Amplitude‐versus‐offset variations in gas sands

Geophysics ◽  
1989 ◽  
Vol 54 (6) ◽  
pp. 680-688 ◽  
Author(s):  
Steven R. Rutherford ◽  
Robert H. Williams
Keyword(s):  
Gulf Of Mexico ◽  
Normal Incidence ◽  
Arkoma Basin ◽  
Offshore Area ◽  
Amplitude Versus Offset ◽  
Wide Range ◽  
Class 1 ◽  
Two Factors ◽  
Seismic Reflections ◽  
Amplitude Versus

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.

Thin‐bed AVO: Compensating for the effects of NMO on reflectivity sequences

Geophysics ◽  
2001 ◽  
Vol 66 (6) ◽  
pp. 1714-1720 ◽  
Author(s):  
Alessandro Castoro ◽  
Roy E. White ◽  
Rhodri D. Thomas
Keyword(s):  
Normal Incidence ◽  
Wavelet Estimation ◽  
Avo Analysis ◽  
Seismic Wavelet ◽  
Amplitude Versus Offset ◽  
Nmo Correction ◽  
Fourier Spectra ◽  
Nmo Stretch ◽  
Amplitude Versus

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.

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
Keyword(s):  
Frequency Domain ◽  
Incident Angle ◽  
Normal Incidence ◽  
Frequency Dependent ◽  
Phase Reversal ◽  
Hard Rocks ◽  
Amplitude Versus Offset ◽  
Nondispersive Medium ◽  
Domain Phase ◽  
Amplitude Versus

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.

Incomplete AVO near salt structures

Geophysics ◽  
1992 ◽  
Vol 57 (4) ◽  
pp. 543-553 ◽  
Author(s):  
Christopher P. Ross
Keyword(s):  
Seismic Profiles ◽  
Spectral Modeling ◽  
Signal Degradation ◽  
Amplitude Versus Offset ◽  
Bright Spots ◽  
Close Proximity ◽  
Pseudo Spectral ◽  
Amplitude Versus ◽  
Structure Class ◽  
Made In

Amplitude versus offset (AVO) measurements for deep hydrocarbon‐bearing sands can be compromised when made in close proximity to a shallow salt piercement structure. Anomalous responses are observed, particularly on low acoustic impedance bright spots. CMP data from key seismic profiles traversing the bright spots do not show the expected Class 3 offset responses. On these CMPs, significant decrease of far trace energy is observed. CMP data from other seismic profiles off‐structure do exhibit the Class 3 offset responses, implying that structural complications may be interfering with the offset response. A synthetic AVO gather was generated using well log data, which supports the off‐structure Class 3 responses, further reinforcing the concept of structurally‐biased AVO responses. Acoustic, pseudo‐spectral modeling of the structure substantiates the misleading AVO response. Pseudo‐spectral modeling results suggest that signal degradation observed on the far offsets is caused by wavefield refraction—a shadow zone, where the known hydrocarbon‐bearing sands are not completely illuminated. Such shadow zones obscure the correct AVO response, which may have bearing on exploration and development.

scholarly journals Physical Transport Processes that Affect the Distribution of Oil in the Gulf of Mexico: Observations and Modeling

Oceanography ◽  
2021 ◽  
Vol 34 (1) ◽  
pp. 58-75
Author(s):  
Michel Boufadel ◽  
◽  
Annalisa Bracco ◽  
Eric Chassignet ◽  
Shuyi Chen ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Physical Environment ◽  
Large Scale ◽  
Transport Processes ◽  
Small Scale ◽  
Surface Mixed Layer ◽  
Physical Processes ◽  
Mixing Processes ◽  
Near Surface ◽  
Wide Range

Physical transport processes such as the circulation and mixing of waters largely determine the spatial distribution of materials in the ocean. They also establish the physical environment within which biogeochemical and other processes transform materials, including naturally occurring nutrients and human-made contaminants that may sustain or harm the region’s living resources. Thus, understanding and modeling the transport and distribution of materials provides a crucial substrate for determining the effects of biological, geological, and chemical processes. The wide range of scales in which these physical processes operate includes microscale droplets and bubbles; small-scale turbulence in buoyant plumes and the near-surface “mixed” layer; submesoscale fronts, convergent and divergent flows, and small eddies; larger mesoscale quasi-geostrophic eddies; and the overall large-scale circulation of the Gulf of Mexico and its interaction with the Atlantic Ocean and the Caribbean Sea; along with air-sea interaction on longer timescales. The circulation and mixing processes that operate near the Gulf of Mexico coasts, where most human activities occur, are strongly affected by wind- and river-induced currents and are further modified by the area’s complex topography. Gulf of Mexico physical processes are also characterized by strong linkages between coastal/shelf and deeper offshore waters that determine connectivity to the basin’s interior. This physical connectivity influences the transport of materials among different coastal areas within the Gulf of Mexico and can extend to adjacent basins. Major advances enabled by the Gulf of Mexico Research Initiative in the observation, understanding, and modeling of all of these aspects of the Gulf’s physical environment are summarized in this article, and key priorities for future work are also identified.

scholarly journals Crosswell Seismic Amplitude-Versus-Offset for Detailed Imaging of Facies and Fluid Distribution within Carbonate Oil Reservoirs

2008 ◽  
Author(s):  
Wayne Pennington ◽  
Mohamed Ibrahim ◽  
Roger Turpening ◽  
Sean Trisch ◽  
Josh Richardson ◽  
...  
Keyword(s):  
Oil Reservoirs ◽  
Fluid Distribution ◽  
Seismic Amplitude ◽  
Amplitude Versus Offset ◽  
Detailed Imaging ◽  
Amplitude Versus

scholarly journals QVOA Techniques for Estimation of Fracture Directions

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Vladimir Sabinin
Keyword(s):  
Quality Factor ◽  
Symmetry Axis ◽  
Factor Versus ◽  
Synthetic Data ◽  
Computational Techniques ◽  
High Quality ◽  
Amplitude Versus Offset ◽  
Target Layer ◽  
Analysis Quality ◽  
Amplitude Versus

Some new computational techniques are suggested for estimating symmetry axis azimuth of fractures in the viscoelastic anisotropic target layer in the framework of QVOA analysis (Quality factor Versus Offset and Azimuth). The different QVOA techniques are compared using synthetic viscoelastic surface reflected data with and without noise. I calculated errors for these techniques which depend on different sets of azimuths and intervals of offsets. Superiority of the high-order “enhanced general” and “cubic” techniques is shown. The high-quality QVOA techniques are compared with one of the high-quality AVOA techniques (Amplitude Versus Offset and Azimuth) in the synthetic data with noise and attenuation. Results are comparable.

High-resolution seismic velocity analysis by sign-based weighted semblance

Geophysics ◽  
2021 ◽  
pp. 1-35
Author(s):  
M. Javad Khoshnavaz
Keyword(s):  
Seismic Velocity ◽  
Resolution Enhancement ◽  
Synthetic Data ◽  
Correlation Coefficients ◽  
Velocity Model ◽  
Seismic Attenuation ◽  
Velocity Analysis ◽  
Velocity Models ◽  
Amplitude Versus Offset ◽  
Amplitude Versus

Building an accurate velocity model plays a vital role in routine seismic imaging workflows. Normal-moveout-based seismic velocity analysis is a popular method to make the velocity models. However, traditional velocity analysis methodologies are not generally capable of handling amplitude variations across moveout curves, specifically polarity reversals caused by amplitude-versus-offset anomalies. I present a normal-moveout-based velocity analysis approach that circumvents this shortcoming by modifying the conventional semblance function to include polarity and amplitude correction terms computed using correlation coefficients of seismic traces in the velocity analysis scanning window with a reference trace. Thus, the proposed workflow is suitable for any class of amplitude-versus-offset effects. The approach is demonstrated to four synthetic data examples of different conditions and a field data consisting a common-midpoint gather. Lateral resolution enhancement using the proposed workflow is evaluated by comparison between the results from the workflow and the results obtained by the application of conventional semblance and three semblance-based velocity analysis algorithms developed to circumvent the challenges associated with amplitude variations across moveout curves, caused by seismic attenuation and class II amplitude-versus-offset anomalies. According to the obtained results, the proposed workflow is superior to all the presented workflows in handling such anomalies.

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