Three-term amplitude-variation-with-offset projections

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. N51-N65 ◽  
Author(s):  
Vaughn Ball ◽  
Luis Tenorio ◽  
Christian Schiøtt ◽  
Michelle Thomas ◽  
J. P. Blangy
Keyword(s):  
Rock Physics ◽  
Projection Methods ◽  
Well Logs ◽  
Rock Properties ◽  
Inversion Method ◽  
Practical Implementation ◽  
Angle Of Incidence ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Maximum Angle

A three-term (3T) amplitude-variation-with-offset projection is a weighted sum of three elastic reflectivities. Parameterization of the weighting coefficients requires two angle parameters, which we denote by the pair [Formula: see text]. Visualization of this pair is accomplished using a globe-like cartographic representation, in which longitude is [Formula: see text], and latitude is [Formula: see text]. Although the formal extension of existing two-term (2T) projection methods to 3T methods is trivial, practical implementation requires a more comprehensive inversion framework than is required in 2T projections. We distinguish between projections of true elastic reflectivities computed from well logs and reflectivities estimated from seismic data. When elastic reflectivities are computed from well logs, their projection relationships are straightforward, and they are given in a form that depends only on elastic properties. In contrast, projection relationships between reflectivities estimated from seismic may also depend on the maximum angle of incidence and the specific reflectivity inversion method used. Such complications related to projections of seismic-estimated elastic reflectivities are systematized in a 3T projection framework by choosing an unbiased reflectivity triplet as the projection basis. Other biased inversion estimates are then given exactly as 3T projections of the unbiased basis. The 3T projections of elastic reflectivities are connected to Bayesian inversion of other subsurface properties through the statistical notion of Bayesian sufficiency. The triplet of basis reflectivities is computed so that it is Bayes sufficient for all rock properties in the hierarchical seismic rock-physics model; that is, the projection basis contains all information about rock properties that is contained in the original seismic.

Seismic reservoir characterization of a class-1 amplitude variation with offset turbiditic system located offshore Cote d’Ivoire, West Africa

2018 ◽  
Vol 6 (2) ◽  
pp. SD115-SD128
Author(s):  
Pedro Alvarez ◽  
William Marin ◽  
Juan Berrizbeitia ◽  
Paola Newton ◽  
Michael Barrett ◽  
...  
Keyword(s):  
West Africa ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Rock Physics ◽  
Rock Properties ◽  
Well Log ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Fluid Content ◽  
Class 1

We have evaluated a case study, in which a class-1 amplitude variation with offset (AVO) turbiditic system located offshore Cote d’Ivoire, West Africa, is characterized in terms of rock properties (lithology, porosity, and fluid content) and stratigraphic elements using well-log and prestack seismic data. The methodology applied involves (1) the conditioning and modeling of well-log data to several plausible geologic scenarios at the prospect location, (2) the conditioning and inversion of prestack seismic data for P- and S-wave impedance estimation, and (3) the quantitative estimation of rock property volumes and their geologic interpretation. The approaches used for the quantitative interpretation of these rock properties were the multiattribute rotation scheme for lithology and porosity characterization and a Bayesian lithofluid facies classification (statistical rock physics) for a probabilistic evaluation of fluid content. The result indicates how the application and integration of these different AVO- and rock-physics-based reservoir characterization workflows help us to understand key geologic stratigraphic elements of the architecture of the turbidite system and its static petrophysical characteristics (e.g., lithology, porosity, and net sand thickness). Furthermore, we found out how to quantify and interpret the risk related to the probability of finding hydrocarbon in a class-1 AVO setting using seismically derived elastic attributes, which are characterized by having a small level of sensitivity to changes in fluid saturation.

scholarly journals An Accurate Jacobian Matrix with Exact Zoeppritz for Elastic Moduli of Dry Rock

2019 ◽  
Vol 9 (24) ◽  
pp. 5485
Author(s):  
Xiaobo Liu ◽  
Jingyi Chen ◽  
Fuping Liu ◽  
Zhencong Zhao
Keyword(s):  
Jacobian Matrix ◽  
Incidence Angle ◽  
Inversion Method ◽  
Seismic Velocities ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Shear Moduli ◽  
Partial Derivatives ◽  
Solid Matrices ◽  
Derivatives Of

Seismic velocities are related to the solid matrices and the pore fluids. The bulk and shear moduli of dry rock are the primary parameters to characterize solid matrices. Amplitude variation with offset (AVO) or amplitude variation with incidence angle (AVA) is the most used inversion method to discriminate lithology in hydrocarbon reservoirs. The bulk and shear moduli of dry rock, however, cannot be inverted directly using seismic data and the conventional AVO/AVA inversions. The most important step to accurately invert these dry rock parameters is to derive the Jacobian matrix. The combination of exact Zoeppritz and Biot–Gassmann equations makes it possible to directly calculate the partial derivatives of seismic reflectivities (PP-and PS-waves) with respect to dry rock moduli. During this research, we successfully derive the accurate partial derivatives of the exact Zoeppritz equations with respect to bulk and shear moduli of dry rock. The characteristics of these partial derivatives are investigated in the numerical examples. Additionally, we compare the partial derivatives using this proposed algorithm with the classical Shuey and Aki–Richards approximations. The results show that this derived Jacobian matrix is more accurate and versatile. It can be used further in the conventional AVO/AVA inversions to invert bulk and shear moduli of dry rock directly.

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.

AVA analysis after velocity-independent DMO and imaging

Geophysics ◽  
1998 ◽  
Vol 63 (2) ◽  
pp. 686-691 ◽  
Author(s):  
Gerald H. F. Gardner ◽  
Anat Canning
Keyword(s):  
Reflection Coefficient ◽  
Peak Amplitude ◽  
Angle Of Incidence ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
The Past ◽  
Reflectivity Function ◽  
Velocity Of Propagation ◽  
Zero Offset ◽  
Amplitude Versus

A common midpoint (CMP) gather usually provides amplitude variation with offset (AVO) information by displaying the reflectivity as the peak amplitude of symmetrical deconvolved wavelets. This puts a reflection coefficient R at every offset h, giving a function R(h). But how do we link h with the angle of incidence, θ, to get the reflectivity function, R(θ)? This is necessary for amplitude versus angle-of-incidence (AVA) analysis. One purpose of this paper is to derive formulas for this linkage after velocity-independent dip-moveout (DMO), done by migrating radial sections, and prestack zero-offset migration. Related studies of amplitude-preserving DMO in the past have dealt with constant-offset DMO but have not given the connection between offset and angle of incidence after processing. The results in the present paper show that the same reflectivity function can be extracted from the imaged volume whether it is produced using radial-trace DMO plus zero-offset migration, constant-offset DMO plus zero-offset migration, or directly by prestack, common-offset migration. The data acquisition geometry for this study consists of parallel, regularly spaced, multifold lines, and the velocity of propagation is constant. Events in the data are caused by an arbitrarily oriented 3-D plane reflector with any reflectivity function. The DMO operation transforms each line of data (m, h, t), i.e., midpoint, half-offset, and time, into an (m1, k, t1) space by Stolt-migrating each radial-plane section of the data, 2h = Ut, with constant velocity U/2. Merging the (m1, k, t1) spaces for all the lines forms an (x, y, k, t1) space, where the first two coordinates are the midpoint location, the third is the new half-offset, and the fourth is the time. Normal moveout (NMO) plus 3-D zero-offset migration of the subspace (x, y, t1) for each k creates a true-amplitude imaged volume (X, Y, k, T). Each peak amplitude in the volume is a reflection coefficient linked to an angle of incidence.

scholarly journals AVO analysis for high amplitude anomalies using 2D pre-stack seismic data

2022 ◽  
Author(s):  
Lamees N. Abdulkareem ◽  
Keyword(s):  
Seismic Data ◽  
High Amplitude ◽  
Rock Properties ◽  
Fluid Substitution ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
The Real ◽  
North West ◽  
Avo Analysis ◽  
Controlling Parameter

Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the controlling parameter on the AVO analysis. AVO cross plots from the real pre-stack seismic data reveal AVO class IV (showing a negative intercept decreasing with offset). This result matches our modelled result of fluid substitution for the seismic synthetics. It is concluded that fluid substitution is the controlling parameter on the AVO analysis and therefore, the high amplitude anomaly on the seabed and the target horizon 9 is the result of changing the fluid content and the lithology along the target horizons. While changing the porosity has little effect on the amplitude variation with offset within the AVO cross plot. Finally, results from the wedge models show that a small change of thickness causes a change in the amplitude; however, this change in thickness gives a different AVO characteristic and a mismatch with the AVO result of the real 2D pre-stack seismic data. Therefore, a constant thin layer with changing fluids is more likely to be the cause of the high amplitude anomalies.

Geophysical pore type inversion in carbonate reservoir: integration of cores, well-logs, and seismic data (Yadana field, offshore Myanmar)

Geophysics ◽  
2021 ◽  
pp. 1-69
Author(s):  
Thomas Teillet ◽  
François Fournier ◽  
Luanxiao Zhao ◽  
Jean Borgomano ◽  
Fei Hong
Keyword(s):  
Seismic Data ◽  
Effective Medium Theory ◽  
Rock Physics ◽  
Carbonate Reservoir ◽  
Well Logs ◽  
Inversion Method ◽  
Gas Field ◽  
Medium Theory ◽  
Scale Thickness ◽  
Pore Types

Detection of pore types and diagenetic features from seismic data is a major challenge for the evaluation of carbonate reservoirs in the subsurface. Based on a detailed petrographical and petrophysical analysis of carbonate rock using optical and scanning electron microscopy, mercury-injection measurements, digital image analysis, and well logs, we have determined the potential of the geophysical pore type (αP) inversion a rock physics inversion scheme based on the differential effective medium theory – to quantitatively and qualitatively characterize the pore type distribution from acoustic data in the Yadana carbonate gas field (Early Miocene, offshore Myanmar). The geophysical pore type (αP) is revealed to be an upscalable parameter, whose depositional/diagenetic interpretation may be performed at well log and at seismic scales. We apply the inversion method on a 3D seismic data to map the reservoir-scale distribution and highlight the occurrence of laterally extended (100–1000 m) subseismic- to seismic-scale (thickness >5 m) geologic bodies. From this approach, two main reservoir geobodies are discriminated and interpreted in terms of depositional and diagenetic fabrics: (1) highly microporous, decameter-scale reservoir units (approximately 80% of the reservoir), mainly consisting of foraminiferal, red algae floatstone to rudstone with vuggy, moldic porosity, and characterized by moderate to high αP (0.11–0.20) and (2) thin, stratiform, cemented scleractinian floatstone/brecciated units (5–10 m; approximately 20% of the reservoir) with low microporosity and macroporosity and exhibiting low αP values (<0.11).

Amplitude-variation-with-offset, elastic-impedence, and wave-equation synthetics — A modeling study

Geophysics ◽  
2007 ◽  
Vol 72 (1) ◽  
pp. C1-C7 ◽  
Author(s):  
Subhashis Mallick
Keyword(s):  
Wave Equation ◽  
Incidence Angle ◽  
Synthetic Data ◽  
P Wave ◽  
Equation Modeling ◽  
Parameter Estimates ◽  
Angle Of Incidence ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Wave Modes

Amplitude-variation-with-offset (AVO) and elastic-impedance (EI) analysis use an approximate plane P-wave reflection coefficient as a function of angle of incidence. AVO and EI both can be used in a three-term or a two-term formulation. This study uses synthetic data to demonstrate that the P-wave primary reflections at large offsets can be contaminated by reflections from other wave modes that can affect the quality of three-term AVO or EI results. The coupling of P-waves and S-waves in seismic-wave propagation through finely layered media generates the interfering wave modes. A methodology such as prestack-wave-equation modeling can properly account for these coupling effects. Both AVO and EI also assume a convolutional model whose accuracy decreases as incidence angles increase. On the other hand, wave-equation modeling is based on the rigorous solution to the wave equation and is valid for any incidence angle. Because wave interference is minimal at small angles, a two-term AVO/EI analysis that restricts input from small angles is likely to give more reliable parameter estimates than a three-term analysis. A three-term AVO/EI analysis should be used with caution and should be calibrated against well data and other data before being used for quantitative analysis.

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.

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.

scholarly journals A direct inverse method for subsurface properties: The conceptual and practical benefit and added value in comparison with all current indirect methods, for example, amplitude-variation-with-offset and full-waveform inversion

2017 ◽  
Vol 5 (3) ◽  
pp. SL89-SL107 ◽  
Author(s):  
Arthur B. Weglein
Keyword(s):  
Success Rate ◽  
Waveform Inversion ◽  
Forward Problem ◽  
Inversion Method ◽  
Elastic Model ◽  
Full Waveform Inversion ◽  
Amplitude Variation ◽  
Indirect Methods ◽  
Amplitude Variation With Offset ◽  
Full Waveform

Direct inverse methods solve the problem of interest; in addition, they communicate whether the problem of interest is the problem that we (the seismic industry) need to be interested in. When a direct solution does not result in an improved drill success rate, we know that the problem we have chosen to solve is not the right problem — because the solution is direct and cannot be the issue. On the other hand, with an indirect method, if the result is not an improved drill success rate, then the issue can be either the chosen problem, or the particular choice within the plethora of indirect solution methods, or both. The inverse scattering series (ISS) is the only direct inversion method for a multidimensional subsurface. Solving a forward problem in an inverse sense is not equivalent to a direct inverse solution. All current methods for parameter estimation, e.g., amplitude-variation-with-offset and full-waveform inversion, are solving a forward problem in an inverse sense and are indirect inversion methods. The direct ISS method for determining earth material properties defines the precise data required and the algorithms that directly output earth mechanical properties. For an elastic model of the subsurface, the required data are a matrix of multicomponent data, and a complete set of shot records, with only primaries. With indirect methods, any data can be matched: one trace, one or several shot records, one component, multicomponent, with primaries only or primaries and multiples. Added to that are the innumerable choices of cost functions, generalized inverses, and local and global search engines. Direct and indirect parameter inversion are compared. The direct ISS method has more rapid convergence and a broader region of convergence. The difference in effectiveness increases as subsurface circumstances become more realistic and complex, in particular with band-limited noisy data.

Sign in / Sign up

Export Citation Format

Share Document