Petroleum Science >2015,??Issue 3:??406-416 DOI: https://doi.org/10.1007/s12182-015-0046-5
Seismic fluid identification using a nonlinear elastic impedanceinversion method based on a fast Markov chain Monte Carlomethod Open?Access
文章信息
作者：Guang-Zhi Zhang,Xin-Peng Pan,Zhen-Zhen Li,Chang-Lu Sun and Xing-Yao Yin
作者單位：
School of Geosciences, China University of Petroleum (East China), Qingdao 266580, Shandong, China;School of Geosciences, China University of Petroleum (East China), Qingdao 266580, Shandong, China;School of Geosciences, China University of Petroleum (East China), Qingdao 266580, Shandong, China;School of Geosciences, China University of Petroleum (East China), Qingdao 266580, Shandong, China;School of Geosciences, China University of Petroleum (East China), Qingdao 266580, Shandong, China
投稿時間：2015-07-28
引用方式：Zhang, GZ., Pan, XP., Li, ZZ. et al. Pet. Sci. (2015) 12: 406. https://doi.org/10.1007/s12182-015-0046-5
文章摘要
Elastic impedance inversion with high efficiency
and high stability has become one of the main directions of
seismic pre-stack inversion. The nonlinear elastic impedance
inversion method based on a fast Markov chain Monte Carlo
(MCMC) method is proposed in this paper, combining
conventional MCMC method based on global optimization
with a preconditioned conjugate gradient (PCG) algorithm
based on local optimization, so this method does not depend
strongly on the initial model. It converges to the global
optimum quickly and efficiently on the condition that efficiency
and stability of inversion are both taken into consideration
at the same time. The test data verify the feasibility
and robustness of the method, and based on this method, we
extract the effective pore-fluid bulk modulus, which is
applied to reservoir fluid identification and detection, and
consequently, a better result has been achieved.
and high stability has become one of the main directions of
seismic pre-stack inversion. The nonlinear elastic impedance
inversion method based on a fast Markov chain Monte Carlo
(MCMC) method is proposed in this paper, combining
conventional MCMC method based on global optimization
with a preconditioned conjugate gradient (PCG) algorithm
based on local optimization, so this method does not depend
strongly on the initial model. It converges to the global
optimum quickly and efficiently on the condition that efficiency
and stability of inversion are both taken into consideration
at the same time. The test data verify the feasibility
and robustness of the method, and based on this method, we
extract the effective pore-fluid bulk modulus, which is
applied to reservoir fluid identification and detection, and
consequently, a better result has been achieved.
關鍵詞
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Elastic impedance Nonlinear inversion FastMarkov chain Monte Carlo method Preconditionedconjugate gradient algorithm Effective pore-fluid bulkmodulus