This repository contains the Pore-Morphology Method (PMM) to simulate drainage process in porous media. For detailed methodology explanation see:

Tavakkoli, O., Ebadi, M., Da Wang, Y., Mostaghimi, P., Armstrong, R.T., 2025. "Assessment of wetting conditions in quasistatic drainage modeling using a pore morphology method and j-function wettability estimator." International Journal of Multiphase Flow 183:105067. doi:10.1016/j.ijmultiphaseflow.2024.105067

The code generates capillary-pressure curves by performing morphological operation on 3D segmented micro-CT images, using an adaptive, parallel kernel-size sweep and trapped wetting phase identification.

• Parallel processing with automatic halo handling (split-volume strategy).
• Adaptive kernel search to reach a target (starting) wetting-phase saturation.
• Support for starting kernel runs when a search is not required.
• Trapped wetting phase detection following the algorithm in the paper.

1. Python 3.9+ recommended.
2. Install dependencies:

• pip:

pip install -r requirements.txt

• conda:

conda create -n pmm -c conda-forge python=3.11 numpy scikit-image matplotlib seaborn -y
conda activate pmm

Example:

filename       = domain.raw        # path to the segmented micro-ct image
filesize_x     = 751               # voxels
filesize_y     = 751
filesize_z     = 572
resolution     = 8.42              # µm per voxel
sigma          = 26                # mN/m
theta          = 0                 # degrees
num_threads    = 12                # CPU cores to use

# Kernel–search options
kernel_search  = true              # true: search, false: starting kernel
starting_sat   = 0.95              # starting saturation if search is enabled
starting_kernel = 20               # used only if kernel_search = false
visualization  = true              # true: save .RAW fluid distribution per saturation step, false: skip saving

python PMM.py

If you use this implementation in academic work, please cite the paper above. A BibTeX entry is:

@article{Tavakkoli2025,
  title = {Assessment of wetting conditions in quasistatic drainage modeling using a pore morphology method and J-function wettability estimator},
  volume = {183},
  ISSN = {0301-9322},
  url = {http://dx.doi.org/10.1016/j.ijmultiphaseflow.2024.105067},
  DOI = {10.1016/j.ijmultiphaseflow.2024.105067},
  journal = {International Journal of Multiphase Flow},
  publisher = {Elsevier BV},
  author = {Tavakkoli,  Omid and Ebadi,  Mohammad and Da Wang,  Ying and Mostaghimi,  Peyman and Armstrong,  Ryan T.},
  year = {2025},
  month = feb,
  pages = {105067}
}