Bayesian prestack seismic inversion with a self-adaptive Huber-Markov random-field edge protection scheme
Tian Yu-Kun1, Zhou Hui1, Chen Han-Ming1, Zou Ya-Ming1, and Guan Shou-Jun1
1. State Key Laboratory of Petroleum Resource and Prospecting, CNPC Key Lab of Geophysical Exploration, China University of Petroleum, Changping 102249, China.
Abstract：
Seismic inversion is a highly ill-posed problem, due to many factors such as the limited seismic frequency bandwidth and inappropriate forward modeling. To obtain a unique solution, some smoothing constraints, e.g., the Tikhonov regularization are usually applied. The Tikhonov method can maintain a global smooth solution, but cause a fuzzy structure edge. In this paper we use Huber-Markov random-field edge protection method in the procedure of inverting three parameters, P-velocity, S-velocity and density. The method can avoid blurring the structure edge and resist noise. For the parameter to be inverted, the Huber-Markov random-field constructs a neighborhood system, which further acts as the vertical and lateral constraints. We use a quadratic Huber edge penalty function within the layer to suppress noise and a linear one on the edges to avoid a fuzzy result. The effectiveness of our method is proved by inverting the synthetic data without and with noises. The relationship between the adopted constraints and the inversion results is analyzed as well.
TIAN Yu-Kun,ZHOU Hui,CHEN Han-Ming et al. Bayesian prestack seismic inversion with a self-adaptive Huber-Markov random-field edge protection scheme[J]. APPLIED GEOPHYSICS, 2013, 10(4): 453-460.
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2013, Vol. 10 
