Acquiring S‐wave velocity using VSP converted wave of P‐wave source

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.

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

Geophysics ◽

10.1190/geo2019-0549.1 ◽

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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Estimating shear‐wave velocities from P-wave and converted‐wave data

Geophysics ◽

10.1190/1.1444556 ◽

1999 ◽

Vol 64 (2) ◽

pp. 504-507 ◽

Cited By ~ 1

Author(s):

Franklyn K. Levin

Keyword(s):

Wave Velocity ◽

Seismic Data ◽

P Wave ◽

S Wave ◽

Converted Wave ◽

Wave Data ◽

Wave Velocities ◽

Shear Wave Velocities ◽

P Wave Velocity ◽

Growing Body

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.

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Elastic-wavefield interferometry using P-wave source VSPs at the Wamsutter field, Wyoming

Geophysics ◽

10.1190/geo2011-0162.1 ◽

2012 ◽

Vol 77 (2) ◽

pp. Q27-Q36 ◽

Cited By ~ 1

Author(s):

James Gaiser ◽

Ivan Vasconcelos ◽

Rosemarie Geetan ◽

John Faragher

Keyword(s):

Stationary Phase ◽

Wave Velocity ◽

P Wave ◽

Phase Point ◽

S Wave ◽

Wave Source ◽

S Waves ◽

Wave Splitting ◽

Zero Offset ◽

Tube Wave

In this study, elastic-wavefield interferometry was used to recover P- and S-waves from the 3D P-wave vibrator VSP data at Wamsutter field in Wyoming. S-wave velocity and birefringence is of particular interest for the geophysical objectives of lithology discrimination and fracture characterization in naturally fractured tight gas sand reservoirs. Because we rely on deconvolution interferometry for retrieving interreceiver P- and S-waves in the subsurface, the output fields are suitable for high-resolution, local reservoir characterization. In 1D media where the borehole is nearly vertical, data at the stationary-phase point is not conducive to conventional interferometry. Strong tube-wave noise generated by physical sources near the borehole interfere with S-wave splitting analyses. Also, converted P- to S-wave (PS-wave) polarity reversals occur at zero offset and cancel their recovery. We developed methods to eliminate tube-wave noise by removing physical sources at the stationary-phase point and perturbing the integration path in the integrand based on P-wave NMO velocity of the direct-arrival. This results in using nonphysical energy outside a Fresnel radius that could not have propagated between receivers. To limit the response near the stationary-phase point, we also applied a weighting condition to suppress energy from large offsets. For PS-waves, a derivative-like operator was applied to the physical sources at zero offset in the form of a polarity reversal. These methods resulted in effectively recovering P-wave dipole and PS-wave quadrupole pseudosource VSPs. The retrieved wavefields kinematically correspond to a vertical incidence representation of reflectivity/transmissivity and can be used for conventional P- and S-wave velocity analyses. Four-component PS-wave VSPs retrieve S-wave splitting in transmitted converted waves that provide calibration for PS-wave and P-wave azimuthal anisotropy measurements from surface-seismic data.

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

The APPEA Journal ◽

10.1071/aj13077 ◽

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.

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Some comments on common-asymptotic-conversion-point (CACP) sorting of converted-wave data in isotropic, laterally inhomogeneous media

Geophysics ◽

10.1190/1.1925750 ◽

2005 ◽

Vol 70 (3) ◽

pp. U29-U36 ◽

Cited By ~ 2

Author(s):

Mirko van der Baan

Keyword(s):

Wave Velocity ◽

Velocity Ratio ◽

P Wave ◽

Pure Mode ◽

S Wave ◽

Converted Wave ◽

Wave Data ◽

Conversion Point ◽

Isotropic Media ◽

Zero Offset

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.

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Computing near-surface velocity models for S-wave static corrections using raypath interferometry

Geophysics ◽

10.1190/geo2017-0340.1 ◽

2018 ◽

Vol 83 (3) ◽

pp. U23-U34

Author(s):

Raul Cova ◽

David Henley ◽

Kristopher A. Innanen

Keyword(s):

Wave Velocity ◽

Velocity Model ◽

P Wave ◽

Surface Velocity ◽

S Wave ◽

Converted Wave ◽

Near Surface ◽

Velocity Models ◽

Consistent Solution ◽

Static Corrections

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.

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

The APPEA Journal ◽

10.1071/aj13109 ◽

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.

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Numerical and Theoretical Investigation on the Origin of the Multiple Peaks of the H/V Ratio Curve

10.5194/egusphere-egu21-6904 ◽

2021 ◽

Author(s):

Wanbo Xiao ◽

Siqi Lu ◽

Yanbin Wang

Keyword(s):

Rayleigh Wave ◽

Wave Velocity ◽

Subsurface Layer ◽

P Wave ◽

Theoretical Formula ◽

S Wave ◽

Multiple Peaks ◽

Ratio Curve ◽

Multiple Layer ◽

Wave Resonance

Despite the popularity of the horizontal to vertical spectral ratio (HVSR) method in site effect studies, the origin of the H/V peaks has been controversial since this method was proposed. Many previous studies mainly focused on the explanation of the first or single peak of the H/V ratio, trying to distinguish between the two hypotheses &#8212; the S-wave resonance and ellipticity of Rayleigh wave. However, it is common both in numerical simulations and practical experiments that the H/V ratio exhibits multiple peaks, which is essential to explore the origin of the H/V peaks.The cause for the multiple H/V peaks has not been clearly figured out, and once was simply explained as the result of multi subsurface layers. Therefore, we adopted numerical method to simulate the ambient noise in various layered half-space models and calculated the H/V ratio curves for further comparisons. The peak frequencies of the H/V curves accord well with the theoretical frequencies of S-wave resonance in two-layer models, whose frequencies only depend on the S wave velocity and the thickness of the subsurface layer. The same is true for models with varying model parameters. Besides, the theoretical formula of the S-wave resonance in multiple-layer models is proposed and then supported by numerical investigations as in the cases of two-layer models. We also extended the S-wave resonance to P-wave resonance and found that its theoretical frequencies fit well with the V/H peaks, which could be an evidence to support the S-wave resonance theory from a new perspective. By contrast, there are obvious differences between the higher orders of the H/V ratio peaks and the higher orders of Rayleigh wave ellipticity curves both in two-layer and multiple-layer models. The Rayleigh wave ellipticity curves are found to be sensitive to the Poisson&#8217;s ratio and the thickness of the subsurface layer, so the variation of the P wave velocity can affect the peak frequencies of the Rayleigh wave ellipticity curves while the H/V peaks show slight change. The Rayleigh wave ellipticity theory is thus proved to be inappropriate for the explanation of the multiple H/V peaks, while the possible effects of the Rayleigh wave on the fundamental H/V peak still cannot be excluded.Based on the analyses above, we proposed a new evidence to support the claim that the peak frequencies of the H/V ratio curve, except the fundamental peaks, are caused by S-wave resonance. The relationship between the P-wave resonance and the V/H peaks may also find further application.

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Using Seismic Data to Predict Shale Pore Pressure and Overpressure Sweet Spots: A Case Study from the Lower Silurian Longmaxi Formation in Sichuan Basin, China

10.2118/208098-ms ◽

2021 ◽

Author(s):

Sheng Chen ◽

Qingcai Zeng ◽

Xiujiao Wang ◽

Qing Yang ◽

Chunmeng Dai ◽

...

Keyword(s):

Prediction Model ◽

Wave Velocity ◽

Shale Gas ◽

Seismic Data ◽

P Wave ◽

Formation Pressure ◽

S Wave ◽

P Wave Velocity ◽

New Formation ◽

Sweet Spots

Abstract Practices of marine shale gas exploration and development in south China have proved that formation overpressure is the main controlling factor of shale gas enrichment and an indicator of good preservation condition. Accurate prediction of formation pressure before drilling is necessary for drilling safety and important for sweet spots predicting and horizontal wells deploying. However, the existing prediction methods of formation pore pressures all have defects, the prediction accuracy unsatisfactory for shale gas development. By means of rock mechanics analysis and related formulas, we derived a formula for calculating formation pore pressures. Through regional rock physical analysis, we determined and optimized the relevant parameters in the formula, and established a new formation pressure prediction model considering P-wave velocity, S-wave velocity and density. Based on regional exploration wells and 3D seismic data, we carried out pre-stack seismic inversion to obtain high-precision P-wave velocity, S-wave velocity and density data volumes. We utilized the new formation pressure prediction model to predict the pressure and the spatial distribution of overpressure sweet spots. Then, we applied the measured pressure data of three new wells to verify the predicted formation pressure by seismic data. The result shows that the new method has a higher accuracy. This method is qualified for safe drilling and prediction of overpressure sweet spots for shale gas development, so it is worthy of promotion.

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