Since the pioneering work of Oren et al. 1998several attempts have been made to predict relative permeability curves with Digital Rock Physics (DRP) technique. However, the problem has proved more complex than what researchers have expected, and these attempts failed. One of the main issues was the high number of uncertain parameters especially for the wettability input and this gets worst in mixed-wet scenario as the number of parameters is higher than in water-wet and oil-wet cases. In fact, Sorbie and Skauge 2012 stated that wettability assignment is the most complex and least validated stage in DRP simulation work ow. Similarly, Bondino et al. 2013concluded that "genuine prediction" of multi-phase ow properties will remain not credible until important progress is achieved in the area of wettability characterization at the pore scale.In this work, we propose a pragmatic approach to tackle these problems. First, we parallelize our pore network simulator in order to achieve large scale PNM simulations. Then, we develop an innovative and fast anchoring experiment imaged by micro-CT scanner, that helps to determine several wettability parameters needed for the DRP simulation (including the fraction of oil-wet/water-wet pores, any spatial or radius correlation of oil wet pores…). This experiment also provides an estimation of macroscopic parameters that help to anchor our pore scale simulations and further reduce the uncertainty. In addition to help reducing the uncertainty of the simulation, this experiment provides a fast estimation of the wettability of the system. Images representing large volumes with low resolution are, rst, improved with Enhanced Super Resolution Generative Adversarial Networks (ESRGAN) to obtain a large image with high resolution. Then, a pore network is extracted, and TotalEnergies parallel pore network simulator is used for multiphase ow simulations considering the constraints from the anchoring experiment to reduce the uncertainty. Finally, we compare our simulations against high quality SCAL experiment performed inhouse and we assess the predictive power of our DRP work ow. Article HighlightsIn this paper, a new methodology to determine wettability input for pore scale simulation is developed.Wettability was characterized and found correlated to the radii of the pores and spatial correlation of wettability was observed. The pore scale simulation coupled with the wettability anchoring experiment was found to be able to predict the results of SCAL experiment performed on the same rock with the same uids.characterization Skauge 2012, Bondino et al. 2013) . DRP could also be criticized for computing properties on usually small rock volumes without proving that the Representative Elementary Volume (REV) for single phase and two-phase ow is reached or that the simulations are not dominated by nite size and boundary effects. In a previous work (Regaieg et al. 2022), we have used ESRGAN method in order to increase the resolution of our images and have large images with good resolution. We ha...

Since the pioneering work of Oren et al. 1998several attempts have been made to predict relative permeability curves with Digital Rock Physics (DRP) technique. However, the problem has proved more complex than what researchers have expected, and these attempts failed. One of the main issues was the high number of uncertain parameters especially for the wettability input and this gets worst in mixed-wet scenario as the number of parameters is higher than in water-wet and oil-wet cases. In fact, Sorbie and Skauge 2012 stated that wettability assignment is the most complex and least validated stage in DRP simulation workflow. Similarly, Bondino et al. 2013concluded that “genuine prediction” of multi-phase flow properties will remain not credible until important progress is achieved in the area of wettability characterization at the pore scale. In this work, we propose a pragmatic approach to tackle these problems. First, we parallelize our pore network simulator in order to achieve large scale PNM simulations. Then, we develop an innovative and fast anchoring experiment imaged by micro-CT scanner, that helps to determine several wettability parameters needed for the DRP simulation (including the fraction of oil-wet/water-wet pores, any spatial or radius correlation of oil wet pores…). This experiment also provides an estimation of macroscopic parameters that help to anchor our pore scale simulations and further reduce the uncertainty. In addition to help reducing the uncertainty of the simulation, this experiment provides a fast estimation of the wettability of the system. Images representing large volumes with low resolution are, first, improved with Enhanced Super Resolution Generative Adversarial Networks (ESRGAN) to obtain a large image with high resolution. Then, a pore network is extracted, and TotalEnergies parallel pore network simulator is used for multiphase flow simulations considering the constraints from the anchoring experiment to reduce the uncertainty. Finally, we compare our simulations against high quality SCAL experiment performed in-house and we assess the predictive power of our DRP workflow.