dorsal/arxiv
View SchemaRepresentative-volume sizing in finite cylindrical computed tomography by low-wavenumber spectral convergence
| Authors | Fernando Alonso-Marroquin, Abdullah Alqubalee, Christian Tantardini |
|---|---|
| Categories | |
| ArXiv ID | 2601.09283vv1 |
| URL | https://arxiv.org/abs/2601.09283 |
| License | http://creativecommons.org/licenses/by-nc-nd/4.0/ |
Abstract
Choosing a representative element volume (REV) from finite cylindrical $\mu$CT scans becomes ambiguous when a key field variable exhibits a slow axial trend, because estimated statistics can change systematically with subvolume size and position rather than converging under simple averaging. A practical workflow is presented to size an REV under such 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 low-wavenumber content stabilizes within a prescribed tolerance. The approach is demonstrated on \textit{Thalassinoides}-bearing rocks, whose branching, connected burrow networks impose heterogeneity on length scales comparable to typical laboratory core diameters, making imaging-based microstructural statistics and downstream digital-rock proxies 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. Representativeness is then posed as a diameter-convergence problem on nested inscribed cylinders: the two-point covariance and its isotropic spectral counterpart $\widehat{C}$ are estimated, and the smallest diameter at which the low-wavenumber plateau becomes stable is selected. Applied to a segmented \textit{Thalassinoides} core, the method identifies a minimum analysis cylinder of approximately $D_{\mathrm{REV}}\approx 93~\mathrm{mm}$ and $H_{\mathrm{REV}}\approx 83~\mathrm{mm}$, enabling reproducible correlation-scale reporting and connectivity-sensitive property estimation.
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"abstract": "Choosing a representative element volume (REV) from finite cylindrical $\\mu$CT scans becomes ambiguous when a key field variable exhibits a slow axial trend, because estimated statistics can change systematically with subvolume size and position rather than converging under simple averaging. A practical workflow is presented to size an REV under such 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 low-wavenumber content stabilizes within a prescribed tolerance. The approach is demonstrated on \\textit{Thalassinoides}-bearing rocks, whose branching, connected burrow networks impose heterogeneity on length scales comparable to typical laboratory core diameters, making imaging-based microstructural statistics and downstream digital-rock proxies highly sensitive to the chosen subvolume. From segmented data, a scalar ``burrowsity\u0027\u0027 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. Representativeness is then posed as a diameter-convergence problem on nested inscribed cylinders: the two-point covariance and its isotropic spectral counterpart $\\widehat{C}$ are estimated, and the smallest diameter at which the low-wavenumber plateau becomes stable is selected. Applied to a segmented \\textit{Thalassinoides} core, the method identifies a minimum analysis cylinder of approximately $D_{\\mathrm{REV}}\\approx 93~\\mathrm{mm}$ and $H_{\\mathrm{REV}}\\approx 83~\\mathrm{mm}$, enabling reproducible correlation-scale reporting and connectivity-sensitive property estimation.",
"arxiv_id": "2601.09283",
"authors": [
"Fernando Alonso-Marroquin",
"Abdullah Alqubalee",
"Christian Tantardini"
],
"categories": [
"cond-mat.soft",
"physics.geo-ph"
],
"license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
"title": "Representative-volume sizing in finite cylindrical computed tomography by low-wavenumber spectral convergence",
"url": "https://arxiv.org/abs/2601.09283",
"version": "v1"
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