Three-dimensional stochastic reconstruction of porous media: A systematic review

The reconstruction of porous materials is an important and meaningful issue in various engineering fields. In this paper, the reconstruction methods of porous materials proposed in the past few decades are systematically reviewed. Generally, the reconstruction methods are divided into two categories, namely interpolation-based reconstruction methods and stochastic reconstruction methods. The stochastic reconstruction methods can be further subdivided into 5 types, including Gaussian stochastic-field reconstruction method, Simulated annealing reconstruction method, Machine learning reconstruction method, Multiple-point stochastic reconstruction method and other stochastic reconstruction method. All these reconstuction methods are reviewed in this paper. Morevoer, the performance of these stochastic reconstruction methods in reconstructing different porous materials are compared with each other, the advantages and disadvantages of these methods in reconstructing different porous materials are also discussed, and several systematic conclusions are drawn in this paper. Finally, the main challenges for the future development of random reconstruction methods for porous materials are evaluated, and the future development direction of such methods is proposed.