Elsevier

Earth and Planetary Science Letters

Volume 400, 15 August 2014, Pages 123-129
Earth and Planetary Science Letters

Pore-space distribution and transport properties of an andesitic intrusion

https://doi.org/10.1016/j.epsl.2014.05.042Get rights and content

Highlights

  • We characterize the pore space of an andesitic intrusion by X-ray microtomography.

  • We observe a power law distribution of pore volumes.

  • Power law scaling is attributed to coalescence of pores at crystal–melt boundaries.

  • Weathering of the andesite is associated with preferential growth in the larger pores.

  • Grain boundarity networks preferentially connect large pores to system boundaries.

Abstract

The pore structure of magmatic rocks records processes operating during magma solidification and cooling. It has first order effects on the petrophysical properties of the magmatic rocks, and also influences mass transfer and mineral reactions during subsequent metamorphism or weathering. Here, the pore space characteristics of an andesitic sill intrusion were determined by multiscale resolution computed X-ray microtomography (μ-CT), and the 3D structure was used for transport modeling.

Unaltered andesite has a power law distribution of pore volumes over a range of five orders of magnitude. The probability distribution function (PDF) scales with the inverse square of the pore volume (V), PDFV2. This scaling behavior is attributed to the coalescence of pores at crystal–melt boundaries. Large pores are concentrated on the outer margins of amphibole and plagioclase phenocrystals. Incipient weathering of the andesite is associated with preferential growth of weathering products in the largest pores. This can be explained by a model in which diffusion of external components into the porous andesite is controlled by a random network of grain boundaries and/or microfractures. This network preferentially links the larger pores to the system boundaries and it is the major fluid transport pathway, confining incipient weathering into a small fraction of the rock volume only.

Introduction

The porosity and pore space distribution in rocks provide first order controls on several petrophysical properties, including elastic moduli, diffusivity and permeability (e.g. Guéguen and Palciauskas, 1994). A broad pore size distribution may also drive internal redistribution of mass due to curvature effects on chemical potentials (Emmanuel and Berkowitz, 2007). This may furthermore control the extent to which crystallization processes in the pores of rocks or porous building materials cause fracturing due to growth related stress generation (Scherer, 2004). It is likely that the rate and progress of any fluid infiltration driven volatilization process in porous rocks, including weathering of igneous and metamorphic rocks, serpentinization of oceanic lithosphere, and carbon sequestration by in situ mineral carbonation, is to a large extent affected by the spatial distribution of the pore space as well as by the total porosity.

Recent advances in technology that enable 3D pore structure characterization over a large range of length scales (X-ray tomography, focused ion beam – scanning electron microscopy, neutron scattering, etc.) have dramatically increased our ability to study rock porosity and its effects on rock properties (cf. Zhu et al., 2011, Baker et al., 2012a, Renard, 2012, Keller et al., 2013).

In igneous rocks, porosity is generated when a low-density fluid exsolves from the host magma upon cooling and/or decompression. Bubble formation in rising magmas is a key element in many volcanic processes and has been studied extensively – both experimentally and theoretically (e.g. Sparks et al., 1994, Blower et al., 2002, Yamada et al., 2005, Gonnermann and Manga, 2007, Baker et al., 2012b). Porosity formation during the comparatively slow cooling and crystallization of intrusive rocks has received less attention (see, however Simakin et al., 1999), although it is likely to have a major effect on the petrophysical properties of the magmatic rocks as well as on post magmatic metamorphic or weathering related alteration process.

Here we present a 3D pore space characterization of an andesitic sill intrusion from the Neuquén Basin in Argentina obtained by computed X-ray microtomography. We then analyze the transport properties of a system in which diffusion takes place through a non-percolating pore space, and a matrix in which diffusion is controlled by 2D planar objects such as microfractures and grain boundaries. Our analysis shows that large pores have a higher probability of being part of the transport network than small pores, and thus that large pores will be preferential sites of reaction during post magmatic alteration. This provides a new explanation of why weathering reactions is localized onto only a fraction of the porosity, and why the pore space does not get clogged after incipient reaction.

Section snippets

The rock

The 8–10 m thick sill intrusion investigated here is andesitic to dacitic in composition (62–65 wt% SiO2) and it was sampled near Cuesta del Chihuido in southern Mendoza, Argentina. The intrusion is hosted in the Vaca Muerta Formation of the Medoza Group, a marine limestone-shale unit of Upper Jurassic to Lower Cretaceous age (Leanza and Hugo, 1978). Field relations were described by Jamtveit et al. (2011).

Mineral analysis was performed using the Cameca SX100 electron microprobe at the

The pore space

Two samples of unweathered homogeneous andesite were characterized by multiscale X-ray computed micro-tomography (μCT). Three datasets were obtained at different spatial resolutions. Low resolution data were obtained using a Nikon Metrology model XT H 225 LC industrial type μCT scanner at the Norwegian Geotechnical Institute with a voxel size of 6.6 μm for a 6 mm sized cubic sample. Two additional data sets from a single sample were obtained at spatial resolutions of 0.56 and 2.8 μm on beamline

Discussion

Most studies of pore size distribution in magmatic rocks have been conducted using vesicular volcanic rocks, and both exponential and power law size distributions have been reported (cf. Baker et al., 2006, and references therein). Models that include nucleation and diffusion controlled growth of vesicles lead to an exponential size distribution (Mangan and Cashman, 1996) unless multiple nucleation events are invoked (Blower et al., 2002). Power law distributions on the other hand are often

Conclusions

This study shows that degassing of partly crystalline intrusions may give rise to a power law distribution of pore volumes over a volume range exceeding five orders of magnitude. This scaling behavior may reflect coalescence of pores at the crystal–melt boundaries. As a consequence, large pores tend to be localized near grain boundaries.

Weathering and, by inference, other fluid infiltration driven alteration processes in andesite is associated with preferential mineral growth in the largest

Acknowledgments

We thank Paul Meakin who made several improvements to the manuscript and Elodie Boller at ESRF for the technical help during the tomography scans. We also thank Marcin Dabrowski and Dani Schmid for insightful comments regarding modelling, and Don Baker and an anonymous reviewer for valuable comments that helped us to clarify the paper. This study was supported by a Center of Excellence grant to PGP (grant no. 146031) from the Norwegian Research Council. BJ also benefited from support from the

References (28)

  • D.R. Baker et al.

    A four-dimensional X-ray tomographic microscopy study of bubble growth in basaltic foam

    Nat. Commun.

    (2012)
  • J.D. Blower et al.

    The evolution of bubble size distribution in volcanic eruptions

    J. Volcanol. Geotherm. Res.

    (2002)
  • D.A.G. Bruggeman

    Calculation of various physical constants of heterogeneous substances. II. Dielectricity constants and conductivity of non regular multi crystal systems

    Ann. Phys.

    (1936)
  • M. Dabrowski et al.

    MILAMIN: MATLAB-based finite element method solver for large problems

    Geochem. Geophys. Geosyst.

    (2008)
  • Cited by (8)

    • Role of pore attribute in the localized deformation of granular rocks: A numerical study

      2021, Tectonophysics
      Citation Excerpt :

      For instance, the samples with a larger grain are similar to porous siliciclastic rocks, and the samples with a larger macro-pore are approximate to porous volcanic and carbonate rocks. The generation of micro-porosity is intimately linked with the diagenetic process in carbonate and volcanic rocks, and the micro-pores may be hosted within either the grain or the matrix (e.g., Jamtveit et al., 2014; Hashim and Kaczmarek, 2019). Accordingly, the micro-pore distribution appears to exert an important role in the mechanical behavior, and a high proportion of matrix generally contributes to a homogenous deformation (e.g., Regnet et al., 2015; Baud et al., 2017).

    • Effect of grain sorting, mineralogy and cementation attributes on the localized deformation in porous rocks: A numerical study

      2021, Tectonophysics
      Citation Excerpt :

      The uniform distribution is obtained by limiting the grain sizes in a specific range (Ding et al., 2014); whereas all grain sizes in the normal distribution are assumed to fall within three standard deviations of the mean, which correspond to the specific size range. The power-law distributions of grain sizes and pore volumes have commonly been reported in the literatures (e.g., Cilona et al., 2012; Jamtveit et al., 2014; Su et al., 2018), which are approximated by varying the relative abundances of different sizes defined by the relationship Ni = Nmax × (dmax/di)D, where dmax, di, Nmax, and Ni denote the largest and incremental grain sizes and corresponding abundances respectively (Morgan, 1999). The exponent D, referred to as the fractal dimension, is set to 0.8, 1.6 or 2.6, the increase of which is representative of a finer-grained rock (Fig. 1b; Sammis et al., 1987).

    • Imaging strain localisation in porous andesite using digital volume correlation

      2020, Journal of Volcanology and Geothermal Research
      Citation Excerpt :

      CT has been used to study the topology of the pore space of simple rocks such as Fontainebleau sandstone (Lindquist et al., 2000) and more microstructurally complex porous rocks (e.g., Bauer et al., 2012; Fusseis et al., 2012; Ji et al., 2012; Kandula et al., 2019). The microstructure of lavas (e.g., Song et al., 2001; Jamtveit et al., 2011, 2014; Pola et al., 2012; Bubeck et al., 2017; Schipper et al., 2017) and high-porosity (>0.5) scoria and pumice (e.g., Polacci et al., 2006; Zandomeneghi et al., 2010; Degruyter et al., 2010; Baker et al., 2011; Voltolini et al., 2011; Giachetti et al., 2011; Pardo et al., 2014) have been studied using CT. CT has also been used to study porosity loss by viscous sintering in granular materials in volcanic systems (Wadsworth et al., 2017, 2019) and particle size and shape in tuffisites (Black et al., 2016).

    • Pore type and pore size distribution of tight reservoirs in the Permian Lucaogou Formation of the Jimsar Sag, Junggar Basin, NW China

      2018, Marine and Petroleum Geology
      Citation Excerpt :

      Manual segmentations were found to be time-consuming, and automatic segmentations were completed using Edge Detection Autothreshold in Matlab; the subsequent quantitative data analyses were conducted in Matlab as well (R2017a, The Math Works, 2017). The pore volumes in natural rock have been proven to follow a power law distribution over a five-order of magnitude range (Jamtveit et al., 2014), and a similar distribution has also been defined in 2D pore surfaces (Desbois et al., 2009; Houben et al., 2013; Klaver et al., 2015). The power law exponent D for datasets obtained from various magnified images was calculated via the cumulative distribution function (CDF) with the form CDF (S) ∝ SD.

    View all citing articles on Scopus
    View full text