A Stable Q Compensated Reverse Time Migration Method Based on Excitation Amplitude Imaging Condition (Communications in Computational Physics, 2020)
The stability and efficiency, especially the stability, are generally concernedissues in Q compensated reverse time migration (Q-RTM). The instability occurs because of the exponentially boosted high frequency ambient noise during the forwardor backward seismic wavefield propagation. The regularization and low-pass filteringmethods are two effective strategies to control the instability of the wave propagation in Q-RTM. However, the regularization parameters are determined experimentally, and the wavefield cannot be recovered accurately. The low-pass filtering methodcannot balance the selection of cutoff frequency for varying Q values, and may damagethe effective signals, especially when the signal-to-noise ratio (SNR) of the seismic datais low, the Q-RTM will be a highly unstable process. In order to achieve the purposeof stability, the selection of cutoff frequency will be small enough, which can causegreat damage to the effective high frequency signals. In this paper, we present a stable Q-RTM algorithm based on the excitation amplitude imaging condition, which cancompensate both the amplitude attenuation and phase dispersion. Unlike the existing Q-RTM algorithms enlarging the amplitude, the exponentially attenuated seismicwavefield will be used during both the forward and backward wavefield propagationof Q-RTM. Therefore, the new Q-RTM algorithm is relative stable, even for the lowSNR seismic data. In order to show the accuracy and stability of our stable Q-RTMalgorithm clearly, an example based on Graben model will be illustrated. Then, a realistic BP gas chimney model further demonstrates that the proposed method enjoysgood stability and anti-noise performance compared with the traditional Q-RTM withamplitude amplification. Compare the Q-RTM images of these two models to the reference images obtained by the acoustic RTM with acoustic seismic data, the new Q-RTMresults match the reference images quite well. The proposed method is also testedusing a field seismic data, the result shows the effectiveness of our proposed method.