Abstract
Image-based pore-scale modeling is an important method to study
multiphase flow in permeable rocks. However, in many rocks, the pore
size distribution is so wide that it cannot be resolved in a single
pore-space image, typically acquired using micro-computed tomography
(micro-CT). Recent multi-scale models therefore incorporate sub-voxel
porosity maps, created by differential micro-CT imaging of a contrast
fluid in the pores. These maps delineate different microporous flow
zones in the model, which must be assigned petrophysical properties as
input. The uncertainty on the pore scale physics in these models is
therefore heightened by uncertainties on the representation of
unresolved pores, also called sub-rock typing. Here, we address this by
validating a multi-scale pore network model using a drainage experiment
imaged with differential micro-CT on an Estaillades limestone sample. We
find that porosity map-based sub-rock typing was unable to match the
micrometer-scale experimental fluid distributions. To investigate why,
we introduce a novel baseline sub-rock typing method, based on a 3D map
of the experimental capillary pressure function. By incorporating this
data, we successfully remove most of the sub-rock typing uncertainty
from the model, obtaining a close fit to the experimental fluid
distributions. Comparison between the two methods shows that in this
sample, the porosity map is poorly correlated to the multiphase flow
behavior of the microporosity. The validation method introduced in this
paper serves to separate and address the uncertainties in multi-scale
models, facilitating simulations in complex geological reservoir rocks
important for e.g. geological storage of CO2 and renewable energy.