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Verifying Pore Network Models of Imbibition in Rocks Using Time‐Resolved Synchrotron Imaging
Author(s) -
Bultreys Tom,
Singh Kamaljit,
Raeini Ali Q.,
Ruspini Leonardo C.,
Øren PålEric,
Berg Steffen,
Rücker Maja,
Bijeljic Branko,
Blunt Martin J.
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 - 10.1029/2019wr026587
Subject(s) - imbibition , capillary action , overfitting , relative permeability , synchrotron , wetting , porous medium , scale (ratio) , mechanics , permeability (electromagnetism) , geology , porosity , capillary pressure , materials science , statistical physics , geotechnical engineering , computer science , physics , chemistry , artificial intelligence , artificial neural network , composite material , optics , biochemistry , botany , germination , quantum mechanics , membrane , biology
At the pore scale, slow invasion of a wetting fluid in porous materials is often modeled with quasi‐static approximations which only consider capillary forces in the form of simple pore‐filling rules. The appropriateness of this approximation, often applied in pore network models, is contested in the literature, reflecting the difficulty of predicting imbibition relative permeability with these models. However, validation by sole comparison to continuum‐scale experiments is prone to induce model overfitting. It has therefore remained unclear whether difficulties generalizing the model performance are caused by errors in the predicted filling sequence or by subsequent calculations. Here, we address this by examining whether such a model can predict the pore‐scale fluid distributions underlying the behavior at the continuum scale. To this end, we compare the fluid arrangement evolution measured in fast synchrotron micro‐CT experiments on two rock types to quasi‐static simulations which implement capillary‐dominated pore filling and snap‐off, including a sophisticated model for cooperative pore filling. The results indicate that such pore network models can, in principle, predict fluid distributions accurately enough to estimate upscaled flow properties of strongly wetted rocks at low capillary numbers.