Direct updating of rock-physics properties using elastic full-waveform inversion

被引:0
|
作者
Hu, Qi [1 ]
Keating, Scott [1 ]
Innanen, Kristopher A. [1 ]
Chen, Huaizhen [2 ]
机构
[1] Univ Calgary, Dept Geosci, Calgary, AB T2N 1N4, Canada
[2] Tongji Univ, Sch Ocean & Earth Sci, Inst Adv Study, State Key Lab Marine Geol, Shanghai 200092, Peoples R China
基金
加拿大自然科学与工程研究理事会;
关键词
TRADE-OFF QUANTIFICATION; VARIATION-WITH-OFFSET; BOTTOM-CABLE DATA; JOINT ESTIMATION; LINEARIZED AVO; SEISMIC-WAVES; GAUSS-NEWTON; MEDIA; RESERVOIR; EXAMPLE;
D O I
10.1190/GEO2020-0199.1
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Quantitative estimation of rock-physics properties is an important part of reservoir characterization. Most current seismic workflows in this field are based on amplitude variation with offset. Building on recent work on high-resolution multiparameter inversion for reservoir characterization, we have constructed a rock-physics parameterized elastic full-waveform inversion (EFWI) scheme. Within a suitably formed multiparameter EFWI, in this case a 2D frequency-domain isotropic elastic full-waveform inversion with a truncated Gauss-Newton optimization, any rock-physics model with a well-defined mapping between its parameters and seismic velocity/density can be examined. We select a three-parameter porosity, clay content, and water saturation (PCS) parameterization, and we link them to elastic properties using three representative rock-physics models: the Han empirical model, the Voigt-Reuss-Hill boundary model, and the Kuster and Toksoz inclusion model. Numerical examples suggest that conditioning issues, which make a sequential inversion (in which velocities and density are first determined through EFWI, followed by PCS parameters) unstable, are avoided in this direct approach. Significant variability in inversion fidelity is visible from one rock-physics model to another. However, the response of the inversion to the range of possible numerical optimization and frequency selections, as well as acquisition geometries, varies widely. Water saturation tends to be the most difficult property to recover in all situations examined. This can be explained with radiation pattern analysis, in which very low relative scattering amplitudes from saturation perturbations are observed. An investigation performed with a Bayesian approach illustrates that the introduction of prior information may increase the inversion sensitivity to water saturation.
引用
收藏
页码:MR117 / MR132
页数:16
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