Seismic fluid identification using a nonlinear elastic impedance
inversion method based on a fast Markov chain Monte Carlo
method |
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Authors: | Guang-Zhi Zhang Xin-Peng Pan Zhen-Zhen Li Chang-Lu Sun and Xing-Yao Yin |
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Affiliation: | 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 |
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Abstract: | 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. |
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Keywords: | Elastic impedance Nonlinear inversion Fast
Markov chain Monte Carlo method Preconditioned
conjugate gradient algorithm Effective pore-fluid bulk
modulus |
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