Building on the concepts of cohesion degree and local relaxation, we propose an integrated hierarchical equilibrium parallel finite-element reverse time migration (HEP-FE-RTM) algorithm, which is a fine-grained central processing unit (CPU) parallel computation method in two-level host-sub-processors mode. A single master process is responsible for data reading and controlling the progress of the calculation, while each subordinate process deals with a part of the depth domain space. This algorithm is able to achieve single source forward-modelling and inversion calculation using more than 2000 CPUs. On the premise of controlling iteration times for convergence, sub-module/processors only communicate with their adjacent counterparts and the host processor, so the level of data exchange is proportional to cohesion degree. This HEP-FE-RTM algorithm has the distinct advantage that parallel efficiency does not decrease as the number of processors increases. In two-level host-sub-processors mode, more than 2000 processors are used and one billion unknowns are solved. By combining the finite-element implicit dynamic Newmark integral scheme, this approach achieves a prestack reverse time migration (RTM) with high expansion. Making full use of the characteristics of high accuracy and strong boundary adaptability of the finite-element method, through the optimisation of finite-element solving, the HEP-FE-RTM algorithm improved the efficiency of parallel computing and achieved RTM implementation using finite element. Model tests show that this method has a significant effect on both imaging efficiency and accuracy.