A New Image Processing Workflow for the Detection of Quartz Types in Shales: Implications for Shale Gas Reservoir Quality Prediction
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...
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MDPI AG
2022-08-01
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| Series: | Minerals |
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| Online Access: | https://www.mdpi.com/2075-163X/12/8/1027 |
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| author | Sen Guo David Misch Reinhard F. Sachsenhofer Yanming Zhu Xin Tang Weichen Bai |
| author_facet | Sen Guo David Misch Reinhard F. Sachsenhofer Yanming Zhu Xin Tang Weichen Bai |
| author_sort | Sen Guo |
| collection | DOAJ |
| description | 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 cm<sup>3</sup>) 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. |
| first_indexed | 2024-03-09T04:03:44Z |
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| institution | Directory Open Access Journal |
| issn | 2075-163X |
| language | English |
| last_indexed | 2024-03-09T04:03:44Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Minerals |
| spelling | doaj.art-8d9c6ddafa434e28b5739cf69ba26f922023-12-03T14:10:24ZengMDPI AGMinerals2075-163X2022-08-01128102710.3390/min12081027A New Image Processing Workflow for the Detection of Quartz Types in Shales: Implications for Shale Gas Reservoir Quality PredictionSen Guo0David Misch1Reinhard F. Sachsenhofer2Yanming Zhu3Xin Tang4Weichen Bai5Coalbed Methane Resources and Reservoir Formation Process Key Laboratory of Ministry of Education, China University of Mining and Technology, Xuzhou 221008, ChinaChair of Petroleum Geology, Montanuniversitaet Leoben, A-8700 Leoben, AustriaChair of Petroleum Geology, Montanuniversitaet Leoben, A-8700 Leoben, AustriaCoalbed Methane Resources and Reservoir Formation Process Key Laboratory of Ministry of Education, China University of Mining and Technology, Xuzhou 221008, ChinaSchool of Civil Engineering, Chongqing Three Gorges University, Chongqing 404100, ChinaEnergy Geology Co., Ltd. of Liaoning Geological Exploration and Mining Group, Shenyang 110013, ChinaA 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 cm<sup>3</sup>) 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.https://www.mdpi.com/2075-163X/12/8/1027shale gasclay-sized quartzimage analysis |
| spellingShingle | Sen Guo David Misch Reinhard F. Sachsenhofer Yanming Zhu Xin Tang Weichen Bai A New Image Processing Workflow for the Detection of Quartz Types in Shales: Implications for Shale Gas Reservoir Quality Prediction Minerals shale gas clay-sized quartz image analysis |
| title | A New Image Processing Workflow for the Detection of Quartz Types in Shales: Implications for Shale Gas Reservoir Quality Prediction |
| title_full | A New Image Processing Workflow for the Detection of Quartz Types in Shales: Implications for Shale Gas Reservoir Quality Prediction |
| title_fullStr | A New Image Processing Workflow for the Detection of Quartz Types in Shales: Implications for Shale Gas Reservoir Quality Prediction |
| title_full_unstemmed | A New Image Processing Workflow for the Detection of Quartz Types in Shales: Implications for Shale Gas Reservoir Quality Prediction |
| title_short | A New Image Processing Workflow for the Detection of Quartz Types in Shales: Implications for Shale Gas Reservoir Quality Prediction |
| title_sort | new image processing workflow for the detection of quartz types in shales implications for shale gas reservoir quality prediction |
| topic | shale gas clay-sized quartz image analysis |
| url | https://www.mdpi.com/2075-163X/12/8/1027 |
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