Estimation of seismic local slope using Hilbert transform noise correction method

Abstract

In seismology, the local slope is essential for various seismic forward and inversion methods, including seismic migration imaging, seismic tomography, structure prediction, and other core seismic data processing methods. However, high-frequency random noise is unavoidable in real seismic data. Therefore, a robust estimation of event-slope attributes becomes important under high-frequency random noise. This research explores a robust and efficient method for estimating local slopes. The relationship between the frequency response of the Hilbert transform and Fourier transform is analyzed. The derivative operator constructed by the Hilbert transform can effectively weaken the effect on the energy enhancement of the high-frequency random noise. Minimizing the quadratic function of the proportionality factors was used to obtain the proportionality factors of the noise correction. Finally, the Hilbert transform and noise correction derived a new linear plane-wave destruction filter operator. The linear operator can effectively estimate the seismic events' local slope with high-frequency random noise. The calculation results of the numerical examples show that the linear plane-wave destruction filter estimation local slope method proposed in this study has high calculation accuracy and efficiency.