Useful approximations for converted‐wave AVO

Geophysics ◽  
2001 ◽  
Vol 66 (6) ◽  
pp. 1721-1734 ◽  
Author(s):  
Antonio C. B. Ramos ◽  
John P. Castagna

Converted‐wave amplitude versus offset (AVO) behavior may be fit with a cubic relationship between reflection coefficient and ray parameter. Attributes extracted using this form can be directly related to elastic parameters with low‐contrast or high‐contrast approximations to the Zoeppritz equations. The high‐contrast approximation has the advantage of greater accuracy; the low‐contrast approximation is analytically simpler. The two coefficients of the low‐contrast approximation are a function of the average ratio of compressional‐to‐shear‐wave velocity (α/β) and the fractional changes in S‐wave velocity and density (Δβ/β and Δρ/ρ). Because of its simplicity, the low‐contrast approximation is subject to errors, particularly for large positive contrasts in P‐wave velocity associated with negative contrasts in S‐wave velocity. However, for incidence angles up to 40° and models confined to |Δβ/β| < 0.25, the errors in both coefficients are relatively small. Converted‐wave AVO crossplotting of the coefficients of the low‐contrast approximation is a useful interpretation technique. The background trend in this case has a negative slope and an intercept proportional to the α/β ratio and the fractional change in S‐wave velocity. For constant α/β ratio, an attribute trace formed by the weighted sum of the coefficients of the low‐contrast approximation provides useful estimates of the fractional change in S‐wave velocity and density. Using synthetic examples, we investigate the sensitivity of these parameters to random noise. Integrated P‐wave and converted‐wave analysis may improve estimation of rock properties by combining extracted attributes to yield fractional contrasts in P‐wave and S‐wave velocities and density. Together, these parameters may provide improved direct hydrocarbon indication and can potentially be used to identify anomalies caused by low gas saturations.

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. U139-U149
Author(s):  
Hongwei Liu ◽  
Mustafa Naser Al-Ali ◽  
Yi Luo

Seismic images can be viewed as photographs for underground rocks. These images can be generated from different reflections of elastic waves with different rock properties. Although the dominant seismic data processing is still based on the acoustic wave assumption, elastic wave processing and imaging have become increasingly popular in recent years. A major challenge in elastic wave processing is shear-wave (S-wave) velocity model building. For this reason, we have developed a sequence of procedures for estimating seismic S-wave velocities and the subsequent generation of seismic images using converted waves. We have two main essential new supporting techniques. The first technique is the decoupling of the S-wave information by generating common-focus-point gathers via application of the compressional-wave (P-wave) velocity on the converted seismic data. The second technique is to assume one common VP/ VS ratio to approximate two types of ratios, namely, the ratio of the average earth layer velocity and the ratio of the stacking velocity. The benefit is that we reduce two unknown ratios into one, so it can be easily scanned and picked in practice. The PS-wave images produced by this technology could be aligned with the PP-wave images such that both can be produced in the same coordinate system. The registration between the PP and PS images provides cross-validation of the migrated structures and a better estimation of underground rock and fluid properties. The S-wave velocity, computed from the picked optimal ratio, can be used not only for generating the PS-wave images, but also to ensure well registration between the converted-wave and P-wave images.


Geophysics ◽  
2000 ◽  
Vol 65 (5) ◽  
pp. 1446-1454 ◽  
Author(s):  
Side Jin ◽  
G. Cambois ◽  
C. Vuillermoz

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.


Geophysics ◽  
1999 ◽  
Vol 64 (2) ◽  
pp. 504-507 ◽  
Author(s):  
Franklyn K. Levin

Tessmer and Behle (1988) show that S-wave velocity can be estimated from surface seismic data if both normal P-wave data and converted‐wave data (P-SV) are available. The relation of Tessmer and Behle is [Formula: see text] (1) where [Formula: see text] is the S-wave velocity, [Formula: see text] is the P-wave velocity, and [Formula: see text] is the converted‐wave velocity. The growing body of converted‐wave data suggest a brief examination of the validity of equation (1) for velocities that vary with depth.


2009 ◽  
Author(s):  
Weifeng Geng ◽  
Aiyuan Hou ◽  
Wenbo Zhang ◽  
Na Lei

Geophysics ◽  
2005 ◽  
Vol 70 (3) ◽  
pp. U29-U36 ◽  
Author(s):  
Mirko van der Baan

Common-midpoint (CMP) sorting of pure-mode data in arbitrarily complex isotropic or anisotropic media leads to moveout curves that are symmetric around zero offset. This greatly simplifies velocity determination of pure-mode data. Common-asymptotic-conversion-point (CACP) sorting of converted-wave data, on the other hand, only centers the apexes of all traveltimes around zero offset in arbitrarily complex but isotropic media with a constant P-wave/S-wave velocity ratio everywhere. A depth-varying CACP sorting may therefore be required to position all traveltimes properly around zero offset in structurally complex areas. Moreover, converted-wave moveout is nearly always asymmetric and nonhyperbolic. Thus, positive and negative offsets need to be processed independently in a 2D line, and 3D data volumes are to be divided in common azimuth gathers. All of these factors tend to complicate converted-wave velocity analysis significantly.


Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. U23-U34
Author(s):  
Raul Cova ◽  
David Henley ◽  
Kristopher A. Innanen

A near-surface velocity model is one of the typical products generated when computing static corrections, particularly in the processing of PP data. Critically refracted waves are the input usually needed for this process. In addition, for the converted PS mode, S-wave near-surface corrections must be applied at the receiver locations. In this case, however, critically refracted S-waves are difficult to identify when using P-wave energy sources. We use the [Formula: see text]-[Formula: see text] representation of the converted-wave data to capture the intercept-time differences between receiver locations. These [Formula: see text]-differences are then used in the inversion of a near-surface S-wave velocity model. Our processing workflow provides not only a set of raypath-dependent S-wave static corrections, but also a velocity model that is based on those corrections. Our computed near-surface S-wave velocity model can be used for building migration velocity models or to initialize elastic full-waveform inversions. Our tests on synthetic and field data provided superior results to those obtained by using a surface-consistent solution.


Author(s):  
Stian Rørheim ◽  
Andreas Bauer ◽  
Rune M Holt

Summary The impact of temperature on elastic rock properties is less-studied and thus less-understood than that of pressure and stress. Thermal effects on dispersion are experimentally observed herein from seismic to ultrasonic frequencies: Young’s moduli and Poisson’s ratios plus P- and S-wave velocities are determined by forced-oscillation (FO) from 1 to 144 Hz and by pulse-transmission (PT) at 500 kHz. Despite being the dominant sedimentary rock type, shales receive less experimental attention than sandstones and carbonates. To our knowledge, no other FO studies on shale at above ambient temperatures exist. Temperature fluctuations are enforced by two temperature cycles from 20 via 40 to 60○C and vice versa. Measured rock properties are initially irreversible but become reversible with increasing number of heating and cooling segments. Rock property-sensitivity to temperature is likewise reduced. It is revealed that dispersion shifts towards higher frequencies with increasing temperature (reversible if decreased), Young’s moduli and P-wave velocity moduli and P-wave velocity maxima occur at 40○C for frequencies below 56 Hz, and S-wave velocities remain unchanged with temperature (if the first heating segment is neglected) at seismic frequencies. In comparison, ultrasonic P- and S-wave velocities are found to decrease with increasing temperatures. Behavioural differences between seismic and ultrasonic properties are attributed to decreasing fluid viscosity with temperature. We hypothesize that our ultrasonic recordings coincide with the transition-phase separating the low- and high-frequency regimes while our seismic recordings are within the low-frequency regime.


2021 ◽  
Vol 11 (4) ◽  
pp. 1809-1822
Author(s):  
Alexander Ogbamikhumi ◽  
Osakpolor Marvellous Omorogieva

AbstractThe application of quantitative interpretation techniques for hydrocarbon prospect evaluation from seismic has become so vital. The effective employment of these techniques is dependent on several factors: the quality of the seismic and well data, sparseness of data, the physics of rock, lithological and structural complexity of the field. This study adopts reflection pattern, amplitude versus offset (AVO), Biot–Gassmann fluid substitution and cross-plot models to understand the physics of the reservoir rocks in the field by examining the sensitivity of the basic rock properties; P-wave velocity, S-wave velocity and density, to variation in lithology and fluid types in the pore spaces of reservoirs. This is to ascertain the applicability of quantitative seismic interpretation techniques to explore hydrocarbon prospect in the studied field. The results of reflection pattern and AVO models revealed that the depth of interest is dominated by Class IV AVO sands with a high negative zero offset reflectivity that reduces with offset. The AVO intercept versus gradient plot indicated that both brine and hydrocarbon bearing sands can be discriminated on seismic. Fluid substitution modelling results revealed that the rock properties will favourably respond to variation in oil saturation, but as little as 5% gas presence will result in huge change in the rock properties, which will remain constant upon further increments of gas saturation, thereby making it difficult to differentiate between economical and sub-economical saturations of gas on seismic data. Rock physics cross-plot models revealed separate cluster points typical of shale presence, brine sands and hydrocarbon bearing sands. Thus, the response of the rock properties to the modelling processes adopted favours the application of quantitative interpretation techniques to evaluate hydrocarbon in the field.


Geophysics ◽  
1996 ◽  
Vol 61 (4) ◽  
pp. 1137-1149 ◽  
Author(s):  
James E. Gaiser

An important step in the simultaneous interpretation or inversion of multicomponent data sets is to quantitatively estimate the ratio of P‐wave velocity to S‐wave velocity [Formula: see text]. In this endeavor, I have developed correlation techniques to determine long‐wavelength components of [Formula: see text] that can lead to more accurate measurements of rock properties and processing parameters. P‐wave reflections are correlated with converted P‐ to S‐wave reflections (or S‐wave reflections) from the same location to determine which events are related to the same subsurface impedance contrasts. Shear waves are transformed (compressed) to P‐wave time via average [Formula: see text] conjugate operators before correlation. Aided by conventional P‐wave velocity information and petrophysical relationships, this technique provides optimal [Formula: see text] estimates in a similar manner that semblance analyses provide stacking velocities. These estimates can be used to transform the entire S‐wave trace to P‐wave time for short‐wavelength amplitude inversion. Also, a target‐oriented correlation analysis quantitatively determines interval [Formula: see text] at a specific horizon or group of horizons. Data from vertical seismic profile (VSP) stacked traces are used to evaluate these techniques. Long‐wavelength average and interval [Formula: see text] estimates obtained from the correlation analyses agree closely with [Formula: see text] results determined from VSP direct‐arrival traveltimes.


Geophysics ◽  
2010 ◽  
Vol 75 (5) ◽  
pp. 75A3-75A13 ◽  
Author(s):  
Douglas J. Foster ◽  
Robert G. Keys ◽  
F. David Lane

We investigate the effects of changes in rock and fluid properties on amplitude-variation-with-offset (AVO) responses. In the slope-intercept domain, reflections from wet sands and shales fall on or near a trend that we call the fluid line. Reflections from the top of sands containing gas or light hydrocarbons fall on a trend approximately parallel to the fluid line; reflections from the base of gas sands fall on a parallel trend on the opposing side of the fluid line. The polarity standard of the seismic data dictates whether these reflections from the top of hydrocarbon-bearing sands are below or above the fluid line. Typically, rock properties of sands and shales differ, and therefore reflections from sand/shale interfaces are also displaced from the fluid line. The distance of these trends from the fluid line depends upon the contrast of the ratio of P-wave velocity [Formula: see text] and S-wave velocity [Formula: see text]. This ratio is a function of pore-fluid compressibility and implies that distance from the fluid line increases with increasing compressibility. Reflections from wet sands are closer to the fluid line than hydrocarbon-related reflections. Porosity changes affect acoustic impedance but do not significantly impact the [Formula: see text] contrast. As a result, porosity changes move the AVO response along trends approximately parallel to the fluid line. These observations are useful for interpreting AVO anomalies in terms of fluids, lithology, and porosity.


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