Quantifying the Impacts of Shale and Clay Distributions on the Effective Elastic Properties of Shaly Sandstones

Abstract Spatial distribution, continuity, shape, concentration, and type of rock components all affect the elastic properties of rocks. Effective medium models, however, do not assimilate the impact of distribution and continuity of rock components. Thin-section images provide quantitative information about rock texture and distribution of components. Their application in assessment of elastic properties of rocks has, however, been limited. The objectives of this paper are to (i) quantify the impacts of clay/shale distribution on the effective elastic properties of clay-rich rocks and (ii) integrate analysis of thin-section images and numerical modeling to enhance assessment of elastic properties of rocks. We perform finite element modeling (FEM) to numerically estimate the effective elastic moduli of centimeter-scale core samples. The inputs to the numerical simulations include segmented images of rock samples (i.e., synthetic or thin-section images) and elastic properties of each rock component. We conduct structural mechanics simulations under static loading conditions. We quantify the resulting stress and strains and calculate the effective elastic properties of the samples. We compare and validate the FEM outcomes against effective medium models such as the self-consistent approximation (SCA) and differential effective medium (DEM) theory. We applied the proposed method to synthetically developed shaly-sandstone samples with laminated, structural, and dispersed clay/shale inclusions as well as thin-section images from a shaly-sandstone formation. Results from synthetic samples and thin-section images suggested that shaly sandstones with structural shale distribution and illite clay type have the highest effective elastic moduli. Moreover, higher shale/clay concentration in shaly sandstones reduces their effective Young's modulus and increases their effective Poisson's ratio. The effective Young's modulus of shaly sandstones drops, and the effective Poisson's ratio increases by an average of 16.4% and 17%, respectively, as shale volumetric concentration increases from 45% to 60%. The outcomes of this paper contribute to the reliable quantification of effective elastic properties of clay-rich rocks featuring different shale/clay distributions, types and concentrations. FEM addressed the limitations of SCA and DEM by incorporating the impacts of clay distribution, continuity, and phase interaction on the effective elastic properties of rocks. Furthermore, integration of FEM and thin-section images enables cost- and time-efficient estimation of rock elastic properties in the absence of seismic and borehole acoustic measurements.

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Journal
SPE Annual Technical Conference and Exhibition
Published
2025-10-13
DOI
https://doi.org/10.2118/228036-ms
Primary Topic
Drilling and Well Engineering
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article
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article

Quantifying the Impacts of Shale and Clay Distributions on the Effective Elastic Properties of Shaly Sandstones

Elsa Maalouf, Zoya Heidari, J. F. El Masry
SPE Annual Technical Conference and Exhibition
Drilling and Well Engineering
article

Quantifying the Impacts of Shale and Clay Distributions on the Effective Elastic Properties of Shaly Sandstones

Elsa Maalouf, Zoya Heidari, J. F. El Masry
article en

Abstract

Abstract Spatial distribution, continuity, shape, concentration, and type of rock components all affect the elastic properties of rocks. Effective medium models, however, do not assimilate the impact of distribution and continuity of rock components. Thin-section images provide quantitative information about rock texture and distribution of components. Their application in assessment of elastic properties of rocks has, however, been limited. The objectives of this paper are to (i) quantify the impacts of clay/shale distribution on the effective elastic properties of clay-rich rocks and (ii) integrate analysis of thin-section images and numerical modeling to enhance assessment of elastic properties of rocks. We perform finite element modeling (FEM) to numerically estimate the effective elastic moduli of centimeter-scale core samples. The inputs to the numerical simulations include segmented images of rock samples (i.e., synthetic or thin-section images) and elastic properties of each rock component. We conduct structural mechanics simulations under static loading conditions. We quantify the resulting stress and strains and calculate the effective elastic properties of the samples. We compare and validate the FEM outcomes against effective medium models such as the self-consistent approximation (SCA) and differential effective medium (DEM) theory. We applied the proposed method to synthetically developed shaly-sandstone samples with laminated, structural, and dispersed clay/shale inclusions as well as thin-section images from a shaly-sandstone formation. Results from synthetic samples and thin-section images suggested that shaly sandstones with structural shale distribution and illite clay type have the highest effective elastic moduli. Moreover, higher shale/clay concentration in shaly sandstones reduces their effective Young's modulus and increases their effective Poisson's ratio. The effective Young's modulus of shaly sandstones drops, and the effective Poisson's ratio increases by an average of 16.4% and 17%, respectively, as shale volumetric concentration increases from 45% to 60%. The outcomes of this paper contribute to the reliable quantification of effective elastic properties of clay-rich rocks featuring different shale/clay distributions, types and concentrations. FEM addressed the limitations of SCA and DEM by incorporating the impacts of clay distribution, continuity, and phase interaction on the effective elastic properties of rocks. Furthermore, integration of FEM and thin-section images enables cost- and time-efficient estimation of rock elastic properties in the absence of seismic and borehole acoustic measurements.

SPE Annual Technical Conference and Exhibition
The University of Texas at Austin (US), American University of Beirut (LB)
Openalex Percentile: Top 34%
Drilling and Well Engineering
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