Effective AVO crossplot modeling: A tutorial

The ability to crossplot attributes from a 3-D seismic volume permits a geophysicist to identify and high grade subsets of the 3-D volume that warrant detailed inspection. In the case of amplitude‐variation‐with‐offset (AVO) crossplotting, the seismic attributes are derived from CDP data. Crossplotting has become a fundamental process in AVO analysis, just as it is in petrophysical analysis. Comprehending the intricacies and selection of attributes is essential for successful AVO analysis and improved seismic interpretation. AVO crossplotting of modeled seismic data derived from well logs with the Biot‐Gassmann equations provides a basis for understanding fluid substitution effects on AVO attribute interactions when crossplotting. With these model‐based understandings, improved multi‐attribute interpretation processes can commence with AVO crossplotting of seismic volumes.

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

Kuwait Journal of Science ◽

10.48129/kjs.12351 ◽

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.

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Amplitude variation with offset analysis of time-lapse land seismic data in a gas field, Thrace Basin, Turkey

Interpretation ◽

10.1190/int-2015-0186.1 ◽

2016 ◽

Vol 4 (4) ◽

pp. T543-T556

Author(s):

Sait Baytok ◽

Şeref Arzu Aktepe ◽

Muhlis Ünaldi

Keyword(s):

Seismic Data ◽

Time Lapse ◽

Amplitude Variation ◽

Amplitude Variation With Offset ◽

Data Cubes ◽

Avo Analysis ◽

Thrace Basin ◽

Northwestern Turkey ◽

4D Seismic ◽

Monitor Data

The Thrace Basin that is located in northwestern Turkey contains sandstone and carbonate reservoirs of Eocene and Oligocene age. Production and exploration activities are still underway. Mapping undrained sweet spots from seismic data is currently a challenge, so time lapse (4D) seismic is used to reduce the risk for new production and development drilling. We have evaluated the normalization and amplitude variation with offset (AVO) analysis of 3D-4D land seismic data in a gas producing field from which baseline and monitor surveys were acquired in 2002 and 2011, respectively. Through AVO analysis, intercept (A) and gradient (B) analysis was conducted, and fluid factor (FF) attribute maps were generated for the assessment of the remaining potential areas. Synthetic gathers were created for simulation of the AVO response, drained and undrained stages and compared with the corresponding 4D seismic data. The drainage of gas from the reservoir interval is evident from the difference maps between 2002 and 2011 seismic data. Both data sets were processed using an amplitude friendly processing sequence. This parallel processing was followed a mild data conditioning and crossequalization for reliable 4D interpretation. The 4D seismic data, especially land data, has low repeatability and requires conditioning to reduce the 4D noise. The 4D noise can be described as nonrepeatable noise, and any difference outside the reservoir zone is not related to production. A so-called crossequalization was applied to the base and the monitor data to bring out similarities so that they cancel out when differences of seismic data and its attributes indicated only the production results over the reservoir zones. As the available 4D data crossequalization software was implemented for stack data only, we created angle band stacks and crossequalized each angle band stack from the base and the monitor data cubes. Five angle band stacks from the base and the monitor prestack data cubes 0°–55° (0°–15°, 15°–25°, 25°–35°, 35°–45°, and 45°–55°) were crossequalized individually. The crossequalized angle band stacks were used in AVO analysis and AVO inversion to generate pore fill identifiers such as FF to map possible undrained zones after 10 years of production.

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An integrated broadband preprocessing method for towed-streamer seismic data

Geophysics ◽

10.1190/geo2019-0521.1 ◽

2020 ◽

Vol 85 (2) ◽

pp. V201-V221 ◽

Cited By ~ 2

Author(s):

Mehdi Aharchaou ◽

Erik Neumann

Keyword(s):

Seismic Data ◽

High Frequency ◽

Pressure Data ◽

Amplitude Variation ◽

Field Source ◽

Amplitude Variation With Offset ◽

Ringing Artifacts ◽

Joint Application ◽

Amplitude Compensation ◽

Unified Method

Broadband preprocessing has become widely used for marine towed-streamer seismic data. In the standard workflow, far-field source designature, receiver and source-side deghosting, and redatuming to mean sea level are applied in sequence, with amplitude compensation for background [Formula: see text] delayed until the imaging or postmigration stages. Thus, each step is likely to generate its own artifacts, quality checking can be time-consuming, and broadband data are only obtained late in this chained workflow. We have developed a unified method for broadband preprocessing — called integrated broadband preprocessing (IBP) — which enables the joint application of all the above listed steps early in the processing sequence. The amplitude, phase, and amplitude-variation-with-offset fidelity of IBP are demonstrated on pressure data from the shallow, deep, and slanted streamers. The integration allows greater sparsity to emerge in the representation of seismic data, conferring clear benefits over the sequential application. Moreover, time sparsity, full dimensionality, and early amplitude [Formula: see text] compensation all have an impact on broadband data quality, in terms of reduced ringing artifacts, improved wavelet integrity at large crossline angles, and fewer residual high-frequency multiples.

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Value of information analysis and Bayesian inversion for closed skew-normal distributions: Applications to seismic amplitude variation with offset data

Geophysics ◽

10.1190/geo2013-0048.1 ◽

2014 ◽

Vol 79 (4) ◽

pp. R151-R163 ◽

Cited By ~ 4

Author(s):

Javad Rezaie ◽

Jo Eidsvik ◽

Tapan Mukerji

Keyword(s):

Seismic Data ◽

Value Of Information ◽

Bayesian Inversion ◽

Information Analysis ◽

Amplitude Variation ◽

Mean Values ◽

Amplitude Variation With Offset ◽

Seismic Amplitude ◽

Value Of Information Analysis ◽

Skew Normal

Information analysis can be used in the context of reservoir decisions under uncertainty to evaluate whether additional data (e.g., seismic data) are likely to be useful in impacting the decision. Such evaluation of geophysical information sources depends on input modeling assumptions. We studied results for Bayesian inversion and value of information analysis when the input distributions are skewed and non-Gaussian. Reservoir parameters and seismic amplitudes are often skewed and using models that capture the skewness of distributions, the input assumptions are less restrictive and the results are more reliable. We examined the general methodology for value of information analysis using closed skew normal (SN) distributions. As an example, we found a numerical case with porosity and saturation as reservoir variables and computed the value of information for seismic amplitude variation with offset intercept and gradient, all modeled with closed SN distributions. Sensitivity of the value of information analysis to skewness, mean values, accuracy, and correlation parameters is performed. Simulation results showed that fewer degrees of freedom in the reservoir model results in higher value of information, and seismic data are less valuable when seismic measurements are spatially correlated. In our test, the value of information was approximately eight times larger for a spatial-dependent reservoir variable compared with the independent case.

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Traveltime and relative geometric spreading approximation in elastic orthorhombic medium

Geophysics ◽

10.1190/geo2019-0811.1 ◽

2020 ◽

Vol 85 (5) ◽

pp. C153-C162 ◽

Cited By ~ 1

Author(s):

Shibo Xu ◽

Alexey Stovas ◽

Hitoshi Mikada

Keyword(s):

Seismic Data ◽

Real Data ◽

P Wave ◽

Form Expression ◽

Amplitude Variation ◽

Rational Form ◽

Amplitude Variation With Offset ◽

Practical Applications ◽

Numerical Tests ◽

Geometric Spreading

Wavefield properties such as traveltime and relative geometric spreading (traveltime derivatives) are highly essential in seismic data processing and can be used in stacking, time-domain migration, and amplitude variation with offset analysis. Due to the complexity of an elastic orthorhombic (ORT) medium, analysis of these properties becomes reasonably difficult, where accurate explicit-form approximations are highly recommended. We have defined the shifted hyperbola form, Taylor series (TS), and the rational form (RF) approximations for P-wave traveltime and relative geometric spreading in an elastic ORT model. Because the parametric form expression for the P-wave vertical slowness in the derivation is too complicated, TS (expansion in offset) is applied to facilitate the derivation of approximate coefficients. The same approximation forms computed in the acoustic ORT model also are derived for comparison. In the numerical tests, three ORT models with parameters obtained from real data are used to test the accuracy of each approximation. The numerical examples yield results in which, apart from the error along the y-axis in ORT model 2 for the relative geometric spreading, the RF approximations all are very accurate for all of the tested models in practical applications.

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Fracture detection via correlating P-wave amplitude variation with offset and azimuth analysis and well data in eastern central Saudi Arabia

Interpretation ◽

10.1190/int-2016-0128.1 ◽

2017 ◽

Vol 5 (4) ◽

pp. T531-T544

Author(s):

Ali H. Al-Gawas ◽

Abdullatif A. Al-Shuhail

Keyword(s):

Saudi Arabia ◽

Seismic Data ◽

Production Data ◽

Fracture Zones ◽

Fracture Detection ◽

Amplitude Variation ◽

Data Set ◽

Amplitude Variation With Offset ◽

Well Data ◽

Patch Geometry

The late Carboniferous clastic Unayzah-C in eastern central Saudi Arabia is a low-porosity, possibly fractured reservoir. Mapping the Unayzah-C is a challenge due to the low signal-to-noise ratio (S/N) and limited bandwidth in the conventional 3D seismic data. A related challenge is delineating and characterizing fracture zones within the Unayzah-C. Full-azimuth 3D broadband seismic data were acquired using point receivers, low-frequency sweeps down to 2 Hz, and 6 km patch geometry. The data indicate significant enhancement in continuity and resolution of the reflection data, leading to improved mapping of the Unayzah-C. Because the data set has a rectangular patch geometry with full inline offsets to 6000 m, using amplitude variation with offset and azimuth (AVOA) may be effective to delineate and characterize fracture zones within Unayzah-A and Unayzah-C. The study was undertaken to determine the improvement of wide-azimuth seismic data in fracture detection in clastic reservoirs. The results were validated with available well data including borehole images, well tests, and production data in the Unayzah-A. There are no production data or borehole images within the Unayzah-C. For validation, we had to refer to a comparison of alternative seismic fracture detection methods, mainly curvature and coherence. Anisotropy was found to be weak, which may be due to noise, clastic lithology, and heterogeneity of the reservoirs, in both reservoirs except for along the western steep flank of the study area. These may correspond to some north–south-trending faults suggested by circulation loss and borehole image data in a few wells. The orientation of the long axis of the anisotropy ellipses is northwest–southeast, and it is not in agreement with the north–south structural trend. No correlation was found among the curvature, coherence, and AVOA in Unayzah-A or Unayzah-C. Some possible explanations for the low correlation between the AVOA ellipticity and the natural fractures are a noisy data set, overburden anisotropy, heterogeneity, granulation seams, and deformation.

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The Shuey-Radon transform

Geophysics ◽

10.1190/geo2018-0376.1 ◽

2019 ◽

Vol 84 (3) ◽

pp. V197-V206 ◽

Cited By ~ 1

Author(s):

Ali Gholami ◽

Milad Farshad

Keyword(s):

Radon Transform ◽

Seismic Data ◽

Matching Pursuit ◽

Real Data ◽

Transform Domain ◽

Amplitude Variation ◽

Amplitude Variation With Offset ◽

Linear System Of Equations ◽

Matching Pursuit Algorithm ◽

Zero Offset

The traditional hyperbolic Radon transform (RT) decomposes seismic data into a sum of constant amplitude basis functions. This limits the performance of the transform when dealing with real data in which the reflection amplitudes include the amplitude variation with offset (AVO) variations. We adopted the Shuey-Radon transform as a combination of the RT and Shuey’s approximation of reflectivity to accurately model reflections including AVO effects. The new transform splits the seismic gather into three Radon panels: The first models the reflections at zero offset, and the other two panels add capability to model the AVO gradient and curvature. There are two main advantages of the Shuey-Radon transform over similar algorithms, which are based on a polynomial expansion of the AVO response. (1) It is able to model reflections more accurately. This leads to more focused coefficients in the transform domain and hence provides more accurate processing results. (2) Unlike polynomial-based approaches, the coefficients of the Shuey-Radon transform are directly connected to the classic AVO parameters (intercept, gradient, and curvature). Therefore, the resulting coefficients can further be used for interpretation purposes. The solution of the new transform is defined via an underdetermined linear system of equations. It is formulated as a sparsity-promoting optimization, and it is solved efficiently using an orthogonal matching pursuit algorithm. Applications to different numerical experiments indicate that the Shuey-Radon transform outperforms the polynomial and conventional RTs.

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Reducing 3-D acquisition footprint for 3-D DMO and 3-D prestack migration

Geophysics ◽

10.1190/1.1444417 ◽

1998 ◽

Vol 63 (4) ◽

pp. 1177-1183 ◽

Cited By ~ 47

Author(s):

Anat Canning ◽

Gerald H. F. Gardner

Keyword(s):

Spatial Distribution ◽

Velocity Analysis ◽

Amplitude Variation ◽

Amplitude Variation With Offset ◽

Prestack Migration ◽

Avo Analysis ◽

And Migration

The acquisition patterns of 3-D surveys often have a significant effect on the results of dip moveout (DMO) or prestack migration. When the spatial distribution of input traces is irregular, results from DMO and migration are contaminated by artifacts. In many cases, the footprint of the acquisition patterns can be seen on the migrated section and may result in incorrect interpretation. This phenomena also has a very significant effect on the feasibility of conducting amplitude variation with offset (AVO) analysis after 3-D prestack migration or after 3-D DMO, and also may affect velocity analysis. We propose a simple enhancement to migration and DMO programs that acts to minimize acquisition artifacts.

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Anisotropic 3D elastic full-wavefield inversion to directly estimate elastic properties and its role in interpretation

The Leading Edge ◽

10.1190/tle40040277.1 ◽

2021 ◽

Vol 40 (4) ◽

pp. 277-286

Author(s):

Haiyang Wang ◽

Olivier Burtz ◽

Partha Routh ◽

Don Wang ◽

Jake Violet ◽

...

Keyword(s):

Elastic Properties ◽

Seismic Data ◽

Reservoir Characterization ◽

P Wave ◽

Quality Estimation ◽

Amplitude Variation ◽

Linear Inversion ◽

Amplitude Variation With Offset ◽

P Wave Velocity ◽

Wavefield Inversion

Elastic properties from seismic data are important to determine subsurface hydrocarbon presence and have become increasingly important for detailed reservoir characterization that aids to derisk specific hydrocarbon prospects. Traditional techniques to extract elastic properties from seismic data typically use linear inversion of imaged products (migrated angle stacks). In this research, we attempt to get closer to Tarantola's visionary goal for full-wavefield inversion (FWI) by directly obtaining 3D elastic properties from seismic shot-gather data with limited well information. First, we present a realistic 2D synthetic example to show the need for elastic physics in a strongly elastic medium. Then, a 3D field example from deepwater West Africa is used to validate our workflow, which can be practically used in today's computing architecture. To enable reservoir characterization, we produce elastic products in a cascaded manner and run 3D elastic FWI up to 50 Hz. We demonstrate that reliable and high-resolution P-wave velocity can be retrieved in a strongly elastic setting (i.e., with a class 2 or 2P amplitude variation with offset response) in addition to higher-quality estimation of P-impedance and VP/VS ratio. These parameters can be directly used in interpretation, lithology, and fluid prediction.

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Constrained nonlinear amplitude variation with offset inversion using Zoeppritz equations

Geophysics ◽

10.1190/geo2017-0543.1 ◽

2018 ◽

Vol 83 (3) ◽

pp. R245-R255 ◽

Cited By ~ 8

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.

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