Acoustic waves are mechanical waves that can be generated via vibrations. The use of such waves for enhancing flow and transport in porous media has some advantages over traditional enhanced recovery methods including eliminating bypassing effects and environmental hazards. Many physical mechanisms have been identified to improve recovery by applying an acoustic wave. However, the relative contributions of different mechanisms to the stimulated flow and transport phenomena are not still well understood. There are also uncertainties regarding the effects of important controlling factors such as frequency or the efficiency of different source coupling methods. In this work, a multiphysics model is developed to address the latter issues and propose a criterion to distinguish different regimes of acoustically induced effects. Simulation results of this model are correlated to the recovery enhancements to provide the required applied stress or supplied energy that causes observable changes in fluid flow behavior under laboratory conditions. A loss number of Nl is proposed based on the dimensionless analysis of wave equation in fluids where the most energy dissipation occurs. The critical values of Nl are obtained by implementing a classifier machine learning algorithm on a data set from the literature. When Nl is less than 2.1 × 10–7, the recovery enhancement is expected to be caused by mechanical effects, and therefore lower frequency (seismic) waves are favorable. At an Nl greater than 10–6, however, higher frequency (ultrasonic) waves are preferred since the changes in flow behavior are triggered by the adsorbed acoustic energy. In seismic excitations, coupling the source to the pore fluid gives the highest performance, while in ultrasonic treatments, the maximum viscosity reduction can be achieved when a transient frequency scenario is adopted. The results of this study give a better understanding of mechanisms behind the effect of acoustic wave application in porous media.