2021
DOI: 10.1155/2021/6616843
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Pore Properties of the Lacustrine Shale in the Upper Part of the Sha-4 Member of the Paleogene Shahejie Formation in the Dongying Depression in East China

Abstract: Lacustrine shales hold a huge potential oil resource in China. Pore properties (pore volume, diameter, specific surface area, and fractal dimensions) and their relationships with geological factors (mineralogy, insoluble organic carbon, burial depth, and vitrinite reflectance) are critical for evaluating shale oil resource. However, the factors controlling pores for lacustrine shale oil remain unclear, as the relationships between pore properties of Soxhlet-extracted samples and geological factors have not bee… Show more

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Cited by 3 publications
(3 citation statements)
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“…And the noted negative correlation between pyrite content and macropore volume has been linked to the macropore blockage caused by idiomorphic pyrites in the Chang-7 shale (Huang et al, 2023;Wang et al, 2023a). Similar negative correlations and interpretation have also been applied to the Shahejie shale of the Dongying Depression (Wang et al, 2021b;Khan et al, 2022). However, it is imperative to emphasize the substantial interconnections among geological factors.…”
Section: Multicollinearity and Limitation Of Correlation Analysismentioning
confidence: 82%
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“…And the noted negative correlation between pyrite content and macropore volume has been linked to the macropore blockage caused by idiomorphic pyrites in the Chang-7 shale (Huang et al, 2023;Wang et al, 2023a). Similar negative correlations and interpretation have also been applied to the Shahejie shale of the Dongying Depression (Wang et al, 2021b;Khan et al, 2022). However, it is imperative to emphasize the substantial interconnections among geological factors.…”
Section: Multicollinearity and Limitation Of Correlation Analysismentioning
confidence: 82%
“…For example, in an examination of the Bakken shale in North America , linear relationships were assumed across all pore and geological factors, leading to a linear PLS-regression analysis based on the original parameters. In another study focusing on the Shahejie shale in East China (Wang et al, 2021b), researchers contemplated relationships as linear or nonlinear, with the choice of functional forms in the subsequent PLS-regression analysis contingent upon the goodness-of-fit derived from univariate regression models (linear, logarithmic, exponential, and power models). Given the absence of a definitive consensus on the most appropriate functional form, this study embraces the consideration of both assumptions in the two phases of PLS-regression analysis conducted herein.…”
Section: Whole-rock Macropore Volume and Its Geological Correlationsmentioning
confidence: 99%
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