Choosing a representative element volume (REV) from finite cylindrical computed tomography (CT) scans becomes ambiguous when a key field variable exhibits a slow axial trend, which may reflect both genuine geological variability and CT acquisition/reconstruction artifacts, because estimated statistics can change systematically with subvolume size and position rather than converging under simple averaging. A practical workflow is presented for sizing an REV under nonstationary conditions by first suppressing axial drift/trend to obtain a residual field suitable for second-order analysis, and then selecting the smallest analysis diameter for which the low-wavenumber content stabilizes within a prescribed tolerance. The approach is demonstrated on Thalassinoides-bearing rocks, whose branching, interconnected burrow networks introduce heterogeneity at length scales comparable to typical laboratory core diameters, making imaging-based microstructural statistics and downstream digital-rock estimates highly sensitive to the chosen subvolume. From segmented data, a scalar “burrowsity” field–capturing burrow-related pore spaces and infills–is defined, and axial detrending (with optional normalization) is applied to mitigate acquisition drift and nonstationary trends, while the subsequent covariance/spectral test is evaluated on nested cylinders consistent with the core geometry. Representativeness is then posed as a diameter-convergence problem on nested inscribed cylinders: the two-point covariance and its isotropic spectral counterpart <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$\widehat{C}$</EquationSource> <EquationSource Format="MATHML"><math> <mover accent="true"> <mi>C</mi> <mo stretchy="true">^</mo> </mover> </math></EquationSource> </InlineEquation> are estimated, and the smallest diameter at which the low-wavenumber plateau becomes stable is selected. Applied to a segmented Thalassinoides core, the method identifies a minimum analysis cylinder of approximately <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$D_{\textrm{REV}}\approx 93~\textrm{mm}$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msub> <mi>D</mi> <mtext>REV</mtext> </msub> <mo>≈</mo> <mn>93</mn> <mspace width="3.33333pt" /> <mtext>mm</mtext> </mrow> </math></EquationSource> </InlineEquation> and <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$H_{\textrm{REV}}\approx 83~\textrm{mm}$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msub> <mi>H</mi> <mtext>REV</mtext> </msub> <mo>≈</mo> <mn>83</mn> <mspace width="3.33333pt" /> <mtext>mm</mtext> </mrow> </math></EquationSource> </InlineEquation>, enabling reproducible correlation-scale reporting and connectivity-sensitive property estimation.

Representative-Volume Sizing in Finite Cylindrical Computed Tomography by Low-Wavenumber Spectral Convergence

期刊论文
发表日期：

2026年7月1日

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Fernando Alonso-Marroquín,
Abdullah Alqubalee,
Christian Tantardini

摘要

Choosing a representative element volume (REV) from finite cylindrical computed tomography (CT) scans becomes ambiguous when a key field variable exhibits a slow axial trend, which may reflect both genuine geological variability and CT acquisition/reconstruction artifacts, because estimated statistics can change systematically with subvolume size and position rather than converging under simple averaging. A practical workflow is presented for sizing an REV under nonstationary conditions by first suppressing axial drift/trend to obtain a residual field suitable for second-order analysis, and then selecting the smallest analysis diameter for which the low-wavenumber content stabilizes within a prescribed tolerance. The approach is demonstrated on Thalassinoides-bearing rocks, whose branching, interconnected burrow networks introduce heterogeneity at length scales comparable to typical laboratory core diameters, making imaging-based microstructural statistics and downstream digital-rock estimates highly sensitive to the chosen subvolume. From segmented data, a scalar “burrowsity” field–capturing burrow-related pore spaces and infills–is defined, and axial detrending (with optional normalization) is applied to mitigate acquisition drift and nonstationary trends, while the subsequent covariance/spectral test is evaluated on nested cylinders consistent with the core geometry. Representativeness is then posed as a diameter-convergence problem on nested inscribed cylinders: the two-point covariance and its isotropic spectral counterpart $\widehat{C}$ $\hat{C}$ are estimated, and the smallest diameter at which the low-wavenumber plateau becomes stable is selected. Applied to a segmented Thalassinoides core, the method identifies a minimum analysis cylinder of approximately $D_{\textrm{REV}}\approx 93~\textrm{mm}$ $D_{REV} \approx 93 mm$ and $H_{\textrm{REV}}\approx 83~\textrm{mm}$ $H_{REV} \approx 83 mm$ , enabling reproducible correlation-scale reporting and connectivity-sensitive property estimation.