3D reconstruction of porous media using MPS based on GPU

It is very important for the study of predicting fluids flowing mechanisms in porous media that the characteristics of porous media can be extracted in relatively smaller scales, and then are copied in a larger region to reconstruct 3D porous media. One of multiple-point statistics (MPS) method, the single normal equation simulation algorithm (SNESIM), has been widely used in reconstructing 3D porous media recently. However, owing to its large CPU cost and rigid memory demand, the application of SNESIM has been limited in some cases. To overcome this disadvantage, parallelization of SNESIM is performed on the compute unified device architecture (CUDA) kernels in the graphic processing unit (GPU) to acquire high-quality reconstruction with a low CPU cost. This parallel GPU-version 3D porous media reconstruction method only requires fixed and relatively small size memory and benefits from the tremendous calculating power given by CUDA kernels to shorten the CPU time, showing its high efficiency and a useful trend for the reconstruction of porous media compared with the former CPUversion reconstruction method.