Stochastic reconstruction of sandstones

Area of Science:

• Geology
• Materials Science
• Computational Modeling

Background:

• Understanding sandstone pore structure is crucial for subsurface applications like oil extraction and carbon sequestration.
• Stochastic modeling offers a way to represent complex geological formations.

Purpose of the Study:

• To develop a stochastic model of Berea and Fontainebleau sandstone pore structures using simulated annealing.
• To assess the accuracy of the generated models by comparing morphological and transport properties with experimental data.

Main Methods:

• Employed a simulated annealing algorithm to generate stochastic models.
• Prescribed two-point probability, lineal-path, and pore size distribution functions for model generation.
• Compared morphological quantities and mean survival time of random walkers between models and original sandstones.

Main Results:

• Rapid temperature decrease during annealing is necessary for isotropic and percolating configurations.
• Reconstructed models show good agreement in simple morphological quantities and random walker mean survival time.
• Local porosity analysis reveals potential significant differences in geometrical connectivity.

Conclusions:

• Simulated annealing can generate realistic sandstone pore models with accurate macroscopic properties.
• While overall structure is well-reproduced, fine-scale geometrical connectivity requires further investigation for precise representation.