The three-dimensional high-resolution imaging of rock samples is the basis for pore-scale characterization of reservoirs. Micro X-ray computed tomography (µ-CT) is considered the most direct means of obtaining the three-dimensional inner structure of porous media without deconstruction. The micrometer resolution of µ-CT, however, limits its application in the detection of small structures such as nanochannels, which are critical for fluid transportation. An effective strategy for solving this problem is applying numerical reconstruction methods to improve the resolution of the µ-CT images. In this paper, a convolutional neural network reconstruction method is introduced to reconstruct high-resolution porous structures based on low-resolution µ-CT images and high-resolution scanning electron microscope (SEM) images. The proposed method involves four steps. First, a three-dimensional low-resolution tomographic image of a rock sample is obtained by µ-CT scanning. Next, one or more sections in the rock sample are selected for scanning by SEM to obtain high-resolution two-dimensional images. The high-resolution segmented SEM images and their corresponding low-resolution µ-CT slices are then applied to train a convolutional neural network (CNN) model. Finally, the trained CNN model is used to reconstruct the entire low-resolution three-dimensional µ-CT image. Because the SEM images are segmented and have a higher resolution than the µ-CT image, this algorithm integrates the super-resolution and segmentation processes. The input data are low-resolution µ-CT images, and the output data are high-resolution segmented porous structures. The experimental results show that the proposed method can achieve state-of-the-art performance. 相似文献
Acta Geochimica - Isotopic signature is a powerful tool to discriminate methane (CH4) source types and constrain regional and global scale CH4 budgets. Peatlands on the Qinghai-Tibetan Plateau are... 相似文献
It is universally known that residual soils behave very differently from sedimentary soils. While the latter is widely known as cross-anisotropic, little is known regarding the strength anisotropy of residual soils. This study presents how the inherent anisotropy affects the strength of natural granite residual soils under generalized conditions, where intact specimens were carefully prepared and sheared under triaxial compression, extension, simple shear, and hollow cylinder torsional shear tests. The strength of natural residual soil, in terms of ultimate stress ratio M and undrained shear strength Su, is found to be significantly anisotropic in a different way from normally consolidated clays with the maximum strength obtained under triaxial compression and the minimum under simple shear or at intermediate principal stress direction. As a result, the existing method failed to measure the anisotropy degree of the studied soil. Two parameters were proposed accordingly to quantify the anisotropic strength under general conditions, taking the special strength anisotropy pattern and cohesive-frictional nature of GRS into account. The proposed parameters enable the direct comparison of strength anisotropy among soils. This study serves as a data set to better understand residual soils regarding their anisotropic behaviors under generalized conditions. Although specific to granite residual soils in China, this study is expected to be more widely applicable to other weathered geomaterials.
When a seismic wave propagates through subsurface viscoelastic media, the formation absorbs the high-frequency energy of the seismic wave more strongly than the... 相似文献
AbstractA series of direct shear tests were performed on cement-admixed silty clay to investigate the effect of cement content and nano-magnesia (MgO) on its shear strength properties. For each normal stress, shear strength increased with cement content. However, an obvious increment in shear strength was achieved when the cement content was adjusted from 13% to 17%. Both cohesion and friction angle of cemented soil increased with cement content, and exponential function was adopted to correlate both the factors with cement content. For cement content of 10% investigated in this study, the optimum nano-MgO content was 10‰, wherein the cohesion could reach the peak value. The microstructure of the mixture revealed that the structure of the mixture was compacted for the optimum nano-MgO content. However, micro-cracks were formed when the amount of nano-MgO exceeded its optimum content. 相似文献