Amplitude variation with incident angle inversion for fluid factor in the depth domain

Qianhao Sun, Zhaoyun Zong


The development of Pre−stack depth migration makes the imaging of the subsurface structure in the depth possible, which set a foun− dation for the study of amplitude variation with incident angle (AVA) inversion. This leads to the increasing demanding of the seismic inversion methods in the depth domain for guiding reservoir characterization. However, the conventional seismic inversion methods in the time domain are not suitable in the depth domain due to the seismic wavelet in the depth domain is depth−variant and depending on medium velocity. To address this issue, we proposed a pragmatic seismic inversion method for fluid factor in the depth domain with amplitude variation with incident angle gathers by using a true−depth wavelet on the process of seismic inversion. This wavelet is es− timated by converting the time wavelet to the depth wavelet with seismic velocity. To guide the fluid discrimination, the proposed method directly estimates the fluid factor from the pre−stack seismic data and all the process of the method is implemented in the depth domain. To deal with the weak nonlinearity induced by the velocity, the Bayesian inference, the prior information and model constraint are in− troduced in this seismic inversion method. Tests on synthetic data show that the fluid factor can be well estimated reasonably even with moderate noise. The field data example illustrates the feasibility and efficiency of the proposed method in application and the estimated fluid factor and shear modulus are in good agreement with the drilling results.


AVA inversion, Depth domain, Seismic wavelet in depth domain, Bayesian inference

Full Text:




Published by INGV, Istituto Nazionale di Geofisica e Vulcanologia - ISSN: 2037-416X