Imperial College London
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ProfessorMartinBlunt

Faculty of Engineering, Department of Earth Science & Engineering

Chair in Flow in Porous Media
 
 
 
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Contact

 

+44 (0)20 7594 6500m.blunt Website

 
 
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Location

 

2.38ARoyal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Raeini:2022:10.1016/j.advwatres.2022.104194,
author = {Raeini, AQ and Giudici, LM and Blunt, MJ and Bijeljic, B},
doi = {10.1016/j.advwatres.2022.104194},
journal = {Advances in Water Resources},
pages = {1--14},
title = {Generalized network modelling of two-phase flow in a water-wet and mixed-wet reservoir sandstone: Uncertainty and validation with experimental data},
url = {http://dx.doi.org/10.1016/j.advwatres.2022.104194},
volume = {164},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - We use a generalized pore network model in combination with image-based experiments to understand the parameters that control upscaled flow properties. The study is focued on water-flooding through a reservoir sandstone under water-wet and mixed-wet conditions. A set of sensitivity studies is presented to quantify the role of wettability, pore geometry, initial and boundary conditions as well as a selection of model parameters used in the computation of fluid volumes, curvatures and flow and electrical conductivities. We quantify the uncertainty in the model predictions, which match the measured relative permeability and capillary pressure within the uncertainty of the experiments. Our results show that contact angle, initial saturation, image quality and image processing algorithm are amongst the parameters which introduce the largest variance in the predictions of upscaled flow properties for both mixed-wet and water-wet conditions.
AU  - Raeini,AQ
AU  - Giudici,LM
AU  - Blunt,MJ
AU  - Bijeljic,B
DO  - 10.1016/j.advwatres.2022.104194
EP  - 14
PY  - 2022///
SN  - 0309-1708
SP  - 1
TI  - Generalized network modelling of two-phase flow in a water-wet and mixed-wet reservoir sandstone: Uncertainty and validation with experimental data
T2  - Advances in Water Resources
UR  - http://dx.doi.org/10.1016/j.advwatres.2022.104194
UR  - https://www.sciencedirect.com/science/article/pii/S0309170822000677?via%3Dihub
UR  - http://hdl.handle.net/10044/1/97068
VL  - 164
ER  -
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