In order to accurately detect the content of H2S trace gas in oil field, an on-line, real-time monitoring and analysis system for trace impurity gases, such as hydrogen sulfide(H2S) in oil field associated gas was designed, which can provide basis for the improvement and formulation of associated gas recovery and utilization technology in oil fields. The system was based on Tunable Laser Diode Spectroscopy(TDLAS) and Wavelength Modulation(WMS), using a tunable distributed feedback laser (DFB), lock-in amplifier, combined with a new Herriot chamber, InGaAs detector, to achieve the simultaneous on-line monitoring of H2S trace gases in oil field associated gas. To eliminate interference of background gases CH4 and other impurities in the gas, comparative experiments of RBF and BP neural network were carried out. A variety of H2S standard gas test systems with different concentrations were provided in the analog gas mixing station. The experimental results show that the interference of strong background gas, the detection limit for H2S is 1.2 ppm, in terms of interference, compared with the classical BP neural network, RBF neural network has a strong advantage, the prediction error is less than 10-10, the system had high detection accuracy and robustness, and strong application value in the field of oil gas detection.