Wettability has a first order impact on transport of fluids through porous materials. As a consequence, wettability is determining the effective properties of a range of different porous media; everything from clothes to membranes for osmotic desalination. From an economic perspective, wetting in porous media is most important for oil recovery, where the wetting properties have large impact on how easily and fast the hydrocarbons can be recovered. Despite this economic importance, the understanding of wetting in porous media is still limited. Traditional measurements is conducted either outside the porous medium, for example on polished surfaces, or only effective properties of the porous medium are measured.
This project will develop methods for estimating wettability on the pore scale. These methods will be based on high-resolution X-ray chromatography images of the fluid distribution within the porous material. Based on such images, we will simulate the same fluid distribution to estimate wettability and its distribution within the porous medium. We will use lattice-Botlzmann simulations, where we iteratively change the pore-scale wetting properties to minimize the difference between simulation results and X-ray chromatography images. This will give us a pore-scale wettability description. This description will be linked to effective properties, such as multiphase transport of fluids through the pore structure. Traditionally, wettability has been viewed as a thermodynamic equilibrium between surface stresses. By examining wettability and its distributions within porous media, we can estimate the influence of other factors, such as fluid-fluid surface curvature. This project is based on open development, and codes developed through this project will be published and distributed under licenses for free software.
Wettability has a first order effect on multiphase flow in porous media, and is therefore essential for generating flow parameters needed for predictive reservoir modeling. Wettability knowledge is also important for a range of enhanced oil recovery techniques. Predictive pore scale modeling is an emerging technology, where the lattice-Boltzmann method (LBM) has proven especially well-suited for simulations directly on pore space images.
This project will extend current state-of-the-art LBM software to include options for wettability heterogeneities and alteration. We will examine that the wettability models reproduce contact angles and curvatures as expected from existing theories. A central task for this project is to develop a workflow for wettability characterization based on LB simulations directly on CT-images of the fluid distribution. We will iterate over different wettability distributions, where the distribution yielding minimal changes from the initial fluid distribution is assumed to best represent the actual wettability. This workflow is assumed to honor the capabilities and limitations of LB modeling.
The laboratory part of SSF PoreLab focus on development of new methods for experimental determination of wettability. This includes imaging of samples at different wetting conditions and at different saturation stages. Both development of methods and interpretation of results will have a strong benefit from the modelling capabilities suggested in this project.
This project will employ one PhD candidate and one postdoctoral fellow. Both will work at the department of Geoscience and Petroleum, with excellent computer resources and laboratory facilities. SFF PoreLab provides an interdisciplinary group of scientist with outstanding knowledge on flow in porous media. International partners represent leading environments on pore scale modeling.