Enhanced density estimation from prestack inversion of multicomponent seismic data

2010 ◽  
Vol 29 (10) ◽  
pp. 1220-1226 ◽  
Author(s):  
Gorka Garcia Leiceaga ◽  
Josimar Silva ◽  
Fredy Artola ◽  
Evelin Marquez ◽  
Joclean Vanzeler
Keyword(s):  
Density Estimation ◽  
Seismic Data ◽  
Prestack Inversion ◽  
Multicomponent Seismic

Elastic inverse scattering for fluid variation with time-lapse seismic data

Geophysics ◽  
2015 ◽  
Vol 80 (2) ◽  
pp. WA61-WA67 ◽  
Author(s):  
Zhaoyun Zong ◽  
Xingyao Yin ◽  
Guochen Wu ◽  
Zhiping Wu
Keyword(s):  
Shear Modulus ◽  
Inverse Scattering ◽  
Seismic Data ◽  
Scattering Theory ◽  
Time Lapse ◽  
Monitoring Data ◽  
Prestack Inversion ◽  
Fluid Factor ◽  
Reference Medium ◽  
The Difference

Elastic inverse-scattering theory has been extended for fluid discrimination using the time-lapse seismic data. The fluid factor, shear modulus, and density are used to parameterize the reference medium and the monitoring medium, and the fluid factor works as the hydrocarbon indicator. The baseline medium is, in the conception of elastic scattering theory, the reference medium, and the monitoring medium is corresponding to the perturbed medium. The difference in the earth properties between the monitoring medium and the baseline medium is taken as the variation in the properties between the reference medium and perturbed medium. The baseline and monitoring data correspond to the background wavefields and measured full fields, respectively. And the variation between the baseline data and monitoring data is taken as the scattered wavefields. Under the above hypothesis, we derived a linearized and qualitative approximation of the reflectivity variation in terms of the changes of fluid factor, shear modulus, and density with the perturbation theory. Incorporating the effect of the wavelet into the reflectivity approximation as the forward solver, we determined a practical prestack inversion approach in a Bayesian scheme to estimate the fluid factor, shear modulus, and density changes directly with the time-lapse seismic data. We evaluated the examples revealing that the proposed approach rendered the estimation of the fluid factor, shear modulus, and density changes stably, even with moderate noise.

Effects of oil‐water saturation on shear‐wave splitting in multicomponent seismic data

2007 ◽  
Author(s):  
Zhongping Qian ◽  
Xiang‐Yang Li ◽  
Mark Chapman ◽  
Yonggang Zhang ◽  
Yanguang Wang
Keyword(s):  
Shear Wave ◽  
Seismic Data ◽  
Water Saturation ◽  
Shear Wave Splitting ◽  
Multicomponent Seismic ◽  
Wave Splitting ◽  
Oil Water

2D anisotropic nonslant stack beam migration for multicomponent seismic data

2021 ◽  
Vol 14 (13) ◽  
Author(s):  
Jianguang Han ◽  
Zhiwei Liu ◽  
Yun Wang ◽  
Jiayong Yan ◽  
Bingluo Gu
Keyword(s):  
Seismic Data ◽  
Multicomponent Seismic
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