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作 者:Zhou Feng Hongliang Wu Weilin Yan Han Tian Jiandong Zheng Chaoliu Li Kewen Wang
机构地区:[1]Research Institute of Petroleum Exploration and Development,CNPC,Beijing,100083,China [2]Exploration and Development Research Institute,Daqing Oilfield,CNPC,Helongjiang,163311,China
出 处:《Energy Geoscience》2024年第3期93-102,共10页能源地球科学(英文)
摘 要:Shale oil reservoirs are generally characterized by complex mineral compositions, rapid lithofacies changes, and thin laminae. Explorations have confirmed that the type and density of shale laminae significantly influence reservoir quality, highlighting the importance of accurately identifying these laminae through well logging for effective shale reservoir evaluation. Presently, relevant technologies primarily focus on the qualitative identification of shale laminae using vertical slab images from image logs. However, influenced by the complex borehole conditions and image logging quality, this approach is less effective in identifying millimeter-scale laminae. This study proposes a new method for achieving high-resolution slab images and quantitatively evaluating the laminae using electrical image logs. The new method effectively improves the processing accuracy of slab images by delicately flattening and aligning the button electrode curves derived from electrical image logs point by point. Meanwhile, it allows for the accurate quantitative evaluation of the lamina number through precise identification of peaks and troughs in microelectrode curves. As demonstrated by the applications in shale oil reservoirs in the Gulong area in Daqing and the Ganchagou area in Qinghai, the proposed method can significantly improve accuracy compared to traditional slab images. Furthermore, the lamination index calculated using this method is highly consistent with the lamina number observed in cores. This study provides a new technical method for the quantitative lamina evaluation and rock structure analysis of shale reservoirs.
关 键 词:Shale oil Slab image Lamina evaluation Lamination index
分 类 号:P631.81[天文地球—地质矿产勘探] P618.13[天文地球—地质学]
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