estimating the permeability of the Grimsel granodiorite - Part 2: modeling, microstructures and complementary data

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.

Geophysical Journal International