Application of Sh S-Wave Data in Lithologic Trap Identification

2021 ◽  
Author(s):  
Jiru Guo ◽  
Zhiwen Deng ◽  
Junyong Zhang ◽  
Wei Tan ◽  
Guowen Chen ◽  
...  
Keyword(s):  
Qaidam Basin ◽  
Research Area ◽  
P Wave ◽  
Sh Wave ◽  
S Wave ◽  
Reservoir Prediction ◽  
Wave Data ◽  
Petrophysical Modeling ◽  
Lithology Prediction ◽  
Wave Matching

Abstract The biogas lithologic reservoirs in Sanhu Area of the Qaidam Basin has a broad exploration prospect, however, the demands of structural implementation and reservoir prediction can hardly be met with the existing P-wave seismic data due to the thin thickness of single sandstone layers, the rapid lateral changes and the low prediction accuracy of lithologic reservoirs. The SH-wave data has a higher resolution ability in lithology prediction. I can better reflect the lateral change features of formations. Because few SH-wave logging data are available and they are in accurate in the current study area, the SH-wave velocity is estimated through petrophysical modeling and the calibration and horizon interpretation of the SH-wave data are realized combined with the P- and SH-wave matching technology. Through the inversion of S-wave data,the lithological distribution of formations are predicted in combination with the comrehensive analysis of P-wave data, which provides a favorable basis for the survey of lithologic gas reservoir in the research area and achieves a good good result. In this way,a set of reservoir prediction methods and processes suitable for the shallow biogas lithological exploration in the Sanhu Area have formed initially.

Direct shear-wave seismic survey in Sanhu area, Qaidam Basin, west China

2022 ◽  
Vol 41 (1) ◽  
pp. 47-53
Author(s):  
Zhiwen Deng ◽  
Rui Zhang ◽  
Liang Gou ◽  
Shaohua Zhang ◽  
Yuanyuan Yue ◽  
...  
Keyword(s):  
Shear Wave ◽  
Reservoir Characterization ◽  
Qaidam Basin ◽  
P Wave ◽  
Data Sets ◽  
Direct Shear ◽  
Subsurface Structure ◽  
S Wave ◽  
West China ◽  
Wave Data

The formation containing shallow gas clouds poses a major challenge for conventional P-wave seismic surveys in the Sanhu area, Qaidam Basin, west China, as it dramatically attenuates seismic P-waves, resulting in high uncertainty in the subsurface structure and complexity in reservoir characterization. To address this issue, we proposed a workflow of direct shear-wave seismic (S-S) surveys. This is because the shear wave is not significantly affected by the pore fluid. Our workflow includes acquisition, processing, and interpretation in calibration with conventional P-wave seismic data to obtain improved subsurface structure images and reservoir characterization. To procure a good S-wave seismic image, several key techniques were applied: (1) a newly developed S-wave vibrator, one of the most powerful such vibrators in the world, was used to send a strong S-wave into the subsurface; (2) the acquired 9C S-S data sets initially were rotated into SH-SH and SV-SV components and subsequently were rotated into fast and slow S-wave components; and (3) a surface-wave inversion technique was applied to obtain the near-surface shear-wave velocity, used for static correction. As expected, the S-wave data were not affected by the gas clouds. This allowed us to map the subsurface structures with stronger confidence than with the P-wave data. Such S-wave data materialize into similar frequency spectra as P-wave data with a better signal-to-noise ratio. Seismic attributes were also applied to the S-wave data sets. This resulted in clearly visible geologic features that were invisible in the P-wave data.

Anisotropy effects in P-wave and SH-wave stacking velocities contain information on lithology

Geophysics ◽  
1986 ◽  
Vol 51 (3) ◽  
pp. 661-672 ◽  
Author(s):  
D. F. Winterstein
Keyword(s):  
Seismic Data ◽  
P Wave ◽  
Sh Wave ◽  
S Wave ◽  
Velocity Anisotropy ◽  
Midland Basin ◽  
Wave Data ◽  
Event Times ◽  
Interval Velocities ◽  
Constituent Layer

Depths calculated from S-wave stacking velocities and event times almost always exceed actual depths, sometimes by as much as 25 percent. In contrast, depths from corresponding P-wave information are often within 10 percent of actual depths. Discrepancies in depths calculated from P- and S-wave data are attributed to velocity anisotropy, a property of sedimentary rocks that noticeably affects S-wave moveout curves but leaves the P-wave relatively unaffected. Two careful studies show that discrepancies in depths, and hence in constituent layer thicknesses, correlate with lithology. Discrepancies ranged from an average of 13 percent (Midland basin) to greater than 40 percent (Paloma field) in shales, but were within expected errors in massive sandstones or carbonates. Hence anisotropy effects are indicators of lithology. Analysis of seismic data involved determining interval velocities from stacking velocities, calculating layer thicknesses, and then comparing layer thicknesses from S-wave data with thicknesses from P-wave data. When the S-wave thicknesses were significantly greater than the P-wave (i.e., outside the range of expected errors), I concluded the layer was anisotropic. I illustrate the technique with data from the Paloma field project of the Conoco Shear Wave Group Shoot.

EXTRACTING SUB-SURFACE INFORMATION FROM LONG OFFSET P-WAVE DATA—A CHEAPER ALTERNATIVE TO MULTICOMPONENT OBC FOR EXPLORATION?

2002 ◽  
Vol 42 (1) ◽  
pp. 627
Author(s):  
R.G. Williams ◽  
G. Roberts ◽  
K. Hawkins
Keyword(s):  
Seismic Energy ◽  
Higher Order ◽  
P Wave ◽  
S Wave ◽  
Additional Information ◽  
Wave Data ◽  
Wave Velocities ◽  
Avo Inversion ◽  
Long Offset ◽  
Multicomponent Data

Seismic energy that has been mode converted from pwave to s-wave in the sub-surface may be recorded by multi-component surveys to obtain information about the elastic properties of the earth. Since the energy converted to s-wave is missing from the p-wave an alternative to recording OBC multi-component data is to examine p-wave data for the missing energy. Since pwave velocities are generally faster than s-wave velocities, then for a given reflection point the converted s-wave signal reaches the surface at a shorter offset than the equivalent p-wave information. Thus, it is necessary to record longer offsets for p-wave data than for multicomponent data in order to measure the same information.A non-linear, wide-angle (including post critical) AVO inversion has been developed that allows relative changes in p-wave velocities, s-wave velocities and density to be extracted from long offset p-wave data. To extract amplitudes at long offsets for this inversion it is necessary to image the data correctly, including correcting for higher order moveout and possibly anisotropy if it is present.The higher order moveout may itself be inverted to yield additional information about the anisotropy of the sub-surface.

Three-parameter prestack seismic inversion based on L1-2 minimization

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. R753-R766 ◽  
Author(s):  
Lingqian Wang ◽  
Hui Zhou ◽  
Yufeng Wang ◽  
Bo Yu ◽  
Yuanpeng Zhang ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Seismic Inversion ◽  
Thin Layers ◽  
P Wave ◽  
S Wave ◽  
Reservoir Prediction ◽  
Linear Inversion ◽  
Prestack Inversion ◽  
The Difference ◽  
Predictive Filtering

Prestack inversion has become a common approach in reservoir prediction. At present, the critical issue in the application of seismic inversion is the estimation of elastic parameters in the thin layers and weak reflectors. To improve the resolution and the accuracy of the inversion results, we introduced the difference of [Formula: see text] and [Formula: see text] norms as a nearly unbiased approximation of the sparsity of a vector, denoted as the [Formula: see text] norm, to the prestack inversion. The nonconvex penalty function of the [Formula: see text] norm can be decomposed into two convex subproblems via the difference of convex algorithm, and each subproblem can be solved efficiently by the alternating direction method of multipliers. Compared with the [Formula: see text] norm regularization, the [Formula: see text] minimization can reconstruct reflectivities more accurately. In addition, the [Formula: see text]-[Formula: see text] predictive filtering was introduced to guarantee the lateral continuity of the location and the amplitude of the reflectivity series. The generalized linear inversion and [Formula: see text]-[Formula: see text] predictive filtering are combined for stable elastic impedance inversion results, and three parameters of P-wave velocity, S-wave velocity, and density can be inverted with the Bayesian linearized amplitude variation with offset inversion. The inversion results of synthetic and real seismic data demonstrate that the proposed method can effectively improve the resolution and accuracy of the inversion results.

P-wave and S-wave azimuthal anisotropy at a naturally fractured gas reservoir, Bluebell‐Altamont Field, Utah

Geophysics ◽  
1999 ◽  
Vol 64 (4) ◽  
pp. 1312-1328 ◽  
Author(s):  
Heloise B. Lynn ◽  
Wallace E. Beckham ◽  
K. Michele Simon ◽  
C. Richard Bates ◽  
M. Layman ◽  
...  
Keyword(s):  
Azimuthal Anisotropy ◽  
P Wave ◽  
Fracture Density ◽  
Wave Reflections ◽  
S Wave ◽  
Gas Reservoir ◽  
Green River ◽  
Wave Data ◽  
Reflection Data ◽  
Naturally Fractured

Reflection P- and S-wave data were used in an investigation to determine the relative merits and strengths of these two data sets to characterize a naturally fractured gas reservoir in the Tertiary Upper Green River formation. The objective is to evaluate the viability of P-wave seismic to detect the presence of gas‐filled fractures, estimate fracture density and orientation, and compare the results with estimates obtained from the S-wave data. The P-wave response to vertical fractures must be evaluated at different source‐receiver azimuths (travelpaths) relative to fracture strike. Two perpendicular lines of multicomponent reflection data were acquired approximately parallel and normal to the dominant strike of Upper Green River fractures as obtained from outcrop, core analysis, and borehole image logs. The P-wave amplitude response is extracted from prestack amplitude variation with offset (AVO) analysis, which is compared to isotropic‐model AVO responses of gas sand versus brine sand in the Upper Green River. A nine‐component vertical seismic profile (VSP) was also obtained for calibration of S-wave reflections with P-wave reflections, and support of reflection S-wave results. The direction of the fast (S1) shear‐wave component from the reflection data and the VSP coincides with the northwest orientation of Upper Green River fractures, and the direction of maximum horizontal in‐situ stress as determined from borehole ellipticity logs. Significant differences were observed in the P-wave AVO gradient measured parallel and perpendicular to the orientation of Upper Green River fractures. Positive AVO gradients were associated with gas‐producing fractured intervals for propagation normal to fractures. AVO gradients measured normal to fractures at known waterwet zones were near zero or negative. A proportional relationship was observed between the azimuthal variation of the P-wave AVO gradient as measured at the tops of fractured intervals, and the fractional difference between the vertical traveltimes of split S-waves (the “S-wave anisotropy”) of the intervals.

Comparison of imaging in anisotropic media using P‐wave and S‐wave data

1998 ◽  
Author(s):  
M. Graziella Kirtland Grech ◽  
J. Helen Isaac ◽  
Don C. Lawton
Keyword(s):  
Anisotropic Media ◽  
P Wave ◽  
S Wave ◽  
Wave Data

scholarly journals Physical and numerical modeling of tuning and diffraction in azimuthally anisotropic media

Geophysics ◽  
2000 ◽  
Vol 65 (5) ◽  
pp. 1613-1621 ◽  
Author(s):  
Richard L. Gibson ◽  
Stephen Theophanis ◽  
M. Nafi Toksöz
Keyword(s):  
Numerical Modeling ◽  
Fractured Reservoirs ◽  
Homogeneous Model ◽  
Azimuthal Anisotropy ◽  
P Wave ◽  
Orthorhombic Symmetry ◽  
Fractured Reservoir ◽  
Sh Wave ◽  
Wave Data ◽  
Ray Methods

Fractured reservoirs are an important target for exploration and production geophysics, and the azimuthal anisotropy often associated with these reservoirs can strongly influence seismic wave propagation. We created a physical model of a fractured reservoir to simulate some of these propagation effects. The reservoir is represented by a phenolite disk that is thin with respect to the elastic wavelengths in the experiment, creating model dimensions that are representative of realistic reservoirs. Phenolite is strongly anisotropic with orthorhombic symmetry, which suggests that azimuthal amplitude versus offset (AVO) effects should be obvious in data. We acquired both SH- and P-wave data in common‐offset gathers with a near offset and a far offset and found that although the SH-wave data show clear azimuthal variations in AVO, the P-wave signals show no apparent changes with azimuth. We then applied numerical modeling to analyze the data. Because ray methods cannot model diffractions from the disk edge, we first used a ray‐Born technique to simulate variations in waveforms associated with such scattering. The synthetic seismograms reproduced variations in the SH-wave waveforms accurately, though the amplitude contrast between acquisition azimuths was overestimated. Assuming a laterally homogeneous model, we then applied ray methods to simulate tuning effects in SH- and P-wave data and confirmed that in spite of the large contrasts in elastic properties, the tuning of the P-wave reflections from the thin disk changed so there was negligible contrast in AVO with azimuth. Models of field scale reservoirs showed that the same effects could be expected for field applications.

Reply by the author to D. F. Winterstein

Geophysics ◽  
1985 ◽  
Vol 50 (11) ◽  
pp. 1793-1793
Author(s):  
R. A. Ensley
Keyword(s):  
P Wave ◽  
S Wave ◽  
Wave Data

Mr. Winterstein is entirely correct in pointing out that the S‐wave data presented in my paper were a brute stack. In addition, the P‐wave data presented were also a brute stack.

Combination of P and S data for the determination of earthquake focal mechanism

1971 ◽  
Vol 61 (6) ◽  
pp. 1655-1673 ◽  
Author(s):  
Umesh Chandra
Keyword(s):  
Focal Mechanism ◽  
P Wave ◽  
Wave Polarization ◽  
S Wave ◽  
Polarization Data ◽  
Wave Data ◽  
Earthquake Focal Mechanism ◽  
First Motion ◽  
Depth Ranges

abstract A method has been proposed for the combination of P-wave first-motion directions and S-wave polarization data for the numerical determination of earthquake focal mechanism. The method takes into account the influence of nearness of stations with inconsistent P-wave polarity observations, with respect to the assumed nodal planes. The mechanism solutions for six earthquakes selected from different geographic locations and depth ranges have been determined. Equal area projections of the nodal planes together with the P-wave first-motion and S-wave polarization data are presented for each earthquake. The quality of resolution of nodal plane determination on the basis of P-wave data, S-wave polarization, and the combination of P and S-wave data according to the present method, is discussed.

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