Leakage monitoring is a safety measure for petroleum products in long-distance pipeline transportation. When testing the leakage monitoring software, although the leakage can be simulated by discharging from the pipeline, it is difficult to fully test the functions of this kind of software in terms of the content and cycle times due to the limitation of site conditions. A pipeline leakage simulation testing platform based on deep learning is designed and implemented. The actual operation data of the pipeline is used to train a pipeline segment model, and the typical pipeline operation procedure is made into a set of scenario templates. Combined with the simulation instructions developed in the project, various operation states of the long-distance pipeline, including leakage events, can be realistically simulated. The testing platform delivers the data to the system to be tested via standard communication protocols. The establishment of simulation testing platform enriches the testing methods of leakage monitoring software evaluation, which is safe and efficient, and allows unlimited repetition of testing cycles with lower costs. This study provides a new solution for testing leakage monitoring software in the pipeline industry.