Data-Driven Attenuation Compensation Via a Shaping Regularization Scheme

Seismic prospecting is one of the most important geophysical survey methods to understand the earth's structure. Properly compensating the anelastic attenuation of seismic data help to clearly characterize the structure of subsurface. Inverse Q-filtering processing is one of the most efficient ways to compensate for anelastic attenuation caused by the earth's structure. Stability is the most challenging task in inverse Q-filtering processing. In this letter, we introduce a shaping regularization method to stabilize the amplitude compensation operator in the inverse Q-filtering. The stabilization operator can be used simultaneously with a phase correction operator. To further improve the robustness of our method to noise, we adopt an adaptive tapering window to control the compensation frequency components according to the frequency bandwidth of seismic data. These schemes can accentuate the attenuated amplitude through Q-filtering and improve the stability of our method to noise. To demonstrate the effectiveness of our method, we first apply it to synthetic examples and to a real seismic data. Both results illustrate that the proposed shaping regularization inverse Q-filtering is an efficient adaptive data-driven inverse Q-filtering method.