A Review on Wettability Characterization from 3D Pore-Scale Images

Abstract Wettability, as represented by contact angles, impacts the multifluid configuration inside porous media, which determines the media’s upscaled behavior. An accurate description of the wettability is therefore crucial in determining and understanding macroscopic flow behavior, such as relative permeability and capillary pressure. Traditional experimental and numerical studies determine the aggregate wettability of a medium as a single parameter assigned to the whole sample. However, the wettability could vary spatially throughout the domain. Advances in micro-CT scanning have improved the capability to see the solid and fluid distribution inside porous media. This has led to more recent developments of different numerical methods to determine the wettability distribution based on segmented micro-CT images. This paper reviews different numerical methods for wettability characterization on three-dimensional (3D) pore-scale images of fluid distribution, concerning their methodology, accuracy, and computational cost where applicable. This study tries to cover all numerical methods for characterizing wettability distribution based on the segmented micro-CT images as of the time of this manuscript. We have divided the methods into six categories: geometry-, topology-, multiphase-, machine learning-, thermodynamic-, and event-based methods. Developments within each category are reviewed, and the different categories are compared. While no category stands out, as they all have different strengths and weaknesses, the geometry-based method tends to be most versatile and robust.