This work describes modern methods of parallelizing time consuming problems. Commonly used parallelization methods, such as OpenMP, MPI and GPUs, aimed to accelerate the solution of electromagnetic forward problems are revisited. Comparison of these technologies, their constraints and benefits for complex three-dimensional geoelectromagnetic field modeling are provided. An approach to configure the distributed computing system to solve most resource-intensive geoelectromagnetic problems is proposed. The problem of load balancing between computational nodes of the distributed computing system, advantages and disadvantages of different task orchestration approaches are considered. Different approaches on building fault tolerant systems to create a reliable one that will be capable of carrying out complex three-dimensional time consuming problems are discussed. The efficiency of the proposed method of distributed computing is shown on the example of solving 3D inverse problems for geoelectromagnetic survey with geoelectrical imaging of a medium with a complex structure. The structure and conductivity of the three layers located at different depths with varying lateral depth, thickness and conductivity was restored. Results of computational experiments show high computational efficiency of the proposed system and fault tolerance to both equipment failures and errors of computing software.