Poroelastic analysis of frequency-dependent amplitude-versus-offset variations

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. C31-C40 ◽  
Author(s):  
Lanfeng Liu ◽  
Siyuan Cao ◽  
Lu Wang

Using analytic equations and numerical modeling, we have investigated characteristics of the frequency-dependent amplitude versus incident angle at an interface between a nondispersive medium and a patchy-saturated dispersive medium. For acoustically hard rocks, at normal incidence and smaller incident angles, the reflection magnitude increases when frequency increases, whereas in the amplitude versus incident-angle domain, the amplitude decreases with increasing incident angle (offset). For acoustically moderate to slightly hard rocks, phase reversal may occur when frequency increases from low to high. This type of response can happen in traditional amplitude-versus-offset class I and II reservoirs, but the frequency-domain phase reversal will be in different incident-angle ranges. For acoustically soft reservoirs, in amplitude versus incident-angle domain, the reflection magnitude increases with increasing incident angle. However, in amplitude-versus-frequency domain, the reflection magnitude increases when frequency decreases, which occurs in all investigated frequencies.

Geophysics ◽  
2000 ◽  
Vol 65 (1) ◽  
pp. 113-125 ◽  
Author(s):  
Xiaoxian Zeng ◽  
George A. McMechan ◽  
Tong Xu

To evaluate the importance of amplitude‐versus‐offset information in the interpretation of ground‐penetrating radar (GPR) data, GPR reflections are synthesized as a function of antenna separation using a 2.5-D finite‐difference solution of Maxwell’s equations. The conductivity, the complex dielectric permittivity, and the complex magnetic permeability are varied systematically in nine suites of horizontally layered models. The source used is a horizontal transverse‐electric dipole situated at the air‐earth interface. Cole‐Cole relaxation mechanisms define the frequency dependence of the media. Reflection magnitudes and their variations with antenna separation differ substantially, depending on the contrast in electromagnetic properties that caused the reflection. The spectral character of the dielectric and magnetic relaxations produces only second‐order variations in reflection coefficients compared with those associated with contrasts in permittivity, conductivity, and permeability, so they may not be separable even when they are detected. In typical earth materials, attenuation of propagating GPR waves is influenced most strongly by conductivity, followed by dielectric relaxation, followed by magnetic relaxation. A pervasive feature of the simulated responses is a locally high amplitude associated with the critical incident angle at the air‐earth interface in the antenna radiation pattern. Full wavefield simulations of two field data sets from a fluvial/eolian environment are able to reproduce the main amplitude behaviors observed in the data.


2016 ◽  
Vol 65 (3) ◽  
pp. 747-765 ◽  
Author(s):  
Zhaoyu Jin ◽  
Mark Chapman ◽  
Xiaoyang Wu ◽  
Giorgos Papageorgiou

Geophysics ◽  
1989 ◽  
Vol 54 (6) ◽  
pp. 680-688 ◽  
Author(s):  
Steven R. Rutherford ◽  
Robert H. Williams

Seismic reflections from gas sands exhibit a wide range of amplitude‐versus‐offset (AVO) characteristics. The two factors that most strongly determine the AVO behavior of a gas‐sand reflection are the normal incidence reflection coefficient [Formula: see text] and the contrast in Poisson’s ratio at the reflector. Of these two factors, [Formula: see text] is the least constrained. Based on their AVO characteristics, gas‐sand reflectors can be grouped into three classes defined in terms of [Formula: see text] at the top of the gas sand. Class 1 gas sands have higher impedance than the encasing shale with relatively large positive values for [Formula: see text]. Class 2 gas sands have nearly the same impedance as the encasing shale and are characterized by values of [Formula: see text] near zero. Class 3 sands have lower impedance than the encasing shale with negative, large magnitude values for [Formula: see text]. Each of these sand classes has a distinct AVO characteristic. An example of a gas sand from each of the three classes is presented in the paper. The Class 1 example involves a Hartshorn channel sand from the Arkoma Basin. The Class 2 example considers a Miocene gas sand from the Brazos offshore area of the Gulf of Mexico. The Class 3 example is a Pliocene gas sand from the High Island offshore area of the Gulf of Mexico.


2016 ◽  
Vol 174 (3) ◽  
pp. 1043-1059 ◽  
Author(s):  
Xiaohui Yang ◽  
Siyuan Cao ◽  
Quanshi Guo ◽  
Yonggan Kang ◽  
Pengfei Yu ◽  
...  

2014 ◽  
Vol 62 (6) ◽  
pp. 1224-1237 ◽  
Author(s):  
Xiaoyang Wu ◽  
Mark Chapman ◽  
Xiang-Yang Li ◽  
Patrick Boston

Geophysics ◽  
2001 ◽  
Vol 66 (6) ◽  
pp. 1714-1720 ◽  
Author(s):  
Alessandro Castoro ◽  
Roy E. White ◽  
Rhodri D. Thomas

Estimating the amplitude versus offset (AVO) gradient for thin beds is problematic because of offset‐dependent tuning and NMO stretch. When AVO analysis is carried out before NMO correction, the nonparallel nature of the NMO hyperbolas results in differential interference conditions at each offset and complicates AVO interpretation. If AVO analysis is carried out after NMO correction, the data bandwidth is distorted and corrections must be made to recover the true AVO response. A correction for NMO stretch can be applied to Fourier spectra obtained after windowing the NMO‐corrected prestack data. This approach requires knowledge of the seismic wavelet but seems to be relatively insensitive to noise in the data or uncertainties in the wavelet estimation. The technique allows the interference conditions to be made independent of offset and the correct AVO gradient relative to the normal incidence amplitude to be recovered.


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