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An Automatic In Situ Contact Angle Determination Based on Level Set Method
Author(s) -
Yang Jianhui,
Zhou Yingfang
Publication year - 2020
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2020wr027107
Subject(s) - contact angle , wetting , smoothing , scale (ratio) , multiphase flow , flow (mathematics) , function (biology) , line (geometry) , surface (topology) , set (abstract data type) , algorithm , level set (data structures) , computer science , materials science , geometry , mathematics , mechanics , artificial intelligence , physics , computer vision , quantum mechanics , evolutionary biology , composite material , biology , programming language
A novel level set‐based approach is presented to calculate in situ contact angle distribution, θ , from pore‐scale immiscible fluids and rock configuration directly imaged with micro‐computed tomography (micro‐CT) techniques. We first identify interfaces of the fluid‐fluid and fluid‐solid by their zero level set functions. This is accomplished by reinitializing the level set functions with a signed distance function. Then the three‐phase contact line is determined at the crossover of the two zero level set functions that represent the two interfaces. The normal vectors of both surfaces are calculated directly using the two level set functions, and the contact angle is found from the dot product of these vectors where they meet at the contact line. We first validated our newly proposed method for the semianalytically calculated fluid configurations in a 2‐D tube and then tested the algorithm on a synthetic spherical oil droplet residing on a tilted flat solid surface where the contact angle is analytically defined. It was then used to measure the in situ contact angle of droplets directly imaged by micro‐CT, and the results are compared with the manually and other available automatically measured results. Compared with other available automatic approaches, our approach is mathematically well defined, and it does not require any other complicated tuning procedures for surface smoothing. This proposed approach allow us to accurately characterize local in situ pore‐scale wettability, which is essential to model multiphase flow in porous media and eventually help us to design and assess optimal processes, such as hydrocarbon recovery and carbon dioxide storage.