The dataset of lamina structure in fine-grained rocks

Fine-grained sedimentary rocks account for two-thirds of all sedimentary rocks, and contain multi-scale lamina structure. Lamina structure contain important information about paleoenvironmental reconstruction, climate change, depositional processes, hydrocarbon accumulation and even global carbon cycle. Fine-grained sedimentary rocks can be divided into massive, layered and laminated according to core-scale lamina observation. Thin section observation reveals that the mineral composition of individual lamina includes carbonate, silt, clay mineral, tuffaceous lamina and organic matter lamina in the micrometer-scales. However, for intervals without core data control, geophysical well logs are needed to predict the multi-scale lamina structure in fine-grained sedimentary rocks. High resolution image logs provide 5 mm vertical resolution images, however, they don’t highlight the lamina characteristics, therefore image logs are used to generate the slab image and button conductivity curves to facilitate the recognition of lamina structure up to 2.5 vertical resolution. This novel and multidisciplinary approach provides a powerful method for continuously identifying lamina structure with a 2.5 mm vertical resolution using well logs.细粒沉积岩（fine-grained sedimentary rocks）占所有沉积岩的三分之二，且发育多尺度纹层构造（lamina structure）。纹层构造蕴含着古环境重建（paleoenvironmental reconstruction）、气候变化、沉积作用过程（depositional processes）、油气聚集（hydrocarbon accumulation）乃至全球碳循环等诸多重要信息。基于岩心尺度纹层观测，细粒沉积岩可划分为块状、层状与纹层状三类。薄片观测（thin section observation）表明，微米尺度（micrometer-scales）下单纹层的矿物组成（mineral composition）包括碳酸盐岩（carbonate）、粉砂（silt）、黏土矿物（clay mineral）、凝灰质纹层（tuffaceous lamina）以及有机质纹层（organic matter lamina）。然而，对于缺乏岩心数据控制（core data control）的井段，需借助地球物理测井资料（geophysical well logs）来预测细粒沉积岩内的多尺度纹层构造。高分辨率成像测井（high resolution image logs）可提供垂向分辨率（vertical resolution）为5 mm的井壁图像，但无法有效凸显纹层特征。为此，研究人员通过成像测井数据生成井壁切片图像与纽扣式电导率曲线，以实现垂向分辨率达2.5 mm的纹层构造识别。这种新颖的多学科方法（multidisciplinary approach），为利用测井资料实现垂向分辨率达2.5 mm的纹层构造连续识别提供了强有力的技术手段。