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.
Highlights
Compared to amplitude versus offset (AVO) inversion based on common mid-point (CMP) gathers, elastic impedance inversion based on partial angle-stack gathersEdited by Jie Hao has the advantages of high computational efficiency, high stability, high noise immunity, and low dependence on the quality of seismic data
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
Compared to amplitude versus offset (AVO) inversion based on common mid-point (CMP) gathers, elastic impedance inversion based on partial angle-stack gathers & Xin-Peng Pan panxinpeng1990@gmail.com
Summary
Compared to amplitude versus offset (AVO) inversion based on common mid-point (CMP) gathers, elastic impedance inversion based on partial angle-stack gathers. Edited by Jie Hao has the advantages of high computational efficiency, high stability, high noise immunity, and low dependence on the quality of seismic data This has been widely used in reservoir fluid identification and detection, and has become one of the main directions of pre-stack inversion (Downton 2005; Yin et al 2014). Cambois (2000) considered that the high noise immunity of elastic impedance could avoid ‘‘leakage’’ between the various AVO attributes generated by noise This is more advantageous in the extraction of pre-stack parameters. On the basis of two-phase medium theory for elastic impedance equation, we extract the effective pore-fluid bulk modulus from seismic data to apply to reservoir fluid identification and detection (Russell et al 2003; Yin et al 2013a)
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