A New Image Processing Workflow for the Detection of Quartz Types in Shales: Implications for Shale Gas Reservoir Quality Prediction

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A New Image Processing Workflow for the Detection of Quartz Types in Shales: Implications for Shale Gas Reservoir Quality Prediction. / Guo, Sen; Misch, David; Sachsenhofer, Reinhard F. et al.
In: Minerals, Vol. 12.2022, No. 8, 1027, 16.08.2022.

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@article{373fd8bf497b4628b769ba260b4bdaf7,
title = "A New Image Processing Workflow for the Detection of Quartz Types in Shales: Implications for Shale Gas Reservoir Quality Prediction",
abstract = "A shale lithofacies scheme is commonly used to characterize source rock reservoirs of the Lower Cambrian Niutitang Formation. However, this classification ignores that individual components such as quartz may have different origins, potentially affecting reservoir quality. The main objective of this article is, therefore, to present a refined scheme for lithofacies and an image processing workflow for the detection of quartz types in the Niutitang Formation shales from the Jiumen outcrop in the Guizhou Province (Upper Yangtze Basin, SW China). In order to do so, a combination of bulk density, optical and scanning electron microscopy and image analysis was used. The shale lithology was macroscopically classified into seven major categories and nineteen subcategories. Subsequently, the shales were investigated at the microscopic level, mainly focusing on quartz types and microstructural variations. Afterwards, the workflow to calculate the weight per unit volume (1 cm3) of the quartz types was presented, i.e., firstly, by calculating the weight of mineral matter by subtraction of the measured weight of organic matter from the bulk shale; secondly, by calculating the weight of total quartz in bulk shale from the weight of mineral matter and its proportion calculated from X-ray diffraction data; thirdly, by calculating the weight of detrital quartz and non-detrital quartz with energy dispersive X-ray mapping, image processing and quartz density; finally, by calculating the weight of clay-sized quartz by subtracting of the weight of detrital and non-detrital quartz from the weight of the total quartz. The bulk quartz content was found to be dominated by clay-sized quartz, which may mainly control the mesopore volume available for gas storage and, hence, the shale gas reservoir development.",
keywords = "clay-sized quartz, image analysis, shale gas",
author = "Sen Guo and David Misch and Sachsenhofer, {Reinhard F.} and Yanming Zhu and Xin Tang and Weichen Bai",
note = "Publisher Copyright: {\textcopyright} 2022 by the authors.",
year = "2022",
month = aug,
day = "16",
doi = "10.3390/min12081027",
language = "English",
volume = "12.2022",
journal = "Minerals",
issn = "2075-163X",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "8",

}

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TY - JOUR

T1 - A New Image Processing Workflow for the Detection of Quartz Types in Shales

T2 - Implications for Shale Gas Reservoir Quality Prediction

AU - Guo, Sen

AU - Misch, David

AU - Sachsenhofer, Reinhard F.

AU - Zhu, Yanming

AU - Tang, Xin

AU - Bai, Weichen

N1 - Publisher Copyright: © 2022 by the authors.

PY - 2022/8/16

Y1 - 2022/8/16

N2 - A shale lithofacies scheme is commonly used to characterize source rock reservoirs of the Lower Cambrian Niutitang Formation. However, this classification ignores that individual components such as quartz may have different origins, potentially affecting reservoir quality. The main objective of this article is, therefore, to present a refined scheme for lithofacies and an image processing workflow for the detection of quartz types in the Niutitang Formation shales from the Jiumen outcrop in the Guizhou Province (Upper Yangtze Basin, SW China). In order to do so, a combination of bulk density, optical and scanning electron microscopy and image analysis was used. The shale lithology was macroscopically classified into seven major categories and nineteen subcategories. Subsequently, the shales were investigated at the microscopic level, mainly focusing on quartz types and microstructural variations. Afterwards, the workflow to calculate the weight per unit volume (1 cm3) of the quartz types was presented, i.e., firstly, by calculating the weight of mineral matter by subtraction of the measured weight of organic matter from the bulk shale; secondly, by calculating the weight of total quartz in bulk shale from the weight of mineral matter and its proportion calculated from X-ray diffraction data; thirdly, by calculating the weight of detrital quartz and non-detrital quartz with energy dispersive X-ray mapping, image processing and quartz density; finally, by calculating the weight of clay-sized quartz by subtracting of the weight of detrital and non-detrital quartz from the weight of the total quartz. The bulk quartz content was found to be dominated by clay-sized quartz, which may mainly control the mesopore volume available for gas storage and, hence, the shale gas reservoir development.

AB - A shale lithofacies scheme is commonly used to characterize source rock reservoirs of the Lower Cambrian Niutitang Formation. However, this classification ignores that individual components such as quartz may have different origins, potentially affecting reservoir quality. The main objective of this article is, therefore, to present a refined scheme for lithofacies and an image processing workflow for the detection of quartz types in the Niutitang Formation shales from the Jiumen outcrop in the Guizhou Province (Upper Yangtze Basin, SW China). In order to do so, a combination of bulk density, optical and scanning electron microscopy and image analysis was used. The shale lithology was macroscopically classified into seven major categories and nineteen subcategories. Subsequently, the shales were investigated at the microscopic level, mainly focusing on quartz types and microstructural variations. Afterwards, the workflow to calculate the weight per unit volume (1 cm3) of the quartz types was presented, i.e., firstly, by calculating the weight of mineral matter by subtraction of the measured weight of organic matter from the bulk shale; secondly, by calculating the weight of total quartz in bulk shale from the weight of mineral matter and its proportion calculated from X-ray diffraction data; thirdly, by calculating the weight of detrital quartz and non-detrital quartz with energy dispersive X-ray mapping, image processing and quartz density; finally, by calculating the weight of clay-sized quartz by subtracting of the weight of detrital and non-detrital quartz from the weight of the total quartz. The bulk quartz content was found to be dominated by clay-sized quartz, which may mainly control the mesopore volume available for gas storage and, hence, the shale gas reservoir development.

KW - clay-sized quartz

KW - image analysis

KW - shale gas

UR - http://www.scopus.com/inward/record.url?scp=85137599336&partnerID=8YFLogxK

U2 - 10.3390/min12081027

DO - 10.3390/min12081027

M3 - Article

AN - SCOPUS:85137599336

VL - 12.2022

JO - Minerals

JF - Minerals

SN - 2075-163X

IS - 8

M1 - 1027

ER -