Paint workers are trained before they work in a field. The workers spray water instead of real paints on walls in practice, since the materials of painting are expensive. Trainees cannot measure the amount of sprayed water on surfaces, and obtain the experiences of the various properties of paints during the training sessions. As an alternative training, we present a simulation system of spray painting in a VR environment. The system can help a user to experience a realistic painting and allows users to evaluate their performance. The purpose of this study is to provide a trainee realistic painting experience in real-time as well as to represent the thickness of the deposited paint on the surface for evaluation of his performance. The Gaussian model is used for a painting model. It enables our system calculate the thickness of paints. For a painting simulation, we can use a particle system. However, the particle system is hardly implemented in real-time since it may have a lot of particles of paints in painting simulation. Therefore, we propose new heuristic algorithm for painting process. In our method, the particles are sampled a few rays. After we find the collision points of rays with an environment, we get the painted area using flood-fill searching method on the texture map. To enhance the accuracy of the painted area, we process additional steps which are a stage of expanding painting and a stage of removing blocked area. To verify that the Gaussian model is appropriate for a painting model, we compared it with a flat model and linear model. The result shows that errors of the Gaussian model are smaller than any others. We analyzed time complexity of our method, and measured execution time to verify that our system operates in real-time.