Amplitude variation with angle inversion using the exact Zoeppritz equations — Theory and methodology

Geophysics ◽  
2016 ◽  
Vol 81 (2) ◽  
pp. N1-N15 ◽  
Author(s):  
Lixia Zhi ◽  
Shuangquan Chen ◽  
Xiang-yang Li
Keyword(s):  
Parameter Extraction ◽  
Tikhonov Regularization Method ◽  
Inversion Method ◽  
Data Sets ◽  
Nonlinear Inversion ◽  
S Wave ◽  
Amplitude Variation ◽  
Highly Nonlinear ◽  
Amplitude Variation With Angle ◽  
Dominant Frequencies

To overcome the weaknesses of conventional prestack amplitude variation with angle inversion based on various linear or quasi-linear approximations, we have conducted a nonlinear inversion method using the exact Zoeppritz matrix (EZAI). However, the inversion using the exact Zoeppritz matrix was highly nonlinear and often unstable, if not properly treated. To tackle these issues, we have used an iteratively regularizing Levenberg-Marquardt scheme (IRLM), which regularizes the inversion problem within an algorithm that minimizes the misfit between the observed and the modeled data at the same time by incorporating the Tikhonov regularization method. As a result, the new EZAI method solved using the IRLM scheme is feasible for seismic data sets with large incidence angles, even up to or beyond the critical angle as well as strong parameter contrasts. Single and multilayered synthetic examples were used to test these features. These tests also showed that EZAI is robust on noisy gathers for parameter extraction and has weak dependence on the initial model. For the influence of inaccurate amplitudes, dominant frequencies, and phase angles, we found that EZAI is less sensitive to the variation in amplitude and phase shifts than to the dominant frequencies. Specifically, the inversion results of EZAI for P- and S-wave velocities and density were reliable if the inaccurate range for the amplitude was within 20% or the angle of the phase shift was no more than 20°. The superiority of EZAI makes it a very promising method for the estimation of subsurface elastic parameters.

Imperialist competitive algorithm optimization method for nonlinear amplitude variation with angle inversion

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. N81-N92 ◽  
Author(s):  
Amir Mollajan ◽  
Hossein Memarian ◽  
Beatriz Quintal
Keyword(s):  
Synthetic Data ◽  
Imperialist Competitive Algorithm ◽  
Optimization Methods ◽  
Hydrocarbon Exploration ◽  
Inversion Method ◽  
Inversion Problem ◽  
S Wave ◽  
Amplitude Variation ◽  
Competitive Algorithm ◽  
Amplitude Variation With Angle

Amplitude variation with angle (AVA) inversion is one of the most effective techniques in hydrocarbon exploration and estimating subsurface petrophysical properties. The inversion problem as a nonlinear, multiparameter, and multimodal optimization problem is conventionally solved through linearized optimization methods, but with the cost of smoothing important geologic interfaces. In addition, the results obtained by these methods are more possible to be trapped in a local minimum, while global-optimization methods can produce more accurate results and preserve the interfaces of geologic structures. A Bayesian framework is used to formulate the AVA inversion problem, which incorporates a novel prior constraint included by two regularization functions, one for sparsity of the coefficients as well as recovering discontinuities and another one for enhancing the lateral continuity. The imperialist competitive algorithm as an efficient evolutionary algorithm is then used to optimize the resulted objective function, to invert the P-and S-wave velocities as well as the density. We compare our algorithm with a commonly used Bayesian linearized inversion method by applying both methods on synthetic data and real seismic data from Gulf of Mexico. Our results reveal the practicability and stability of the presented method for the AVA inversion problem.

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.

SH-SH wave inversion for S-wave velocity and density

Geophysics ◽  
2022 ◽  
pp. 1-59
Author(s):  
Fucai Dai ◽  
Feng Zhang ◽  
Xiangyang Li
Keyword(s):  
Wave Velocity ◽  
Inversion Method ◽  
Data Sets ◽  
Sh Wave ◽  
S Wave ◽  
Data Set ◽  
Sh Waves ◽  
Model Parameter ◽  
Wave Inversion ◽  
Impedance Contrast

SS-waves (SV-SV waves and SH-SH waves) are capable of inverting S-wave velocity ( VS) and density ( ρ) because they are sensitive to both parameters. SH-SH waves can be separated from multicomponent data sets more effectively than the SV-SV wave because the former is decoupled from the PP-wave in isotropic media. In addition, the SH-SH wave can be better modeled than the SV-SV wave in the case of strong velocity/impedance contrast because the SV-SV wave has multicritical angles, some of which can be quite small when velocity/ impedance contrast is strong. We derived an approximate equation of the SH-SH wave reflection coefficient as a function of VS and ρ in natural logarithm variables. The approximation has high accuracy, and it enables the inversion of VS and ρ in a direct manner. Both coefficients corresponding to VS and ρ are “model-parameter independent” and thus there is no need for prior estimate of any model parameter in inversion. Then, we developed an SH-SH wave inversion method, and demonstrated it by using synthetic data sets and a real SH-SH wave prestack data set from the west of China. We found that VS and ρ can be reliably estimated from the SH-SH wave of small angles.

Computation of dry-rock VP/VS ratio, fluid property factor, and density estimation from amplitude-variation-with-offset inversion

Geophysics ◽  
2018 ◽  
Vol 83 (6) ◽  
pp. R669-R679 ◽  
Author(s):  
Gang Chen ◽  
Xiaojun Wang ◽  
Baocheng Wu ◽  
Hongyan Qi ◽  
Muming Xia
Keyword(s):  
Reservoir Characterization ◽  
Synthetic Data ◽  
Pore Fluid ◽  
Inversion Method ◽  
S Wave ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Fluid Identification ◽  
Fluid Property ◽  
Avo Inversion

Estimating the fluid property factor and density from amplitude-variation-with-offset (AVO) inversion is important for fluid identification and reservoir characterization. The fluid property factor can distinguish pore fluid in the reservoir and the density estimate aids in evaluating reservoir characteristics. However, if the scaling factor of the fluid property factor (the dry-rock [Formula: see text] ratio) is chosen inappropriately, the fluid property factor is not only related to the pore fluid, but it also contains a contribution from the rock skeleton. On the other hand, even if the angle gathers include large angles (offsets), a three-parameter AVO inversion struggles to estimate an accurate density term without additional constraints. Thus, we have developed an equation to compute the dry-rock [Formula: see text] ratio using only the P- and S-wave velocities and density of the saturated rock from well-logging data. This decouples the fluid property factor from lithology. We also developed a new inversion method to estimate the fluid property factor and density parameters, which takes full advantage of the high stability of a two-parameter AVO inversion. By testing on a portion of the Marmousi 2 model, we find that the fluid property factor calculated by the dry-rock [Formula: see text] ratio obtained by our method relates to the pore-fluid property. Simultaneously, we test the AVO inversion method for estimating the fluid property factor and density parameters on synthetic data and analyze the feasibility and stability of the inversion. A field-data example indicates that the fluid property factor obtained by our method distinguishes the oil-charged sand channels and the water-wet sand channel from the well logs.

Direct nonlinear inversion of multiparameter 1D elastic media using the inverse scattering series

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. WCD15-WCD27 ◽  
Author(s):  
Haiyan Zhang ◽  
Arthur B. Weglein
Keyword(s):  
Wave Velocity ◽  
Material Properties ◽  
Value Added ◽  
P Wave ◽  
Added Value ◽  
Inversion Method ◽  
Elastic Media ◽  
Nonlinear Inversion ◽  
Model Matching ◽  
S Wave

In the direct nonlinear inversion method and in algorithms for 1D elastic media, P-wave velocity, S-wave velocity, and density are depth dependent. “Direct nonlinear” means that the method uses explicit formulas that (1) input data and directly output changes in material properties without the need for indirect procedures such as model matching, searching, optimization, or other assumed aligned objectives or proxies and that (2) the algorithms recognize and directly invert the intrinsic nonlinear relationship between changes in material properties and the recorded reflection wavefields. To achieve full elastic inversion, all components of data (such as PP, SP, and SS data) are needed. The method assumes that only data and reference medium propertiesare input, and terms in the inverse series for moving mislocated reflectors resulting from the linear inverse term are separated from amplitude correction terms. Although in principle this direct inversion approach requires all components of elastic data, synthetic tests indicate that a consistent value-added result may be achieved given only PP data measurements, as long as the PP data are used to approximately synthesize the PS and SP components. Further value would be derived from measuring all components of the data as the method requires. If all components of data are available, one consistent method can solve for all of the second terms (the first terms beyond linear). The explicit nonlinear inversion formulas provide an unambiguous data requirement message as well as conceptual and practical added value beyond both linear approaches and all indirect methods.

Joint anisotropic amplitude variation with offset inversion of PP and PS seismic data

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. N31-N50 ◽  
Author(s):  
Jun Lu ◽  
Yun Wang ◽  
Jingyi Chen ◽  
Ying An
Keyword(s):  
Seismic Data ◽  
Local Minimum ◽  
Synthetic Data ◽  
Inversion Method ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Avo Inversion ◽  
Time Migration ◽  
Amplitude Variation With Angle ◽  
Two Stages

With the increase in exploration target complexity, more parameters are required to describe subsurface properties, particularly for finely stratified reservoirs with vertical transverse isotropic (VTI) features. We have developed an anisotropic amplitude variation with offset (AVO) inversion method using joint PP and PS seismic data for VTI media. Dealing with local minimum solutions is critical when using anisotropic AVO inversion because more parameters are expected to be derived. To enhance the inversion results, we adopt a hierarchical inversion strategy to solve the local minimum solution problem in the Gauss-Newton method. We perform the isotropic and anisotropic AVO inversions in two stages; however, we only use the inversion results from the first stage to form search windows for constraining the inversion in the second stage. To improve the efficiency of our method, we built stop conditions using Euclidean distance similarities to control iteration of the anisotropic AVO inversion in noisy situations. In addition, we evaluate a time-aligned amplitude variation with angle gather generation approach for our anisotropic AVO inversion using anisotropic prestack time migration. We test the proposed method on synthetic data in ideal and noisy situations, and find that the anisotropic AVO inversion method yields reasonable inversion results. Moreover, we apply our method to field data to show that it can be used to successfully identify complex lithologic and fluid information regarding fine layers in reservoirs.

Model parameterization and amplitude variation with angle and azimuthal inversion in orthotropic media

Geophysics ◽  
2020 ◽  
Vol 86 (1) ◽  
pp. R1-R14
Author(s):  
Zhaoyun Zong ◽  
Lixiang Ji
Keyword(s):  
Parameter Estimation ◽  
Seismic Data ◽  
Inversion Method ◽  
Initial Model ◽  
Amplitude Variation ◽  
Inversion Result ◽  
Model Parameterization ◽  
Orthotropic Media ◽  
The Stability ◽  
Amplitude Variation With Angle

Horizontal layered formations with a suite of vertical or near-vertical fractures are usually assumed to be an approximate orthotropic medium and are more suitable for estimating fracture properties with wide-azimuth prestack seismic data in shale reservoirs. However, the small contribution of anisotropic parameters to the reflection coefficients highly reduces the stability of anisotropic parameter estimation by using seismic inversion approaches. Therefore, a novel model parameterization approach for the reflectivity and a pragmatic inversion method are proposed to enhance the stability of the inversion for orthotropic media. Previous attempts to characterize orthotropic media properties required using four or five independent parameters. However, we have derived a novel formulation that reduces the number of parameters to three. The inversion process is better conditioned with fewer degrees of freedom. An accuracy comparison of our formula with the previous ones indicates that our approach is sufficiently precise for reasonable parameter estimation. Furthermore, a Bayesian inversion method is developed that uses the amplitude variation with angle and azimuth (AVAZ) of the seismic data. Smooth background constraints reduce the similarity between the inversion result and the initial model, thereby reducing the sensitivity of the initial model to the inversion result. Cauchy and Gaussian probability distributions are used as prior constraints on the model parameters and the likelihood function, respectively. These ensure that the results are within the range of plausibility. Synthetic examples demonstrate that the adopted orthotropic AVAZ inversion method is feasible for estimating the anisotropic parameters even with moderate noise. The field data example illustrates the inversion robustness and stability of the adopted method in a fractured reservoir with a single well control.

2-D inversion of gravity data using sources laterally bounded by continuous surfaces and depth‐dependent density

Geophysics ◽  
2000 ◽  
Vol 65 (4) ◽  
pp. 1128-1141 ◽  
Author(s):  
Juan García‐Abdeslem
Keyword(s):  
Sensitivity Analysis ◽  
Gravity Data ◽  
Synthetic Data ◽  
Gravity Modeling ◽  
Inversion Method ◽  
Data Sets ◽  
Nonlinear Inversion ◽  
Correlation Matrices ◽  
Significant Difference ◽  
Dependent Density

A description is given of numerical methods for 2-D gravity modeling and nonlinear inversion. The forward model solution is suitable for calculating the gravity anomaly caused by a 2-D source body with depth‐dependent density that is laterally bounded by continuous surfaces and can easily accommodate different kinds of geologic structures. The weighted and damped discrete nonlinear inverse method addressed here can invert both density and geometry of the source body. Both modeling and inversion methods are illustrated with several examples using synthetic and two field gravity data sets—one over a sulfide ore body and other across a sedimentary basin. A sensitivity analysis is carried out for the resulting solutions by means of the resolution, covariance, and correlation matrices, providing insight into the capabilities and limitations of the inversion method. The inversion of synthetic data provides meaningful results, showing that the method is robust in the presence of noise. Its sensitivity analysis indicates an almost perfect resolution and small covariance, but high correlation between some parameters. Differences in the asperity aspect of the inverted‐field data sets turned out to be important for the inversion capabilities of the algorithm, making a significant difference in the resolution achieved, its covariance, and the degree of correlation among parameters.

Interpreter's Corner

2021 ◽  
Vol 40 (6) ◽  
pp. 454-459
Author(s):  
David J. Went
Keyword(s):  
Seismic Data ◽  
Incidence Angle ◽  
Seismic Inversion ◽  
P Wave ◽  
Data Sets ◽  
Oil Sand ◽  
S Wave ◽  
Seismic Line ◽  
The Difference ◽  
Amplitude Variation With Angle

Global empirical relationships of P-wave to S-wave and density for sandstones and shales are used to model two-term amplitude variation with angle at various depths of burial in a typically compacting siliciclastic basin. Data from the normally pressured Tertiary strata of Judd Basin, Atlantic Margin, West of Shetland, are used as a control. For a typical prospect depth of 1750 m below mudline, forward models of angle-dependent reflectivity reveal that discrimination of lithology (shale and brine sand) and fluid (oil sand) is optimally resolved at a 47° incidence angle (θ). This is equivalent to an angle of 28° on an intercept-gradient crossplot. Repeat experiments at other depths produce similar results but with the angle for optimal lithology and fluid determination shifting slightly with increasing depth. Background trends in seismic data crossplots of intercept versus gradient are typically overprinted by noise that has a disproportionate effect on the gradient. This study suggests that the difference between the noise and background rock-property trend is relatively small, such that in most modern seismic data sets, anomalies should be identifiable on time-windowed crossplots and equivalent weighted stacks. It is proposed that a seismic inversion for relative extended elastic impedance at a 45° incidence angle should capture most anomalies of interest in frontier basins with simple burial histories. An example is illustrated from a seismic line in Mozambique.

Nonlinear amplitude-variation-with-offset inversion for Lamé parameters using a direct inversion method

2017 ◽  
Vol 5 (3) ◽  
pp. SL57-SL67 ◽  
Author(s):  
Guangsen Cheng ◽  
Xingyao Yin ◽  
Zhaoyun Zong
Keyword(s):  
Nonlinear Equation ◽  
Real Data ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Nonlinear Inversion ◽  
Reservoir Prediction ◽  
Amplitude Variation ◽  
Linear Inversion ◽  
Amplitude Variation With Offset ◽  
Avo Inversion

Prestack seismic inversion is widely used in fluid indication and reservoir prediction. Compared with linear inversion, nonlinear inversion is more precise and can be applied to high-contrast situations. The inversion results can be affected by the parameters’ sensitivity, so the parameterization of nonlinear equations is very significant. Considering the poor nonlinear amplitude-variation-with-offset (AVO) inversion results of impedance and velocity parameters, we adjust the parameters of the nonlinear equation, avoid the inaccuracy caused by parameters sensitivity and get the ideal nonlinear AVO inversion results of the Lamé parameters. The feasibility and stability of the nonlinear equation based on the Lamé parameters and method are verified by the model and the real data examples. The resolution and the lateral continuity of nonlinear inversion results are better compared with the linear inversion results.

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