Seismic scattering inversion for multiple parameters of overburden-stressed isotropic media

Author:

Chen Fubin1,Zong Zhaoyun2,Yin Xingyao2

Affiliation:

1. China University of Petroleum (East China), State Key Laboratory of Deep Oil and Gas, Qingdao, China; Laoshan Laboratory, Qingdao, China and Curtin University, Centre for Exploration Geophysics, Perth, Australia..

2. China University of Petroleum (East China), State Key Laboratory of Deep Oil and Gas, Qingdao, China and Laoshan Laboratory, Qingdao, China..

Abstract

Subsurface reservoirs are compressed by overburden stress resulting from the gravity of overlying masses, and the resulting stress changes significantly affect the seismic reflection responses generated at the reservoir interfaces. Several exact reflection coefficient equations have been well established to delineate the role that in-situ stress plays in altering the energy transition and amplitude of seismic reflection responses. These exact equations, however, cannot be effectively used in practice due to their intricate formulations and the difficult geophysical estimation for the third-order elastic constants (3oECs) embedded in reflection coefficients. Based on the theories of nonlinear elasticity and elastic wave inverse scattering, we derive an approximate seismic reflection coefficient equation for overburden-stressed isotropic media in terms of the P-wave modulus, shear modulus, density and a defined stress-related parameter (SRP). The SRP is a combined quantity of elastic moduli, 3oECs and overburden stress, which can be naturally treated as a dimensionless stress-induced anisotropy parameter. Its inclusion effectively eliminates the need for 3oECs information when using our equation to estimate the desired reservoir properties from seismic observations. By comparing our equation to the exact one, we confirm its validity within the moderate-stress range. Then we introduce a Bayesian inversion approach incorporating the new reflection coefficient equation to estimate four model parameters. In our approach, the Cauchy and Gaussian distribution functions are used for the a priori probability and the likelihood distributions, respectively. The synthetic tests from two well-log datasets and a field example demonstrate that four parameters can be reasonably inverted using our approach with rather smooth initial models, which illustrates the feasibility of our inversion approach.

Publisher

Society of Exploration Geophysicists

Reference2 articles.

1. Aki, K., and P. G. Richards, 1980, Quantitative seismology: Theory and methods: W. H. Freeman & Co.

2. Asaka, M., 2018, Anisotropic AVO: Implications for reservoir characterization: The Leading

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