Pore and throat size distributions measured from synchrotron X‐ray tomographic images of Fontainebleau sandstones

Lindquist, W. Brent; Venkatarangan, A.; Dunsmuir, J. H.; Wong, Teng-fong

doi:10.1029/2000jb900208

Cited by 436 publications

(371 citation statements)

References 41 publications

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“…With its growing importance in the geological field, SRXTM has been applied to various geomaterials such as sandstone (Lindquist et al, 2000), mylonite (Fusseis et al, 2009), peridotite , volcanic rock (Voltolini et al, 2011), meteorites (Friedrich et al, 2008), gypsum (Fusseis et al, 2012) and shale (Lenoir et al, 2007;Kanitpanyacharoen et al, 2011Kanitpanyacharoen et al, , 2012. Shales are of interest owing to the low porosity and permeability, which allow them to serve as cap rocks for hydrocarbon reservoirs (Best & Katsube, 1995), repository sites for nuclear wastes (Mallants et al, 2001;Bossart & Thury, 2007), and storehouses for carbon sequestration (Chadwick et al, 2004;Busch et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

A comparative study of X-ray tomographic microscopy on shales at different synchrotron facilities: ALS, APS and SLS

Kanitpanyacharoen

Parkinson

Carlo

et al. 2012

J Synchrotron Radiat

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Synchrotron radiation X-ray tomographic microscopy (SRXTM) was used to characterize the three-dimensional microstructure, geometry and distribution of different phases in two shale samples obtained from the North Sea (sample N1) and the Upper Barnett Formation in Texas (sample B1). Shale is a challenging material because of its multiphase composition, small grain size, low but significant amount of porosity, as well as strong shape-and lattice-preferred orientation. The goals of this round-robin project were to (i) characterize microstructures and porosity on the micrometer scale, (ii) compare results measured at three synchrotron facilities, and (iii) identify optimal experimental conditions of high-resolution SRXTM for fine-grained materials. SRXTM data of these shales were acquired under similar conditions at the Advanced Light Source (ALS) of Lawrence Berkeley National Laboratory, USA, the Advanced Photon Source (APS) of Argonne National Laboratory, USA, and the Swiss Light Source (SLS) of the Paul Scherrer Institut, Switzerland. The data reconstruction of all datasets was handled under the same procedures in order to compare the data quality and determine phase proportions and microstructures. With a 10Â objective lens the spatial resolution is approximately 2 mm. The sharpness of phase boundaries in the reconstructed data collected from the APS and SLS was comparable and slightly more refined than in the data obtained from the ALS. Important internal features, such as pyrite (high-absorbing), and low-density features, including pores, fractures and organic matter or kerogen (low-absorbing), were adequately segmented on the same basis. The average volume fractions of low-density features for sample N1 and B1 were estimated at 6.3 (6)% and 4.5 (4)%, while those of pyrite were calculated to be 5.6 (6)% and 2.0 (3)%, respectively. The discrepancy of data quality and volume fractions were mainly due to different types of optical instruments and varying technical set-ups at the ALS, APS and SLS.

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Section: Introductionmentioning

confidence: 99%

A comparative study of X-ray tomographic microscopy on shales at different synchrotron facilities: ALS, APS and SLS

Kanitpanyacharoen

Parkinson

Carlo

et al. 2012

J Synchrotron Radiat

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“…5). Numerous cylindrical straight pipes having a tortuosity of unity are connected randomly to mimic the pore channel network having a specific coordination number at the network junctions in natural sedimentary rocks (Lindquist et al 2000). Affine transformation and pore-erosion operation were applied to the two models.…”

Section: Description Of Diffusion Simulationsmentioning

confidence: 99%

“…The tracer diffuses in the pore network having large pores (pools) and narrow throats (e.g., Roberts and Schwartz 1985;Lindquist et al 2000) as illustrated in Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

Steady-State Local Diffusive Fluxes in Porous Geo-Materials Obtained by Pore-Scale Simulations

Nakashima

Nakano

2012

Transp Porous Med

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Computer simulations of non-sorbing tracers diffusing in fluid-saturated porous sediment/rock were performed using pore-scale X-ray microtomographic images to reveal the following. (i) The histogram of the magnitude of the local diffusive flux vector obeys a unimodal log-normal distribution having a long positive tail. Simulations using model images were also performed to show that the flux broadening in large pores and the flux mixing at the pore network junctions are responsible for the log-normal shape. (ii) The simulation enabled us to directly visualize pore voxels with large and small fluxes, confirming the existence of transport pores and stagnant pores. Because of the unimodal nature, however, it was difficult to distinguish transport pores from stagnant pores using an objective threshold in the histogram. (iii) Another histogram of the flux vector component along the direction of the macroscopic concentration gradient was analyzed. A negative tail was found in the histogram, indicating that local counter diffusion exists in the porous geo-materials. However, the population and intensity of the counter diffusion fluxes are too small and weak to contribute to the overall diffusive transport across the porous media system. A long positive tail representing a large-flux diffusive pathway was also observed in the histogram. However, again, the population of the large-flux transport pores is small. As a result, the main conveyer of the tracer is the stagnant pores (not the transport pores), which have small positive flux values but a large population.

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“…A simple thresholding based on matching a predetermined bulk measurement (phase fraction) is often used to segment a tomographic image. We use a kriging-based thresholding method [37] to give a binary pore-solid image [23,24]. The images are also corrected for noise by re-identifying the phase type of all isolated grain and void voxel clusters.…”

Section: Experimental Images From Microtomographymentioning

confidence: 99%

Characterising the Morphology of Disordered Materials

Arns

Knackstedt

Mecke

2002

Morphology of Condensed Matter

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Abstract. We introduce Minkowski functionals to characterise, reconstruct and discriminate different complex material microstructures, for instance, experimental data sets generated from X-ray computer tomography imaging; samples include a suite of Fontainebleau sandstone, and a heterogeneous cross-bedded sandstone. Three distinct classes of digitised complex microstructure are considered: particle based Boolean models, structures generated by level-cuts through Gaussian fields, and models based on a Voronoi tesselation of space. One can define a set of measures for random composite media from a single image at any phase fraction φ which allows one to accurately reconstruct the medium for all other phase fractions and to predict, for instance, the percolation threshold pc. The evolution of the Minkowski functions during erosion and dilation operations on non-convex morphologies leads to a very accurate discrimination of morphologybetter than commonly used techniques such as structure functions or chord length distributions. Spatial Structures: Experimental Data and Stochastic ModelsThe structure of a disordered material -an oil bearing rock, a piece of paper, or a polymer composite -is a remarkably incoherent concept. Despite this, scientists and engineers are asked to predict the properties of a disordered material based on the "structure" of its constituent components. A major shortcoming in the understanding of processes involving complex materials has been an inability to accurately characterize microstructure. The specification of "structure" requires topological as well as geometric descriptors to characterize the connectivity and the shape of the spatial configuration. In oil recovery from petroleum reservoir rocks, an area of particular interest to the authors, recovery depends crucially on the topology of the pore space and on the mean curvature of the surfaces where immiscible phases meet at a contact angle. To determine accurate flow models and to devise intelligent recovery strategies requires an accurate characterization of reservoir rocks in terms of topology and geometry.To date, the main toolkit used to quantify complex structures has been primarily that of the statistical physicist and not the advanced techniques developed in spatial statistics [11,59]

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Pore and throat size distributions measured from synchrotron X‐ray tomographic images of Fontainebleau sandstones

Cited by 436 publications

References 41 publications

A comparative study of X-ray tomographic microscopy on shales at different synchrotron facilities: ALS, APS and SLS

A comparative study of X-ray tomographic microscopy on shales at different synchrotron facilities: ALS, APS and SLS

Steady-State Local Diffusive Fluxes in Porous Geo-Materials Obtained by Pore-Scale Simulations

Characterising the Morphology of Disordered Materials

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