Some effects of velocity variation on AVO and its interpretation

Geophysics ◽  
1993 ◽  
Vol 58 (9) ◽  
pp. 1297-1300 ◽  
Author(s):  
Yu Xu ◽  
G. H. F. Gardner ◽  
J. A. McDonald
Keyword(s):  
Velocity Gradient ◽  
Poisson’S Ratio ◽  
Incident Angle ◽  
Elastic Parameter ◽  
Poisson's Ratio ◽  
Velocity Variation ◽  
Elastic Parameters ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Meaningful Relationship

In recent years interest has increased in the interpretation of the amplitude variation of reflected signals as a function of offset (AVO). A more meaningful relationship for interpreting reflection coefficients at the target horizon is amplitude variation with incident angle (AVA). The challenge is to convert from AVO to AVA. The effects of velocity variation in the overburden on amplitude variation with offset (AVO) and on the final inversion of AVO data into velocity, density, and Poisson’s ratio can be significant. Examples are given here for subsurface medium with a vertical velocity gradient range of [Formula: see text] to [Formula: see text]. When the medium is treated as homogeneous in the conversion from AVO to AVA, this velocity variation causes significant errors (about 10 percent) in both the gradient of AVA and in the normal incident reflection coefficient. Such errors produce errors of similar magnitude in the inversion of AVA data into the elastic parameters of velocity, Poisson’s ratio, and density. The errors depend on the velocity gradient, the offset range, the elastic parameter contrast across the interface, and the interface depth.

Implications of thin layers for amplitude variation with offset (AVO) studies

Geophysics ◽  
1993 ◽  
Vol 58 (8) ◽  
pp. 1200-1204 ◽  
Author(s):  
Christopher Juhlin ◽  
Roger Young
Keyword(s):  
Reflection Coefficient ◽  
Poisson’S Ratio ◽  
Thin Layers ◽  
Poisson's Ratio ◽  
Angle Of Incidence ◽  
Amplitude Variation ◽  
Seismic Reflection Data ◽  
Amplitude Variation With Offset ◽  
Rock Types ◽  
Gas Bearing

Amplitude variation with offset (AVO), or amplitude variation with angle (AVA), analyses of seismic reflection data are becoming increasingly popular in the exploration industry (Ostrander, 1984; Pichin and Mitchell, 1991; Mazzotti and Mirri, 1991) and also in scientific studies of the earth’s crust (Juhlin, 1990). In the exploration industry, AVO analyses are particularly suitable for the detection and mapping of gas zones since reservoirs often consist of shale with high Poisson’s ratio (high [Formula: see text]) overlying gas bearing sands with low Poisson’s ratio (low [Formula: see text]). If the gas sand has lower impedance than the overlying shale, the magnitude of the reflection coefficient will increase with increasing angle of incidence or offset. Other combinations of rock types will also show a similar increase in magnitude, such as shale over hard limestone, but the sign of the reflection coefficient will be positive in most of these cases. Therefore, if the polarity of the reflection can be determined to be negative and there is an increase in the absolute amplitude of the reflection with offset, then this is highly indicative of a gas bearing zone.

Information on elastic parameters obtained from the amplitudes of reflected waves

Geophysics ◽  
1995 ◽  
Vol 60 (5) ◽  
pp. 1426-1436 ◽  
Author(s):  
Wojciech Dȩbski ◽  
Albert Tarantola
Keyword(s):  
Mass Density ◽  
Seismic Velocities ◽  
Elastic Parameters ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Reflected Waves ◽  
Seismic Amplitude ◽  
Earth Models ◽  
Definition Of ◽  
Proper Analysis

Seismic amplitude variation with offset data contain information on the elastic parameters of geological layers. As the general solution of the inverse problem consists of a probability over the space of all possible earth models, we look at the probabilities obtained using amplitude variation with offset (AVO) data for different choices of elastic parameters. A proper analysis of the information in the data requires a nontrivial definition of the probability defining the state of total ignorance on different elastic parameters (seismic velocities, Lamé’s parameters, etc.). We conclude that mass density, seismic impedance, and Poisson’s ratio constitute the best resolved parameter set when inverting seismic amplitude variation with offset data.

Improving lateral and vertical resolution of seismic images by correcting for wavelet stretch in common-angle migration

Geophysics ◽  
2007 ◽  
Vol 72 (6) ◽  
pp. C95-C104 ◽  
Author(s):  
Gabriel Perez ◽  
Kurt J. Marfurt
Keyword(s):  
Signal To Noise Ratio ◽  
Incident Angle ◽  
Large Angle ◽  
Acoustic Medium ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Velocity Anisotropy ◽  
Time Migration ◽  
Reflection Angle ◽  
Seismic Reflections

Long-offset or high-incident-angle seismic reflections provide us with improved velocity resolution, better leverage against multiples, less contamination by ground roll, and information that is often critical when estimating lithology and fluid product. Unfortunately, high-incident-angle seismic reflections suffer not only from nonhyperbolic moveout but also from wavelet stretch during imaging, resulting in lower-resolution images that mix the response from adjacent lithologies. For an arbitrary acoustic medium, wavelet stretch from prestack migration depends only on the cosine of the reflection angle, such that the amount of wavelet stretch will be the same for all samples of a common-reflection-angle migrated trace. Thus, we are able to implement a wavelet stretch correction by applying a simple stationary spectral shaping operation to common-angle migrated traces. We obtain such traces directly by a prestack Kirchhoff migration algorithm. Correcting for stretch effectively increases the fold of imaged data, far beyond that achieved in conventional migration, resulting in improved signal-to-noise ratio of the final stacked section. Increasing the fidelity of large incident angles results in images with improved vertical and lateral resolution and with increased angular illumination, valuable for amplitude variation with angle (AVA) and amplitude variation with offset (AVO) analysis. Finally, such large-angle images are more sensitive to and therefore provide increased leverage over errors in velocity and velocity anisotropy. These ideas were applied to prestack time migration on seismic data from the Fort Worth basin, in Texas.

Factors facilitating or limiting the use of AVO for coal-bed methane

Geophysics ◽  
2006 ◽  
Vol 71 (4) ◽  
pp. C49-C56 ◽  
Author(s):  
Suping Peng ◽  
Huajing Chen ◽  
Ruizhao Yang ◽  
Yunfeng Gao ◽  
Xinping Chen
Keyword(s):  
Poisson’S Ratio ◽  
Poisson's Ratio ◽  
Coal Bed ◽  
Coal Bed Methane ◽  
Coal Seams ◽  
Amplitude Variation With Offset ◽  
Impedance Contrast ◽  
Reservoir Potential ◽  
Sweet Spots

There are similarities and differences in employing amplitude variation with offset (AVO) to explore for gas-sand reservoirs, as opposed to coal-bed methane (CBM) reservoirs. The main similarity is that large Poisson’s ratio contrasts, resulting in AVO gradient anomalies, are expected for both kinds of reservoirs. The main difference is that cleating and fracturing raise the Poisson’s ratio of a coal seam as it improves its reservoir potential for CBM, while gas always lowers the Poisson’s ratio of a sandstone reservoir. The top of gas sands usually has a negative AVO gradient, leading to a class one, two, or three anomaly depending on the impedance contrast with the overlying caprock. On the other hand, the top of a CBM reservoir has a positive AVO gradient, leading to a class four anomaly. Three environmental factors may limit the usage of AVO for CBM reservoirs: the smaller contrast in Poisson’s ratio between a CBM reservoir and its surrounding rock, variations in the caprock of a specific CBM reservoir, and the fact that CBM is not always free to collect at structurally high points in the reservoir. However, other factors work in favor of using AVO. The strikingly high reflection amplitude of coal improves signal/noise ratio and hence the reliability of AVO measurements. The relatively simple characteristics of AVO anomalies make them easy to interpret. Because faults are known to improve the quality of CBM reservoirs, faults accompanied by AVO anomalies would be especially convincing. A 3D-AVO example offered in this paper shows that AVO might be helpful to delineate methane-rich sweet spots within coal seams.

Elastic impedance parameterization and inversion with Young’s modulus and Poisson’s ratio

Geophysics ◽  
2013 ◽  
Vol 78 (6) ◽  
pp. N35-N42 ◽  
Author(s):  
Zhaoyun Zong ◽  
Xingyao Yin ◽  
Guochen Wu
Keyword(s):  
Parameter Estimation ◽  
Young’S Modulus ◽  
Seismic Data ◽  
Poisson’S Ratio ◽  
Young's Modulus ◽  
Incident Angle ◽  
P Wave ◽  
Poisson's Ratio ◽  
Data Set ◽  
Elastic Impedance

Young’s modulus and Poisson’s ratio are related to quantitative reservoir properties such as porosity, rock strength, mineral and total organic carbon content, and they can be used to infer preferential drilling locations or sweet spots. Conventionally, they are computed and estimated with a rock physics law in terms of P-wave, S-wave impedances/velocities, and density which may be directly inverted with prestack seismic data. However, the density term imbedded in Young’s modulus is difficult to estimate because it is less sensitive to seismic-amplitude variations, and the indirect way can create more uncertainty for the estimation of Young’s modulus and Poisson’s ratio. This study combines the elastic impedance equation in terms of Young’s modulus and Poisson’s ratio and elastic impedance variation with incident angle inversion to produce a stable and direct way to estimate the Young’s modulus and Poisson’s ratio, with no need for density information from prestack seismic data. We initially derive a novel elastic impedance equation in terms of Young’s modulus and Poisson’s ratio. And then, to enhance the estimation stability, we develop the elastic impedance varying with incident angle inversion with damping singular value decomposition (EVA-DSVD) method to estimate the Young’s modulus and Poisson’s ratio. This method is implemented in a two-step inversion: Elastic impedance inversion and parameter estimation. The introduction of a model constraint and DSVD algorithm in parameter estimation renders the EVA-DSVD inversion more stable. Tests on synthetic data show that the Young’s modulus and Poisson’s ratio are still estimated reasonable with moderate noise. A test on a real data set shows that the estimated results are in good agreement with the results of well interpretation.

scholarly journals Characterization of hydrocarbon reservoir by pore fluid and lithology using elastic parameters in an x field, Niger delta, Nigeria

2018 ◽  
Vol 6 (2) ◽  
pp. 173
Author(s):  
Akpabio . ◽  
Idara O ◽  
Ojo . ◽  
Odunayo T
Keyword(s):  
Wave Velocity ◽  
Niger Delta ◽  
Poisson’S Ratio ◽  
Velocity Ratio ◽  
Rock Physics ◽  
Pore Fluid ◽  
Poisson's Ratio ◽  
Oil Sand ◽  
Elastic Parameters ◽  
Hydrocarbon Reservoir

Quantitative rock physics analysis was carried out to determine the lithology and pore fluid of a reservoir in the Niger Delta. Density, compressional wave velocity and shear wave velocity logs were used as input to calculate elastic parameters such as velocity ratio, Poisson’s ratio, and Bulk Modulus, after estimating the hydrocarbon reservoir in the X field. The calculated velocity ratio log was used to differentiate between sand, sandstone and shale. Poisson’s ratio and velocity ratio were used delineate pore fluid content; gas sand, oil sand and sandstone formation from cross plot analysis. The reservoir in the field lies ranges from 9050 - 9426.5ft, (2760.25 – 2874.93m), this confirm what is obtained in the Niger Delta Basin. The Net Pay zones show an economical viable reservoir, it Net pay depth is 39 – 73.5ft. The Porosity and Permeability of the reservoirs suggested a productivity hydrocarbon reservoir. The reservoir lies between Gas sands, Oil sands and Brine sands, reservoir 2 and reservoir 3 are oil sand reservoirs while reservoir 1 lies between an oil sand and a brine sand.   

DFT study of SmXO3 (X = Al and Co) for elastic, mechanical and optical properties

2018 ◽  
Vol 32 (32) ◽  
pp. 1850362 ◽  
Author(s):  
A. Afaq ◽  
Abu Bakar ◽  
Sajid Anwar ◽  
Waheed Anwar ◽  
Fazal-e-Aleem
Keyword(s):  
Optical Properties ◽  
Poisson’S Ratio ◽  
Density Functional ◽  
Structural Parameters ◽  
Poisson's Ratio ◽  
Published Data ◽  
Generalized Gradient ◽  
Elastic Parameters ◽  
Functional Theory ◽  
Anisotropic Factor

The first-principles study of cubic perovskites SmXO3 (X = Al and Co) for elastic, mechanical and optical properties is done in the framework of density functional theory (DFT). Optimized structural parameters are obtained first to find mechanical and optical properties of the materials. These obtained structural parameters are in accordance with the published data. The cubic elastic parameters C[Formula: see text], C[Formula: see text] and C[Formula: see text] are then calculated by using generalized gradient approximation (GGA) as an exchange correlation functional in Kohn–Sham equations. Poisson’s ratio, shear modulus, Young’s modulus and anisotropic factor are deduced from these elastic parameters. These compounds are found to be elastically anisotropic and SmAlO3 is brittle while SmCoO3 is ductile. Their covalent nature is also discussed by using Poisson’s ratio. In addition, optical properties like absorption coefficient, extinction coefficient, energy loss function, dielectric function, refractive index, reflectivity and optical conductivity are studied. This study predicts that SmAlO3 and SmCoO3 are suitable for optoelectronic devices.

Sensitivity analysis of seismic reflectivity to partial gas saturation

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. C45-C57 ◽  
Author(s):  
Carmen T. Gomez ◽  
Robert H. Tatham
Keyword(s):  
Sensitivity Analysis ◽  
Shale Gas ◽  
Poisson’S Ratio ◽  
Essential Element ◽  
Elastic Parameter ◽  
Poisson's Ratio ◽  
Density Contrast ◽  
Water Contact ◽  
Gas Saturation ◽  
Seismic Reflectivity

We analyze the sensitivity of seismic reflectivity to contrasts in density, seismic propagation velocities, Poisson’s ratio, and gas saturation using the complete Zoeppritz equations. Sensitivities of reflection coefficients to each bulk elastic parameter are computed as the partial derivatives of the seismic reflectivities, relative to each parameter. The sensitivity of reflectivity to gas saturation is then calculated as the full derivative of the reflectivities with respect to gas saturation, assuming both a homogeneous and a patchy distribution of gas in the pore fluids. We compute sensitivities for a sealing shale/gas-sand interface and a gas-sand/wet-sand (gas-water contact, GWC) interface. For the SH-SH reflectivity, the effect of density contrast is strongest in the 30°–50° range of incidence angles for the fluid-fluid interface and at nearer offsets for the shale/gas-sand interface. P-SV reflectivity forthe fluid-fluid interfaces is more sensitive to density contrast in the range of angles of incidence from 30° to 60°. The overall response of P-SV reflectivity to gas saturation throughout all offsets is dominated by the Poisson’s ratio of the gas sand. In the case of P-P reflectivity, the sensitivity to gas saturation increases with increasing incidence angles. The sensitivity of P-SV reflectivity to gas saturation tends to be greatest in the 20°–40° range of incidence angles. For SH-SH reflectivity, the sensitivity to gas saturation for most offsets is controlled mainly by the density contrast, and the sensitivity to density decreases with increasing offset. There is still not a generally accepted seismic reflection method to discriminate commercial gas concentrations from low gas saturation. From the sensitivity analysis, we conclude that the use of P-SV or SH-SH amplitude variation with offset (AVO), integrated with the P-P AVO, will be an essential element in understanding this problem fully.

Sign in / Sign up

Export Citation Format

Share Document