Amplitude variation with offset inversion using the reflectivity method

Geophysics ◽  
2016 ◽  
Vol 81 (4) ◽  
pp. R185-R195 ◽  
Author(s):  
Hongxing Liu ◽  
Jingye Li ◽  
Xiaohong Chen ◽  
Bo Hou ◽  
Li Chen
Keyword(s):  
Wave Velocity ◽  
P Wave ◽  
Transmission Losses ◽  
Amplitude Variation ◽  
Data Set ◽  
Amplitude Variation With Offset ◽  
Avo Inversion ◽  
Propagation Effects ◽  
Reflectivity Method ◽  
Internal Multiples

Most existing amplitude variation with offset (AVO) inversion methods are based on the Zoeppritz’s equation or its approximations. These methods assume that the amplitude of seismic data depends only on the reflection coefficients, which means that the wave-propagation effects, such as geometric spreading, attenuation, transmission loss, and multiples, have been fully corrected or attenuated before inversion. However, these requirements are very strict and can hardly be satisfied. Under a 1D assumption, reflectivity-method-based inversions are able to handle transmission losses and internal multiples. Applications of these inversions, however, are still time-consuming and complex in computation of differential seismograms. We have evaluated an inversion methodology based on the vectorized reflectivity method, in which the differential seismograms can be calculated from analytical expressions. It is computationally efficient. A modification is implemented to transform the inversion from the intercept time and ray-parameter domain to the angle-gather domain. AVO inversion is always an ill-posed problem. Following a Bayesian approach, the inversion is stabilized by including the correlation of the P-wave velocity, S-wave velocity, and density. Comparing reflectivity-method-based inversion with Zoeppritz-based inversion on a synthetic data and a real data set, we have concluded that reflectivity-method-based inversion is more accurate when the propagation effects of transmission losses and internal multiples are not corrected. Model testing has revealed that the method is robust at high noise levels.

Constrained nonlinear amplitude variation with offset inversion using Zoeppritz equations

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. R245-R255 ◽  
Author(s):  
Ali Gholami ◽  
Hossein S. Aghamiry ◽  
Mostafa Abbasi
Keyword(s):  
Nonlinear Equations ◽  
Wave Velocity ◽  
Seismic Data ◽  
P Wave ◽  
Simultaneous Estimation ◽  
Model Parameters ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Zoeppritz Equations ◽  
Avo Inversion

The inversion of prestack seismic data using amplitude variation with offset (AVO) has received increased attention in the past few decades because of its key role in estimating reservoir properties. AVO is mainly governed by the Zoeppritz equations, but traditional inversion techniques are based on various linear or quasilinear approximations to these nonlinear equations. We have developed an efficient algorithm for nonlinear AVO inversion of precritical reflections using the exact Zoeppritz equations in multichannel and multi-interface form for simultaneous estimation of the P-wave velocity, S-wave velocity, and density. The total variation constraint is used to overcome the ill-posedness while solving the forward nonlinear model and to preserve the sharpness of the interfaces in the parameter space. The optimization is based on a combination of Levenberg’s algorithm and the split Bregman iterative scheme, in which we have to refine the data and model parameters at each iteration. We refine the data via the original nonlinear equations, but we use the traditional cost-effective linearized AVO inversion to construct the Jacobian matrix and update the model. Numerical experiments show that this new iterative procedure is convergent and converges to a solution of the nonlinear problem. We determine the performance and optimality of our nonlinear inversion algorithm with various simulated and field seismic data sets.

Shear‐wave velocity and density estimation from PS-wave AVO analysis: Application to an OBS dataset from the North Sea

Geophysics ◽  
2000 ◽  
Vol 65 (5) ◽  
pp. 1446-1454 ◽  
Author(s):  
Side Jin ◽  
G. Cambois ◽  
C. Vuillermoz
Keyword(s):  
Wave Velocity ◽  
North Sea ◽  
Random Noise ◽  
P Wave ◽  
S Wave ◽  
Data Set ◽  
Avo Analysis ◽  
The North ◽  
Avo Inversion ◽  
The North Sea

S-wave velocity and density information is crucial for hydrocarbon detection, because they help in the discrimination of pore filling fluids. Unfortunately, these two parameters cannot be accurately resolved from conventional P-wave marine data. Recent developments in ocean‐bottom seismic (OBS) technology make it possible to acquire high quality S-wave data in marine environments. The use of (S)-waves for amplitude variation with offset (AVO) analysis can give better estimates of S-wave velocity and density contrasts. Like P-wave AVO, S-wave AVO is sensitive to various types of noise. We investigate numerically and analytically the sensitivity of AVO inversion to random noise and errors in angles of incidence. Synthetic examples show that random noise and angle errors can strongly bias the parameter estimation. The use of singular value decomposition offers a simple stabilization scheme to solve for the elastic parameters. The AVO inversion is applied to an OBS data set from the North Sea. Special prestack processing techniques are required for the success of S-wave AVO inversion. The derived S-wave velocity and density contrasts help in detecting the fluid contacts and delineating the extent of the reservoir sand.

Two-step joint PP- and PS-wave three-term amplitude-variation with offset inversion

2016 ◽  
Vol 4 (4) ◽  
pp. T613-T625 ◽  
Author(s):  
Qizhen Du ◽  
Bo Zhang ◽  
Xianjun Meng ◽  
Chengfeng Guo ◽  
Gang Chen ◽  
...  
Keyword(s):  
Reflection Coefficient ◽  
Wave Reflection ◽  
Coefficient Matrix ◽  
P Wave ◽  
Inversion Method ◽  
S Wave ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Avo Inversion ◽  
Pp Wave

Three-term amplitude-variation with offset (AVO) inversion generally suffers from instability when there is limited prior geologic or petrophysical constraints. Two-term AVO inversion shows higher instability compared with three-term AVO inversion. However, density, which is important in the fluid-type estimation, cannot be recovered from two-term AVO inversion. To reliably predict the P- and S-waves and density, we have developed a robust two-step joint PP- and PS-wave three-term AVO-inversion method. Our inversion workflow consists of two steps. The first step is to estimate the P- and S-wave reflectivities using Stewart’s joint two-term PP- and PS-AVO inversion. The second step is to treat the P-wave reflectivity obtained from the first step as the prior constraint to remove the P-wave velocity related-term from the three-term Aki-Richards PP-wave approximated reflection coefficient equation, and then the reduced PP-wave reflection coefficient equation is combined with the PS-wave reflection coefficient equation to estimate the S-wave and density reflectivities. We determined the effectiveness of our method by first applying it to synthetic models and then to field data. We also analyzed the condition number of the coefficient matrix to illustrate the stability of the proposed method. The estimated results using proposed method are superior to those obtained from three-term AVO inversion.

Amplitude variation with offset inversion using acoustic-elastic local solver

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. R251-R262 ◽  
Author(s):  
Ligia Elena Jaimes-Osorio ◽  
Alison Malcolm ◽  
Ali Gholami
Keyword(s):  
Elastic Material ◽  
Point Sources ◽  
P Wave ◽  
Reflection Coefficients ◽  
Local Domain ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Zoeppritz Equations ◽  
Avo Inversion ◽  
Full Domain

Conventional amplitude variation with offset (AVO) inversion analysis uses the Zoeppritz equations, which are based on a plane-wave approximation. However, because real seismic data are created by point sources, wave reflections are better modeled by spherical waves than by plane waves. Indeed, spherical reflection coefficients deviate from planar reflection coefficients near the critical and postcritical angles, which implies that the Zoeppritz equations are not applicable for angles close to critical reflection in AVO analysis. Elastic finite-difference simulations provide a solution to the limitations of the Zoeppritz approximation because they can handle near- and postcritical reflections. We have used a coupled acoustic-elastic local solver that approximates the wavefield with high accuracy within a locally perturbed elastic subdomain of the acoustic full domain. Using this acoustic-elastic local solver, the local wavefield generation and inversion are much faster than performing a full-domain elastic inversion. We use this technique to model wavefields and to demonstrate that the amplitude from within the local domain can be used as a constraint in the inversion to recover elastic material properties. Then, we focus on understanding how much the amplitude and phase contribute to the reconstruction accuracy of the elastic material parameters ([Formula: see text], [Formula: see text], and [Formula: see text]). Our results suggest that the combination of amplitude and phase in the inversion helps with the convergence. Finally, we analyze elastic parameter trade-offs in AVO inversion, from which we find that to recover accurate P-wave velocities we should invert for [Formula: see text] and [Formula: see text] simultaneously with fixed density.

Fracture-porosity inversion from P-wave AVOA data along 2D seismic lines: An example from the Austin Chalk of southeast Texas

Geophysics ◽  
2007 ◽  
Vol 72 (1) ◽  
pp. B1-B7 ◽  
Author(s):  
Abdullatif A. Al-Shuhail
Keyword(s):  
Aspect Ratio ◽  
Wave Velocity ◽  
P Wave ◽  
S Wave ◽  
Amplitude Variation ◽  
Fracture Porosity ◽  
Amplitude Variation With Offset ◽  
P Wave Velocity ◽  
Austin Chalk ◽  
Southeast Texas

Vertical aligned fractures can significantly enhance the horizontal permeability of a tight reservoir. Therefore, it is important to know the fracture porosity and direction in order to develop the reservoir efficiently. P-wave AVOA (amplitude variation with offset and azimuth) can be used to determine these fracture parameters. In this study, I present a method for inverting the fracture porosity from 2D P-wave seismic data. The method is based on a modeling result that shows that the anisotropic AVO (amplitude variation with offset) gradient is negative and linearly dependent on the fracture porosity in a gas-saturated reservoir, whereas the gradient is positive and linearly dependent on the fracture porosity in a liquid-saturated reservoir. This assumption is accurate as long as the crack aspect ratio is less than 0.1 and the ratio of the P-wave velocity to the S-wave velocity is greater than 1.8 — two conditions that are satisfied in most naturally fractured reservoirs. The inversion then uses the fracture strike, the crack aspect ratio, and the ratio of the P-wave velocity to the S-wave velocity to invert the fracture porosity from the anisotropic AVO gradient after inferring the fluid type from the sign of the anisotropic AVO gradient. When I applied this method to a seismic line from the oil-saturated zone of the fractured Austin Chalk of southeast Texas, I found that the inversion gave a median fracture porosity of 0.21%, which is within the fracture-porosity range commonly measured in cores from the Austin Chalk.

Bayesian linearized AVO inversion

Geophysics ◽  
2003 ◽  
Vol 68 (1) ◽  
pp. 185-198 ◽  
Author(s):  
Arild Buland ◽  
Henning Omre
Keyword(s):  
Wave Velocity ◽  
Posterior Distribution ◽  
Acoustic Impedance ◽  
Velocity Ratio ◽  
P Wave ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
S Wave ◽  
Data Set ◽  
Avo Inversion

A new linearized AVO inversion technique is developed in a Bayesian framework. The objective is to obtain posterior distributions for P‐wave velocity, S‐wave velocity, and density. Distributions for other elastic parameters can also be assessed—for example, acoustic impedance, shear impedance, and P‐wave to S‐wave velocity ratio. The inversion algorithm is based on the convolutional model and a linearized weak contrast approximation of the Zoeppritz equation. The solution is represented by a Gaussian posterior distribution with explicit expressions for the posterior expectation and covariance; hence, exact prediction intervals for the inverted parameters can be computed under the specified model. The explicit analytical form of the posterior distribution provides a computationally fast inversion method. Tests on synthetic data show that all inverted parameters were almost perfectly retrieved when the noise approached zero. With realistic noise levels, acoustic impedance was the best determined parameter, while the inversion provided practically no information about the density. The inversion algorithm has also been tested on a real 3‐D data set from the Sleipner field. The results show good agreement with well logs, but the uncertainty is high.

An Artificial Immune Algorithm and its Application in AVO Inversion

2012 ◽  
Vol 268-270 ◽  
pp. 1779-1782
Author(s):  
Hai Yan Zhang ◽  
Zi Li Liu
Keyword(s):  
Global Optimization ◽  
Wave Amplitude ◽  
Immune Algorithm ◽  
P Wave ◽  
Initial Population ◽  
Artificial Immune ◽  
Amplitude Variation ◽  
Artificial Immune Algorithm ◽  
Amplitude Variation With Offset ◽  
Avo Inversion

An improved artificial immune algorithm is proposed for geophysical P-wave amplitude variation with offset (AVO) inversion. In this paper, the algorithm is described and implemented. The orthogonal crossover is used to generate the initial population and the elitist-crossover is adopted to add the good patterns of the population. The hybrid mutation method is presented to increase the ability of local and global optimization. The improved immune algorithm is then applied to earth interface models of Mexican gulf for AVO inversion. The experimental results show that the improved algorithm is of high precision than the traditional immune algorithm.

Interpreting azimuthal Fourier coefficients for anisotropic and fracture parameters

2015 ◽  
Vol 3 (3) ◽  
pp. ST9-ST27 ◽  
Author(s):  
Jonathan E. Downton ◽  
Benjamin Roure
Keyword(s):  
Fourier Coefficients ◽  
P Wave ◽  
Amplitude Variation ◽  
Data Set ◽  
Amplitude Variation With Offset ◽  
Fracture Parameters ◽  
Isotropic Media ◽  
Transverse Isotropic ◽  
Axis Of Symmetry ◽  
Vertical Fractures

Amplitude variation with offset and azimuth (AVOAz) analysis can be separated into two separate parts: amplitude variation with offset (AVO) analysis and amplitude variation with azimuth (AVAz) analysis. Useful information about fractures and anisotropy can be obtained just by examining the AVAz. The AVAz can be described as a sum of sinusoids of different periodicities, each characterized by its magnitude and phase. This sum is mathematically equivalent to a Fourier series, and hence the coefficients describing the AVAz response are azimuthal Fourier coefficients (FCs). This FC parameterization is purely descriptive. The aim of this paper is to help the interpreter understand what these coefficients mean in terms of anisotropic and fracture parameters for the case of P-wave reflectivity using a linearized approximation. The FC representation is valid for general anisotropy. However, to gain insight into the significance of FCs, more restrictive assumptions about the anisotropy or facture system must be assumed. In the case of transverse isotropic media with a horizontal axis of symmetry, the P-wave reflectivity linearized approximation may be rewritten in terms of azimuthal FCs with the magnitude and phase of the different FCs corresponding to traditional AVAz attributes. Linear slip theory is used to show that the FCs can be interpreted similarly for the cases of a single set of parallel vertical fractures in isotropic media and in transverse isotropic media with a vertical axis of symmetry (VTI). The magnitude of the FCs depends on the fracture weakness parameters and the background media. For the case of vertical fractures in a VTI background, the AVOAz inverse problem is underdetermined, so extra information must be incorporated to determine how the weights are modified due to this background anisotropy. We evaluated this on a 3D data set from northwest Louisiana for which the main target was the Haynesville shale.

Wave propagation effects on amplitude variation with offset measurements: A modeling study

Geophysics ◽  
1993 ◽  
Vol 58 (4) ◽  
pp. 534-543 ◽  
Author(s):  
Ruben D. Martinez
Keyword(s):  
Wave Propagation ◽  
Synthetic Seismograms ◽  
Inverse Filtering ◽  
Transmission Losses ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Propagation Effects ◽  
Converted Waves ◽  
Inelastic Attenuation ◽  
Modeling Study

Wave propagation effects can significantly affect amplitude variation with offset (AVO) measurements. These effects include spreading losses, transmission losses, interbed multiples, surface multiple reflections, P‐SV mode converted waves and inelastic attenuation. Examination of prestack elastic synthetic seismograms suggests that spreading losses and the transmission losses plus compressional interbed multiples are manifest mainly as a time and offset effect on the primary reflections. The surface related multiples and the P‐SV mode‐converted waves interfere with prestack amplitudes inducing distortions in the AVO pattern. Such distortions cause large variances in AVO model fitting. Prestack viscoelastic synthetic seismograms also suggest that inelastic attenuation further complicates the AVO response because of the offset and time variant amplitude decay effects and the phase change due to dispersion. Together, all these effects severely alter AVO behavior and result in serious errors in AVO parameter estimates being made from inadequately corrected seismograms. This modeling study suggests that time and offset dependent data processing prior to AVO analysis would be necessary to correct for the wave propagation effects, via either inverse filtering or model based approaches. Comparisons between acoustic and elastic synthetic seismograms show that corrections for the wave propagation effects derived using acoustic approximations are inadequate. Corrections need to be calculated based on elastic approximations provided that the inelastic attenuation effects have been previously removed.

Fracture characterization at Valhall: Application of P‐wave amplitude variation with offset and azimuth (AVOA) analysis to a 3D ocean‐bottom data set

Geophysics ◽  
2003 ◽  
Vol 68 (4) ◽  
pp. 1150-1160 ◽  
Author(s):  
Stephen A. Hall ◽  
J‐Michael Kendall
Keyword(s):  
High Resolution ◽  
Wave Amplitude ◽  
Effective Medium ◽  
Normal Direction ◽  
P Wave ◽  
Ocean Bottom ◽  
Induced Anisotropy ◽  
Amplitude Variation ◽  
Data Set ◽  
Amplitude Variation With Offset

The delineation and characterization of fracturing is important in the successful exploitation of many hydrocarbon reservoirs. Such fracturing often occurs in preferentially aligned sets; if the fractures are of subseismic scale, this may result in seismic anisotropy. Thus, measurements of anisotropy from seismic data may be used to delineate fracture patterns and investigate their properties. Here fracture‐induced anisotropy is investigated in the Valhall field, which lies in the Norwegian sector of the North Sea. This field is a chalk reservoir with good porosity but variable permeability, where fractures may significantly impact production, e.g., during waterflooding. To investigate the nature of fracturing in this reservoir, P‐wave amplitude variation with offset and azimuth (AVOA) is analyzed in a 3D ocean‐bottom cable (OBC) data set. In general, 3D ocean‐bottom seismic (OBS) acquisition leads to patchy coverage in offset and azimuth, and this must be addressed when considering such data. To overcome this challenge and others associated with 3D OBS acquisition, a new method for processing and analysis is presented. For example, a surface fitting approach, which involves analyzing azimuthal variations in AVO gradients, is used to estimate the orientation and magnitude of the fracture‐induced anisotropy. This approach is also more widely applicable to offset‐azimuth analysis of other attributes (e.g., traveltimes) and any data set where there has been true 3D data acquisition, land or marine. Using this new methodology, we derive high‐resolution maps of P‐wave anisotropy from the AVOA analysis for the top‐chalk reflection at Valhall. These anisotropy maps show coherent but laterally varying trends. Synthetic AVOA modeling, using effective medium models, indicates that if this anisotropy is from aligned fracturing, the fractures are likely liquid filled with small aspect ratios and the fracture density must be high. Furthermore, we show that the fracture‐normal direction is parallel to the direction of most positive AVO gradient. In other situations the reverse can be true, i.e., the fracture‐normal direction can be parallel to the direction of the most negative AVO gradient. Effective medium modeling or comparisons with anisotropy estimates from other approaches (e.g., azimuthal variations in velocity) must therefore be used to resolve this ambiguity. The inferred fracture orientations and anisotropy magnitudes show a degree of correlation with the positions and alignments of larger scale faults, which are estimated from 3D coherency analysis. Overall, this work demonstrates that significant insight may be gained into the alignment and character of fracturing and the stress field variations throughout a field using this high‐resolution AVOA method.

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