Abstract Characterization of shale systems requires imaging at different scales. One reason can be due to a diverse pore-size distribution. Low-resolution images often cover the large-scale structures and are available for a large region of the sample. On the other hand, fine-scale images usually cover a small region and they are mostly used to discover the complexity within the nano-scale pores in shale samples. Acquiring large image containing both the micro- and the nano-scale feature can be very expensive and time demanding. In this paper, a new method for integrating of such images at different scales is proposed. The aim is to include the nano-scale information within the coarse images. The input of this method is a set of coarse- and fine-scale images. The corresponding regions of each fine-scale image within the coarser image are determined using a similarity map. Then, the coarse image is refined iteratively to include the fine-scale information. The final image contains both the micro and nano-meter images and can readily be used for various purposes.

中文翻译：

---

页岩样品的纳米级和多分辨率模型

摘要 页岩系统的表征需要不同尺度的成像。一个原因可能是由于不同的孔径分布。低分辨率图像通常覆盖大尺度结构，可用于样本的大区域。另一方面，精细图像通常覆盖的区域很小，它们主要用于发现页岩样品中纳米级孔隙内的复杂性。获取包含微米级和纳米级特征的大图像可能非常昂贵且耗时。在本文中，提出了一种在不同尺度上整合此类图像的新方法。目的是在粗略图像中包含纳米级信息。该方法的输入是一组粗略和精细的图像。使用相似度图确定粗略图像内每个细尺度图像的相应区域。然后，粗略图像被迭代地细化以包括细尺度信息。最终图像包含微米和纳米图像，可以很容易地用于各种目的。