The application of optimized artificial neural network to refraction static correction

Optimized artificial neural network is used to pick refraction first arrival times, log and field refraction data are combined to inverse weathering layer velocity and refraction layer velocity, and Taner’s 3-D refraction static correction is applied in this paper. The result of real data shows that the work efficiency is enhanced by using Optimized artificial neural network to pick refraction first arrival times, the CMP gathers are stacked in phase and the ratio of S/N and transversal resolution of the stacked profile are improved.