A new tracking approach of the seismic record event based on Kalman filtering and its performance analysis

In the field of seismic exploration, the Kalman filter is often used for deconvolution of seismic data in order to improve the resolution and signal-to-noise ratio of seismic records. Differently, a new system model of Kalman filter is established and used to track the event of seismic data in this paper. Events play an important role in many aspects such as judging underground media attributes, depth of interface and oil-gas condition. Few of the present methods for picking the event are related to the motion laws of seismic waves. Based on the time-distance equation of seismic reflected wave, the state equation and measurement equation for the Kalman filtering system for tracking the reflected event are constructed. And the new model involves several important physical quantities such as the arrival time of the seismic wavelet, the offset and the propagation velocity of the seismic wave. Then the filtering model and initialization for the Kalman filter are given. Finally the effects of various parameters on the performances of the Kalman filter are analyzed. The experimental results show that the proposed tracking system can work well in picking the seismic reflected event, which will provide a new solution for picking the seismic event.