We study the in situ measured distributions of contact angles and curvatures within mm-size X-ray tomography images of rock samples from a producing
hydrocarbon carbonate reservoir imaged after wateflooding . We analyse
their spatial correlation on a pore-by-pore basis using automated methods for
measuring contact angles , a new method for measuring curvatures, and by
performing pore network extraction using generalized network modeling . The
automated methods allow us to study image volumes of diameter approximately
1.92 mm and 1.2 mm long, obtaining hundreds of thousands of values from a
dataset with 435 million voxels. We calculate the capillary pressure based on
the mode curvature value, and associate this value with a nearby throat, or
restriction, in the pore space.
We demonstrate the capability of our methods to distinguish different wetta-
bility states in the samples studied: water-wet, mixed-wet, and weakly oil-wet.
The contact angle is spatially correlated over approximately the scale of an av-
erage pore. There is a wide distribution of contact angles within single pores. A
range of local curvature is found with both positive and negative values. How-
ever, there is only a weak correlation between contact angle and curvature with
lower and negative values of the curvature associated with larger contact an-
gles (more oil-wet conditions). We observed a weak correlation between average
contact angle and pore size, with the larger pores tending to be more oil-wet.
Our analysis could potentially have large implications for pore-scale modeling
of multiphase flow, in which methods using local curvature measurements could be directly used to calculate capillary pressures for displacement.
 Alhammadi A. M., AlRatrout A., Singh K., Bijeljic B., and Blunt M. J. In situ characterization of mixed-wettability in a reservoir rock at subsurface conditions. Scientific Reports, 7:10753, 2017. https://doi.org/10.1038/s41598-017-10992-w.
 AlRatrout A., Raeini A. Q., Bijeljic B., and Blunt M. J.
Automatic measurement of contact angle in pore-space images. Advances in Water Resources, 109:158–169, 2017. https://doi.org/10.1016/j.advwatres.2017.07.018.
 Raeini A. Q., Bijeljic B., and Blunt M. J. Generalized network modeling: Network extraction as a coarse-scale discretization of the void space of porous media. Physical Review E, 96:013312, 2017. https://doi.org/10.1103/PhysRevE.96.013312.
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