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Large-Pore Network Simulations Coupled with Innovative Wettability Anchoring Experiment to Predict Relative Permeability of a Mixed-Wet Rock

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Abstract

Since the pioneering work of Oren et al. (SPE J 3(04):324–336, 1998), several 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 (Petrophysics 53(06):401–409, 2012) stated that wettability assignment is the most complex and least validated stage in the DRP simulation workflow. Similarly, Bondino et al. (54(6):538–546, 2013) concluded that “genuine prediction” of multiphase 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, etc.). 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.

Article Highlights

  • A new methodology to determine wettability input for pore-scale simulation was developed.

  • Direct and clear observations that wettability is correlated with the pore radii were made and mixed-wet small wettability model was observed.

  • Wettability spatial correlation was observed, and correlation length was measured.

  • Layer models in the PNM simulator were changed, and a historical modeling artifact was corrected. As a direct consequence, expected relative permeability trends after a change of wettability have been observed.

  • PNM simulator was parallelized for faster PNM simulations.

  • The pore-scale simulation coupled with the wettability anchoring experiment was found to be able to predict the results of a mixed-wet SCAL experiment performed on the same rock with the same fluids.

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Acknowledgements

The authors would like to thank TotalEnergies’ management for the authorization to publish this work. ICE imaging platform is acknowledged for the image acquisition.

Funding

The authors have not disclosed any funding.

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Authors and Affiliations

  1. TotalEnergies One Tech, Pau, France

    Mohamed Regaieg, Titly Farhana Faisal & Richard Rivenq

  2. MODIS, Pau, France

    Franck Nono

Authors
  1. Mohamed Regaieg
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  2. Franck Nono
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  3. Titly Farhana Faisal
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  4. Richard Rivenq
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Contributions

MR has developed and parallelized the PNM simulator. FN has performed the wettability anchoring experiment. MR  and TFF have analyzed the wettability anchoring experiment and performed the simulations. RR has contributed to the analysis of the results.

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Correspondence to Mohamed Regaieg.

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The authors would like to mention that a patent about the wettability input determination has been filed: Regaieg, M., Brugidou, R., & Nono, F.: “A porous sample wettability parameter determining method and related system” (US Patent No. 63/342,923) filed on 17th May 2022.

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Regaieg, M., Nono, F., Faisal, T.F. et al. Large-Pore Network Simulations Coupled with Innovative Wettability Anchoring Experiment to Predict Relative Permeability of a Mixed-Wet Rock. Transp Porous Med 147, 495–517 (2023). https://doi.org/10.1007/s11242-023-01921-9

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