A Multi-Radius LBP Method to Characterize the Geometry of Heterogeneous Shale Model.

The appropriate characterization of the geometrical structure for the heterogeneous shale sample is essential for digital rock classification. Local Binary Pattern (LBP) as a competitive method is widely used in characterizing geological models and measuring morphological similarity. Focusing on the local structures, the comparison between the central point and neighboring points plays an important role in LBP methods. However, one major limitation is to automatically define the radius of the neighborhood. In this work, we explore a multi-radius LBP method to improve characterization quality and simplify parameterization. The core idea is to calculate the importance of neighboring points according to the intrinsic characteristic of given images. A digitalized three-dimensional heterogeneous shale model is used to evaluate the proposed method. The experimental results verify that our method can effectively distinguish the different rock slices. In comparison with existing methods, the multi-radius LBP exhibits a better performance in terms of characterization accuracy.