Quantification of Pore Size Population and Diagenesis using Digital Rock Tools
Quantification of the pore system in reservoir rocks is essential for subsurface exploration to understand the displacement process to locate the remaining hydrocarbon. To acquire a better understanding of rock physics and pore structure, a more quantitative method is required. Practically, a repres...
Published in: | Asia Petroleum Geoscience Conference and Exhibition, APGCE 2022 |
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European Association of Geoscientists and Engineers, EAGE
2022
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2-s2.0-85172359365 Japperi N.S.; Wu K.; Starkey A.; Panaitescu C. Quantification of Pore Size Population and Diagenesis using Digital Rock Tools 2022 Asia Petroleum Geoscience Conference and Exhibition, APGCE 2022 10.3997/2214-4609.202270209 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172359365&doi=10.3997%2f2214-4609.202270209&partnerID=40&md5=515fe29c59a5f21dd79fc9dda3abb7f8 Quantification of the pore system in reservoir rocks is essential for subsurface exploration to understand the displacement process to locate the remaining hydrocarbon. To acquire a better understanding of rock physics and pore structure, a more quantitative method is required. Practically, a representative large-scale multiscale pore structure model for mixed wettability reservoirs can be constructed by adding diagenesis and facies modelling. This study tries to use the detailed pore structure and diagenesis information from scanning electron microscopy (SEM) and micro computed tomography (micro-CT) imaging to quantify the diagenesis linked to the reservoir rocks’ quality. This involves the pore and grain size distribution, cement, and pore fill mineral features of rock samples by discretizing them into different elements. These features will be quantified using statistical population function based on the high-resolution SEM and micro-CT images. Through distributions functions fitting, the cubic polynomial exhibits the best fits and the lowest mean square error (MSE). The best-fitted curve from all images is found on the normal distribution for both histogram and log histogram. The digital rock tools are able to provide the details of the pore structure and associated diagenetic process with lithofacies. Furthermore, the well-logging features will be linked in further analysis. © Asia Petroleum Geoscience Conference and Exhibition, APGCE 2022. European Association of Geoscientists and Engineers, EAGE English Conference paper |
author |
Japperi N.S.; Wu K.; Starkey A.; Panaitescu C. |
spellingShingle |
Japperi N.S.; Wu K.; Starkey A.; Panaitescu C. Quantification of Pore Size Population and Diagenesis using Digital Rock Tools |
author_facet |
Japperi N.S.; Wu K.; Starkey A.; Panaitescu C. |
author_sort |
Japperi N.S.; Wu K.; Starkey A.; Panaitescu C. |
title |
Quantification of Pore Size Population and Diagenesis using Digital Rock Tools |
title_short |
Quantification of Pore Size Population and Diagenesis using Digital Rock Tools |
title_full |
Quantification of Pore Size Population and Diagenesis using Digital Rock Tools |
title_fullStr |
Quantification of Pore Size Population and Diagenesis using Digital Rock Tools |
title_full_unstemmed |
Quantification of Pore Size Population and Diagenesis using Digital Rock Tools |
title_sort |
Quantification of Pore Size Population and Diagenesis using Digital Rock Tools |
publishDate |
2022 |
container_title |
Asia Petroleum Geoscience Conference and Exhibition, APGCE 2022 |
container_volume |
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container_issue |
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doi_str_mv |
10.3997/2214-4609.202270209 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172359365&doi=10.3997%2f2214-4609.202270209&partnerID=40&md5=515fe29c59a5f21dd79fc9dda3abb7f8 |
description |
Quantification of the pore system in reservoir rocks is essential for subsurface exploration to understand the displacement process to locate the remaining hydrocarbon. To acquire a better understanding of rock physics and pore structure, a more quantitative method is required. Practically, a representative large-scale multiscale pore structure model for mixed wettability reservoirs can be constructed by adding diagenesis and facies modelling. This study tries to use the detailed pore structure and diagenesis information from scanning electron microscopy (SEM) and micro computed tomography (micro-CT) imaging to quantify the diagenesis linked to the reservoir rocks’ quality. This involves the pore and grain size distribution, cement, and pore fill mineral features of rock samples by discretizing them into different elements. These features will be quantified using statistical population function based on the high-resolution SEM and micro-CT images. Through distributions functions fitting, the cubic polynomial exhibits the best fits and the lowest mean square error (MSE). The best-fitted curve from all images is found on the normal distribution for both histogram and log histogram. The digital rock tools are able to provide the details of the pore structure and associated diagenetic process with lithofacies. Furthermore, the well-logging features will be linked in further analysis. © Asia Petroleum Geoscience Conference and Exhibition, APGCE 2022. |
publisher |
European Association of Geoscientists and Engineers, EAGE |
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English |
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Conference paper |
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scopus |
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Scopus |
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1820775456784252928 |