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.

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.

Effect of VS predictors on amplitude variation with offset response

Geophysics ◽  
2018 ◽  
Vol 83 (1) ◽  
pp. N1-N13
Author(s):  
Humberto S. Arévalo-López ◽  
Uri Wollner ◽  
Jack P. Dvorkin
Keyword(s):  
Seismic Data ◽  
Poor Quality ◽  
Rock Properties ◽  
Specific Situation ◽  
S Wave ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Seismic Amplitude ◽  
Text Prediction ◽  
A Site

We have posed a question whether the differences between various [Formula: see text] predictors affect one of the ultimate goals of [Formula: see text] prediction, generating synthetic amplitude variation with offset (AVO) gathers to serve as a calibration tool for interpreting the seismic amplitude for rock properties and conditions. We address this question by evaluating examples in which we test several such predictors at an interface between two elastic layers, at pseudowells, and at a real well with poor-quality S-wave velocity data. The answer based on the examples presented is that no matter which [Formula: see text] predictor is used, the seismic responses at a reservoir are qualitatively identical. The choice of a [Formula: see text] predictor does not affect our ability (or inability) to forecast the presence of hydrocarbons from seismic data. We also find that the amplitude versus angle responses due to different predictors consistently vary along the same pattern, no matter which predictor is used. Because our analysis uses a “by-example” approach, the conclusions are not entirely general. However, the method of comparing the AVO responses due to different [Formula: see text] predictors discussed here is. Hence, in a site-specific situation, we recommend using several relevant predictors to ascertain whether the choice significantly affects the synthetic AVO response and if this response is consistent with veritable seismic data.

Nonlinear inversion of seismic amplitude variation with offset for an effective stress parameter

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. R299-R311
Author(s):  
Huaizhen Chen ◽  
Junxiao Li ◽  
Kristopher A. Innanen
Keyword(s):  
Effective Stress ◽  
Seismic Data ◽  
Incidence Angle ◽  
Fluid Substitution ◽  
Nonlinear Inversion ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Sensitive Parameter ◽  
Stress Parameter ◽  
Set Up

Effective stress estimates play important roles in reservoir characterization, for instance, in guiding the selection of fracturing areas in unconventional reservoirs. Based on Gassmann’s fluid substitution model, we have set up a workflow for nonlinear inversion of seismic data for dry rock moduli, fluid factors, and a stress-sensitive parameter. We first make an approximation within the fluid substitution equation, replacing the porosity term with a stress-sensitive parameter. We then derive a linearized reflection coefficient as a function of a stress-parameter reflectivity and reexpress it in terms of elastic impedance (EI). An amplitude-variation-with-offset (AVO) inversion workflow is set up, in which the seismic data are transformed to EI, after stacking within five incidence angle ranges; these are then inverted to determine the stress-sensitive parameter. The two-step process involves two inversions with significantly different properties. The first is a model-based least-squares inversion to estimate EI; the second is a more complex nonlinear inversion of the EI for a set of unknowns including the stress-sensitive parameter. Motivated by an interest in hybridizing AVO and full-waveform inversion (FWI), we set the latter step up to resemble some features of a published AVO-FWI formulation. The approach is subjected to synthetic validation, which permits us to analyze the response and test the stability of the workflow. We finally apply the workflow to real data acquired over a gas-bearing reservoir, which reveals that the approach generates potential indicators of fluid presence and stress prediction.

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

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.

Effective AVO crossplot modeling: A tutorial

Geophysics ◽  
2000 ◽  
Vol 65 (3) ◽  
pp. 700-711 ◽  
Author(s):  
Christopher P. Ross
Keyword(s):  
Seismic Data ◽  
Well Logs ◽  
Substitution Effects ◽  
High Grade ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Avo Analysis ◽  
Fundamental Process ◽  
Seismic Volumes ◽  
Selection Of

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.

An integrated broadband preprocessing method for towed-streamer seismic data

Geophysics ◽  
2020 ◽  
Vol 85 (2) ◽  
pp. V201-V221 ◽  
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.

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

Geophysics ◽  
2014 ◽  
Vol 79 (4) ◽  
pp. R151-R163 ◽  
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.

Traveltime and relative geometric spreading approximation in elastic orthorhombic medium

Geophysics ◽  
2020 ◽  
Vol 85 (5) ◽  
pp. C153-C162 ◽  
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.

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

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.

The Shuey-Radon transform

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. V197-V206 ◽  
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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