Pore scale modeling of multiphase flow in heterogeneously wet media

Date

2018-10-09

Authors

Verma, Rahul (Ph. D. in petroleum engineering)

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Abstract

Pore scale simulation has recently become an important tool for understanding multiphase flow behavior in porous materials. It enables detailed mechanistic studies of upscaled flow parameters such as capillary-pressure saturation curves, residual saturation of each phase, and relative permeability. However, direct modeling of multiphase flow given the complex solid surfaces in a porous medium is a non-trivial problem. In this work, we develop a new quasi-static, variational level set formulation capable of handling trapped phases as well as wettability. We extend our previous work [1, 2] for simple geometries, and develop a new parallelized code enabling application of the method in larger geometries. We compare our model results against several experimental and semi-analytical datasets. The model is first applied to both homogeneous and heterogeneously wet rhomboidal pores, and compared against semi-analytical solutions derived by Mason and Morrow [3]. Subsequently, we focus on a quasi-2D micromodel study of fluid-fluid displacement for different wettabilities, which is quantified using the displacement efficiency and fractal dimension of the displacement patterns [4]. We then study classic experiments by Haines [5] and Leverett [6] for measuring the capillary pressure and relative permeability curves in sphere packs and sandpacks, respectively. We match trends in trapping in sandpacks during drainage/imbibition experiments by Pentland et al. [7], and also compare it against predictions by several other pore-scale models. Finally, we confirm the pore-scale hypothesis suggested by DiCarlo et al. [8] for explaining experimental observations of three-phase relative permeability of the intermediate-wet phase in sandpack experiments. For these three-phase experiments, we propose an approximation based on finding phases trapped between constant curvature surfaces, using two-phase simulations. We demonstrate the versatility of our methods by applying it to these disparate experimental datasets, and suggest future applications of our work.

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