Dynamic imaging of multiphase flow through porous media using 4D cumulative reconstruction

This paper introduces an original application on reconstruction strategies for X-ray computed microtomography, enabling the observation of time-dependent changes that occur during multiphase flow. In general, by sparsely collecting radiographs, the reconstruction of the object is compromised. Optimizations can be achieved by combining specific characteristics of the dynamics with the acquisition. Herein, the proposed method relies on short random intervals in which no drastic changes occur in the sample to acquire as many radiographs as possible that constitute a reconstructible data set. As these intervals are unpredictable, the method tries to guarantee that the collected radiograph data during these specific intervals are enough to recover useful information about the dynamics. Simulations of a percolating fluid in a digital rock are used to replicate an X-ray computed microtomography experiment to test the proposed method. The results demonstrate the potential of the proposed strategy for imaging multiphase flow in porous media and how data collected during distinct events can be combined to enhance the reconstruction of frames of the percolation process.