A LithoScanner logging data processing method and application applicable to shale oil formation
Lithology identification is crucial for understanding the characteristics of reservoirs, optimizing development plans, and enhancing development efficiency. For shale oil formations, the mineral composition is complex and the lithological combinations are diverse, which imposes limitations on conven...
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Frontiers Media S.A.
2025-03-01
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| Series: | Frontiers in Earth Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2025.1524300/full |
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| author | Xuan Hu Zhen Lin Wang Jing Su Wang Wang Yang Xiao Xuan Chen Peng Liu Lei Zhao |
| author_facet | Xuan Hu Zhen Lin Wang Jing Su Wang Wang Yang Xiao Xuan Chen Peng Liu Lei Zhao |
| author_sort | Xuan Hu |
| collection | DOAJ |
| description | Lithology identification is crucial for understanding the characteristics of reservoirs, optimizing development plans, and enhancing development efficiency. For shale oil formations, the mineral composition is complex and the lithological combinations are diverse, which imposes limitations on conventional well logging interpretation for lithology identification.LithoScanner Logging is a method for quantifying mineral content; however, discrepancies persist between logging-derived mineral content and core experimental results in the actual exploration and development process. There are four main problems in LithoScanner Logging data processing: 1. Core data used to calibrate the dry weight of LithoScanner Logging elements are difficult to locate; 2. Changes in sedimentary environments and downhole geological conditions in different regions have a greater impact onthe instrument’s built-in sensitivity parameters; 3. The converted yields of some elements with low dry weight percentages are converted to dry weight curves, and the data are distorted not reflecting the real situation of the stratum; 4. The optimization algorithm exhibits poor applicability, lacks robust constraints, converges rapidly, and tends to trap in local optima. In response to the four questions above. First, rock matrix density is calculated using density and nuclear magnetic resonance (NMR) logging data, serving as the basis for depth normalization of core data; secondly, based on the oxide closure model, the offset and scaling factor are added to the calculation of the elemental dry weights, so as to obtain the optimal solution of the logged elemental dry weights; lastly, the elemental dry weights are combined with the differential evolution method, and the density profile and the sum of the mineral dry weights is used as the constraints, so as to carry out the inversion of the mineral dry weight is inverted.The results of mineral inversion have been well applied in different types of shale oil such as Daqing Gulong, Sichuan Liang Gaoshan, Xinjiang Mabei, etc. The mean absolute error between calculated mineral dry weights and core XRD experimental results is less than 5%. |
| format | Article |
| id | doaj-art-3f3b83a763df446d83ddfc0516ee5f03 |
| institution | DOAJ |
| issn | 2296-6463 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj-art-3f3b83a763df446d83ddfc0516ee5f032025-08-20T03:02:28ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632025-03-011310.3389/feart.2025.15243001524300A LithoScanner logging data processing method and application applicable to shale oil formationXuan HuZhen Lin WangJing SuWang Wang YangXiao Xuan ChenPeng LiuLei ZhaoLithology identification is crucial for understanding the characteristics of reservoirs, optimizing development plans, and enhancing development efficiency. For shale oil formations, the mineral composition is complex and the lithological combinations are diverse, which imposes limitations on conventional well logging interpretation for lithology identification.LithoScanner Logging is a method for quantifying mineral content; however, discrepancies persist between logging-derived mineral content and core experimental results in the actual exploration and development process. There are four main problems in LithoScanner Logging data processing: 1. Core data used to calibrate the dry weight of LithoScanner Logging elements are difficult to locate; 2. Changes in sedimentary environments and downhole geological conditions in different regions have a greater impact onthe instrument’s built-in sensitivity parameters; 3. The converted yields of some elements with low dry weight percentages are converted to dry weight curves, and the data are distorted not reflecting the real situation of the stratum; 4. The optimization algorithm exhibits poor applicability, lacks robust constraints, converges rapidly, and tends to trap in local optima. In response to the four questions above. First, rock matrix density is calculated using density and nuclear magnetic resonance (NMR) logging data, serving as the basis for depth normalization of core data; secondly, based on the oxide closure model, the offset and scaling factor are added to the calculation of the elemental dry weights, so as to obtain the optimal solution of the logged elemental dry weights; lastly, the elemental dry weights are combined with the differential evolution method, and the density profile and the sum of the mineral dry weights is used as the constraints, so as to carry out the inversion of the mineral dry weight is inverted.The results of mineral inversion have been well applied in different types of shale oil such as Daqing Gulong, Sichuan Liang Gaoshan, Xinjiang Mabei, etc. The mean absolute error between calculated mineral dry weights and core XRD experimental results is less than 5%.https://www.frontiersin.org/articles/10.3389/feart.2025.1524300/fullelemental capture spectroscopyLithoScanner logginglithology interpretationmineral dry weightshale oil reservoir |
| spellingShingle | Xuan Hu Zhen Lin Wang Jing Su Wang Wang Yang Xiao Xuan Chen Peng Liu Lei Zhao A LithoScanner logging data processing method and application applicable to shale oil formation Frontiers in Earth Science elemental capture spectroscopy LithoScanner logging lithology interpretation mineral dry weight shale oil reservoir |
| title | A LithoScanner logging data processing method and application applicable to shale oil formation |
| title_full | A LithoScanner logging data processing method and application applicable to shale oil formation |
| title_fullStr | A LithoScanner logging data processing method and application applicable to shale oil formation |
| title_full_unstemmed | A LithoScanner logging data processing method and application applicable to shale oil formation |
| title_short | A LithoScanner logging data processing method and application applicable to shale oil formation |
| title_sort | lithoscanner logging data processing method and application applicable to shale oil formation |
| topic | elemental capture spectroscopy LithoScanner logging lithology interpretation mineral dry weight shale oil reservoir |
| url | https://www.frontiersin.org/articles/10.3389/feart.2025.1524300/full |
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