The investigation of dynamically significant information in miscible displacement flow is conducted using a data-decomposition method based on dynamic mode decomposition (DMD). This is achieved by taking into account the numerical data produced by the nonlinear miscible viscous fingering in a two-dimensional porous medium. Using a low-dimensional representation of an approximation inter-snapshot map and its eigenvalues and eigenvectors, the exact-DMD generated flow information that characterized the data sequence’s dynamic processes. It is promising to apply DMD to miscible fingering in the setting of rectilinear flow. The structure of the most unstable mode is shown. The original numerical data and the recreated data from DMD are in perfect agreement.