Underwater acoustic imaging has been gaining popularity due to its ability to image in very turbid oceanic conditions. However, the complexity of conducting underwater experiments using expensive hardware is an infeasible solution and hence there is an importance of realistic simulation models to understand various underwater scenarios. The k-Wave toolbox models realistic underwater scenario for accurate object detection, image enhancement and classification. The advantage of k-Wave is that it offers precise and computationally effective simulation for acoustic imaging and has the advantage of modeling the 2D environment with the ability to assign the sound speed and medium density at pixel level, providing more accurate backscattered echoes for various sonar signal processing applications. However, modeling underwater scenarios requires large computational grids, resulting in huge storage memory and computation requirements resulting in limited usage of k-Wave for underwater scenarios. In this study, we propose an efficient multilayering technique for modelling underwater targets for acoustical 2D imaging using the k- Wave toolbox. It is observed that the time and memory taken was reduced by 21\% and 77.02\% when employing the proposed multi-layering technique when compared to the typical k- Wave simulations.