scholarly journals Three-component amplitude versus offset analysis

1989 ◽  
Vol 20 (2) ◽  
pp. 257
Author(s):  
D.R. Miles ◽  
G. Gassaway ◽  
L. Bennett ◽  
R. Brown
Keyword(s):  
Seismic Data ◽  
P Wave ◽  
S Wave ◽  
Converted Wave ◽  
P Waves ◽  
S Waves ◽  
Avo Analysis ◽  
Avo Inversion ◽  
Amplitude Versus Offset ◽  
Converted Waves

Three-component (3-C) amplitude versus offset (AVO) inversion is the AVO analysis of the three major energies in the seismic data, P-waves, S-waves and converted waves. For each type of energy the reflection coefficients at the boundary are a function of the contrast across the boundary in velocity, density and Poisson's ratio, and of the angle of incidence of the incoming wave. 3-C AVO analysis exploits these relationships to analyse the AVO changes in the P, S, and converted waves. 3-C AVO analysis is generally done on P, S, and converted wave data collected from a single source on 3-C geophones. Since most seismic sources generate both P and S-waves, it follows that most 3-C seismic data may be used in 3-C AVO inversion. Processing of the P-wave, S-wave and converted wave gathers is nearly the same as for single-component P-wave gathers. In split-spread shooting, the P-wave and S-wave energy on the radial component is one polarity on the forward shot and the opposite polarity on the back shot. Therefore to use both sides of the shot, the back shot must be rotated 180 degrees before it can be stacked with the forward shot. The amplitude of the returning energy is a function of all three components, not just the vertical or radial, so all three components must be stacked for P-waves, then for S-waves, and finally for converted waves. After the gathers are processed, reflectors are picked and the amplitudes are corrected for free-surface effects, spherical divergence and the shot and geophone array geometries. Next the P and S-wave interval velocities are calculated from the P and S-wave moveouts. Then the amplitude response of the P and S-wave reflections are analysed to give Poisson's ratio. The two solutions are then compared and adjusted until they match each other and the data. Three-component AVO inversion not only yields information about the lithologies and pore-fluids at a specific location; it also provides the interpreter with good correlations between the P-waves and the S-waves, and between the P and converted waves, thus greatly expanding the value of 3-C seismic data.

Examining the processing differences between P and P-S waves in a Rocky Mountain Foothills model

2014 ◽  
Vol 54 (2) ◽  
pp. 504
Author(s):  
Sanjeev Rajput ◽  
Michael Ring
Keyword(s):  
Rocky Mountain ◽  
P Wave ◽  
S Wave ◽  
Converted Wave ◽  
Wave Source ◽  
Depth Migration ◽  
S Waves ◽  
Full Waveform ◽  
Fluid Saturation ◽  
Converted Waves

For the past two decades, most of the shear-wave (S-wave) or converted wave (P-S) acquisitions were performed with P-wave source by making the use of downgoing P-waves converting to upgoing S-waves at the mode conversion boundaries. The processing of converted waves requires studying asymmetric reflection at the conversion point, difference in geometries and conditions of source and receiver, and the partitioning of energy into orthogonally polarised components. Interpretation of P-S sections incorporates the identification of P-S waves, full waveform modeling, correlation with P-wave sections and depth migration. The main applications of P-S wave imaging are to obtain a measure of subsurface S-wave properties relating to rock type and fluid saturation (in addition to the P-wave values), imaging through gas clouds and shale diapers, and imaging interfaces with low P-wave contrast but significant S-wave changes. This study examines the major differences in processing of P and P-S wave surveys and the feasibility of identifying converted mode reflections by P-wave sources in anisotropic media. Two-dimensional synthetic seismograms for a realistic rocky mountain foothills model were studied. A Kirchhoff-based technique that includes anisotropic velocities is used for depth migration of converted waves. The results from depth imaging show that P-S section help in distinguishing amplitude associated with hydrocarbons from those caused by localised stratigraphic changes. In addition, the full waveform elastic modeling is useful in finding an appropriate balance between capturing high-quality P-wave data and P-S data challenges in a survey.

Examining the processing differences between P and P-S waves in a Rocky Mountain Foothills model

2014 ◽  
Vol 54 (2) ◽  
pp. 536
Author(s):  
Sanjeev Rajput ◽  
Michael Ring
Keyword(s):  
Rocky Mountain ◽  
P Wave ◽  
S Wave ◽  
Converted Wave ◽  
Wave Source ◽  
Depth Migration ◽  
S Waves ◽  
Full Waveform ◽  
Fluid Saturation ◽  
Converted Waves

For the past two decades, most of the shear-wave (S-wave) or converted wave (P-S) acquisitions were performed with P-wave source by making the use of downgoing P-waves converting to upgoing S-waves at the mode conversion boundaries. The processing of converted waves requires studying asymmetric reflection at the conversion point, difference in geometries and conditions of source and receiver, and the partitioning of energy into orthogonally polarised components. Interpretation of P-S sections incorporates the identification of P-S waves, full waveform modeling, correlation with P-wave sections and depth migration. The main applications of P-S wave imaging are to obtain a measure of subsurface S-wave properties relating to rock type and fluid saturation (in addition to the P-wave values), imaging through gas clouds and shale diapers, and imaging interfaces with low P-wave contrast but significant S-wave changes. This study examines the major differences in processing of P and P-S wave surveys and the feasibility of identifying converted mode reflections by P-wave sources in anisotropic media. Two-dimensional synthetic seismograms for a realistic rocky mountain foothills model were studied. A Kirchhoff-based technique that includes anisotropic velocities is used for depth migration of converted waves. The results from depth imaging show that P-S section help in distinguishing amplitude associated with hydrocarbons from those caused by localised stratigraphic changes. In addition, the full waveform elastic modeling is useful in finding an appropriate balance between capturing high-quality P-wave data and P-S data challenges in a survey.

A simple method for resolving large converted‐wave (P-SV) statics

Geophysics ◽  
1993 ◽  
Vol 58 (3) ◽  
pp. 429-433 ◽  
Author(s):  
Peter W. Cary ◽  
David W. S. Eaton
Keyword(s):  
P Wave ◽  
S Wave ◽  
Converted Wave ◽  
P Waves ◽  
Simple Method ◽  
Near Surface ◽  
S Waves ◽  
Static Solutions ◽  
Surface Fluctuations

The processing of converted‐wave (P-SV) seismic data requires certain special considerations, such as commonconversion‐point (CCP) binning techniques (Tessmer and Behle, 1988) and a modified normal moveout formula (Slotboom, 1990), that makes it different for processing conventional P-P data. However, from the processor’s perspective, the most problematic step is often the determination of residual S‐wave statics, which are commonly two to ten times greater than the P‐wave statics for the same location (Tatham and McCormack, 1991). Conventional residualstatics algorithms often produce numerous cycle skips when attempting to resolve very large statics. Unlike P‐waves, the velocity of S‐waves is virtually unaffected by near‐surface fluctuations in the water table (Figure 1). Hence, the P‐wave and S‐wave static solutions are largely unrelated to each other, so it is generally not feasible to approximate the S‐wave statics by simply scaling the known P‐wave static values (Anno, 1986).

Shear‐wave velocity and density estimation from PS-wave AVO analysis: Application to an OBS dataset from the North Sea

Geophysics ◽  
2000 ◽  
Vol 65 (5) ◽  
pp. 1446-1454 ◽  
Author(s):  
Side Jin ◽  
G. Cambois ◽  
C. Vuillermoz
Keyword(s):  
Wave Velocity ◽  
North Sea ◽  
Random Noise ◽  
P Wave ◽  
S Wave ◽  
Data Set ◽  
Avo Analysis ◽  
The North ◽  
Avo Inversion ◽  
The North Sea

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.

Numerical simulation of azimuthal acoustic logging in a borehole penetrating a rock formation boundary

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. D283-D291 ◽  
Author(s):  
Peng Liu ◽  
Wenxiao Qiao ◽  
Xiaohua Che ◽  
Xiaodong Ju ◽  
Junqiang Lu ◽  
...  
Keyword(s):  
Domain Model ◽  
P Wave ◽  
S Wave ◽  
Angle Variation ◽  
P Waves ◽  
Acoustic Logging ◽  
S Waves ◽  
Rock Formation ◽  
Logging Tool ◽  
Difference Time

We have developed a new 3D acoustic logging tool (3DAC). To examine the azimuthal resolution of 3DAC, we have evaluated a 3D finite-difference time-domain model to simulate a case in which the borehole penetrated a rock formation boundary when the tool worked at the azimuthal-transmitting-azimuthal-receiving mode. The results indicated that there were two types of P-waves with different slowness in waveforms: the P-wave of the harder rock (P1) and the P-wave of the softer rock (P2). The P1-wave can be observed in each azimuthal receiver, but the P2-wave appears only in the azimuthal receivers toward the softer rock. When these two types of rock are both fast formations, two types of S-waves also exist, and they have better azimuthal sensitivity compared with P-waves. The S-wave of the harder rock (S1) appears only in receivers toward the harder rock, and the S-wave of the softer rock (S2) appears only in receivers toward the softer rock. A model was simulated in which the boundary between shale and sand penetrated the borehole but not the borehole axis. The P-wave of shale and the S-wave of sand are azimuthally sensitive to the azimuth angle variation of two formations. In addition, waveforms obtained from 3DAC working at the monopole-transmitting-azimuthal-receiving mode indicate that the corresponding P-waves and S-waves are azimuthally sensitive, too. Finally, we have developed a field example of 3DAC to support our simulation results: The azimuthal variation of the P-wave slowness was observed and can thus be used to reflect the azimuthal heterogeneity of formations.

Transformation to zero offset for mode‐converted waves

Geophysics ◽  
1992 ◽  
Vol 57 (3) ◽  
pp. 474-477 ◽  
Author(s):  
Mohammed Alfaraj ◽  
Ken Larner
Keyword(s):  
Seismic Data ◽  
Constant Velocity ◽  
Reflection Point ◽  
P Waves ◽  
S Waves ◽  
Nmo Correction ◽  
Converted Waves ◽  
Zero Offset ◽  
Correct Data

The transformation to zero offset (TZO) of prestack seismic data for a constant‐velocity medium is well understood and is readily implemented when dealing with either P‐waves or S‐waves. TZO is achieved by inserting a dip moveout (DMO) process to correct data for the influence of dip, either before or after normal moveout (NMO) correction (Hale, 1984; Forel and Gardner, 1988). The TZO process transforms prestack seismic data in such a way that common‐midpoint (CMP) gathers are closer to being common reflection point gathers after the transformation.

Downhole seismic imaging of a massive sulfide orebody with mode‐converted waves, Halfmile lake, New Brunswick, Canada

Geophysics ◽  
2004 ◽  
Vol 69 (2) ◽  
pp. 318-329 ◽  
Author(s):  
Gilles Bellefleur ◽  
Christof Müller ◽  
David Snyder ◽  
Larry Matthews
Keyword(s):  
New Brunswick ◽  
Seismic Data ◽  
Massive Sulfide ◽  
Data Migration ◽  
P Waves ◽  
S Waves ◽  
Additional Imaging ◽  
Mineralized Zone ◽  
Converted Waves ◽  
Host Rocks

Multioffset, multiazimuth downhole seismic data were acquired at Halfmile lake, New Brunswick, to image known massive sulfide lenses and to investigate the potential existence of a steeply dipping mineralized zone connecting them. The massive sulfide lenses, which have significantly higher elastic impedances than host rocks, produce strong scattering. The downhole seismic data show prominent scattered (P‐P and S‐S) and mode‐converted (P‐S and S‐P) waves originating from the deposit. Such complex scattering from massive sulfide ore was not observed previously in vertical seismic profiling data. Migration of the scattered and mode‐converted waves from several shot points imaged different parts of the deepest lens. The scattered S‐waves and mode‐converted waves provide additional imaging capabilities that should be considered when selecting downhole seismic methods for mining exploration.

Bayesian closed-skew Gaussian inversion of seismic AVO data for elastic material properties

Geophysics ◽  
2010 ◽  
Vol 75 (1) ◽  
pp. R1-R11 ◽  
Author(s):  
Omid Karimi ◽  
Henning Omre ◽  
Mohsen Mohammadzadeh
Keyword(s):  
Elastic Material ◽  
Material Properties ◽  
P Wave ◽  
S Wave ◽  
High Dimensions ◽  
Seismic Amplitude ◽  
The North ◽  
Avo Inversion ◽  
Amplitude Versus Offset ◽  
The North Sea

Bayesian closed-skew Gaussian inversion is defined as a generalization of traditional Bayesian Gaussian inversion, which is used frequently in seismic amplitude-versus-offset (AVO) inversion. The new model captures skewness in the variables of interest; hence, the posterior model for log-transformed elastic material properties given seismic AVO data might be a skew probability density function. The model is analytically tractable, and this makes it applicable in high-dimensional 3D inversion problems. Assessment of the posterior models in high dimensions requires numerical approximations, however. The Bayesian closed-skew Gaussian inversion approach has been applied on real elastic material properties from a well in the Sleipner field in the North Sea. A comparison with results from traditional Bayesian Gaussian inversion shows that the mean square error of predictions of P-wave and S-wave velocities are reduced by a factor of two, although somewhat less for density predictions.

Imaging beneath a high‐velocity layer using converted waves

Geophysics ◽  
1992 ◽  
Vol 57 (11) ◽  
pp. 1444-1452 ◽  
Author(s):  
Guy W. Purnell
Keyword(s):  
High Velocity ◽  
Energy Partitioning ◽  
P Wave ◽  
Converted Wave ◽  
P Waves ◽  
Lower Velocity ◽  
S Waves ◽  
High Velocity Layer ◽  
The Waves ◽  
Velocity Layer

High‐velocity layers (HVLs) often hinder seismic imaging of deeper reflectors using conventional techniques. A major factor is often the unusual energy partitioning of waves incident at an HVL boundary from lower‐velocity material. Using elastic physical modeling, I demonstrate that one effect of this factor is to limit the range of dips beneath an HVL that can be imaged using unconverted P‐wave arrivals. At the same time, however, partitioning may also result in P‐waves outside the HVL coupling efficiently with S‐waves inside. By exploiting some of the waves that convert upon transmission into and/or out of the physical‐model HVL, I am able to image a much broader range of underlying dips. This is accomplished by acoustic migration tailored (via the migration velocities used) for selected families of converted‐wave arrivals.

Converted-wave model building and imaging based on common-focus-point methodology

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. U139-U149
Author(s):  
Hongwei Liu ◽  
Mustafa Naser Al-Ali ◽  
Yi Luo
Keyword(s):  
Elastic Wave ◽  
Wave Velocity ◽  
Seismic Data ◽  
Model Building ◽  
P Wave ◽  
Rock Properties ◽  
S Wave ◽  
Converted Wave ◽  
Seismic Images ◽  
Focus Point

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.

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