On: “Comparison of P‐ and S‐wave seismic data: A new method for detecting gas reservoirs” by R. A. Ensley (GEOPHYSICS, 49, 1420‐1431, September, 1984).

Geophysics ◽  
1985 ◽  
Vol 50 (11) ◽  
pp. 1793-1793
Author(s):  
D. F. Winterstein
Keyword(s):  
Shear Wave ◽  
Seismic Data ◽  
New Method ◽  
Wave Group ◽  
S Wave ◽  
Gas Reservoirs ◽  
Wave Data

Ensley’s paper was based on data of the Conoco Shear Wave Group Shoot of 1977–1978; hence, many companies besides Exxon, including my own, have the Putah Sink data he showed. The stacked sections he showed look identical to the Conoco brute stacks furnished to group shoot participants. The brute stacks had no residual statics or stacking velocity corrections. Those of us who have processed S-wave data often have been pleasantly surprised at how much improvement can come from careful application of residual statics and stacking velocity corrections. Our experience shows that it is unwise to interpret stacked S-wave data that have not had benefit of such refinements.

Comparison of P‐ and S‐wave seismic data: A new method for detecting gas reservoirs

Geophysics ◽  
1984 ◽  
Vol 49 (9) ◽  
pp. 1420-1431 ◽  
Author(s):  
Ross Alan Ensley
Keyword(s):  
Shear Wave ◽  
Seismic Data ◽  
Quantitative Methods ◽  
Qualitative Evaluation ◽  
Compressional Wave ◽  
Bright Spot ◽  
S Wave ◽  
Gas Reservoirs ◽  
Compressional Waves

Compressional waves are sensitive to the type of pore fluid within rocks, but shear waves are only slightly affected by changes in fluid type. This suggests that a comparison of compressional‐ and shear‐wave seismic data recorded over a prospect may allow an interpreter to discriminate between gas‐related anomalies and those related to lithology. This case study documents that where a compressional‐wave “bright spot” or other direct hydrocarbon indicator is present, such a comparison can be used to verify the presence of gas. In practice, the technique can only be used for a qualitative evaluation. However, future improvement of shear‐wave data quality may enable the use of more quantitative methods as well.

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.

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

Geophysics ◽  
1999 ◽  
Vol 64 (2) ◽  
pp. 504-507 ◽  
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.

scholarly journals Advantages of Shear Wave Seismic in Morrow Sandstone Detection

2011 ◽  
Vol 2011 ◽  
pp. 1-16 ◽  
Author(s):  
Paritosh Singh ◽  
Thomas Davis
Keyword(s):  
Shear Wave ◽  
Pure Shear ◽  
High Amplitude ◽  
Compressional Wave ◽  
Side Lobe ◽  
P Wave ◽  
S Wave ◽  
Converted Wave ◽  
P Waves ◽  
Wave Data

The Upper Morrow sandstones in the western Anadarko Basin have been prolific oil producers for more than five decades. Detection of Morrow sandstones is a major problem in the exploration of new fields and the characterization of existing fields because they are often very thin and laterally discontinuous. Until recently compressional wave data have been the primary resource for mapping the lateral extent of Morrow sandstones. The success with compressional wave datasets is limited because the acoustic impedance contrast between the reservoir sandstones and the encasing shales is small. Here, we have performed full waveform modeling study to understand the Morrow sandstone signatures on compressional wave (P-wave), converted-wave (PS-wave) and pure shear wave (S-wave) gathers. The contrast in rigidity between the Morrow sandstone and surrounding shale causes a strong seismic expression on the S-wave data. Morrow sandstone shows a distinct high amplitude event in pure S-wave modeled gathers as compared to the weaker P- and PS-wave events. Modeling also helps in understanding the adverse effect of interbed multiples (due to shallow high velocity anhydrite layers) and side lobe interference effects at the Morrow level. Modeling tied with the field data demonstrates that S-waves are more robust than P-waves in detecting the Morrow sandstone reservoirs.

Joint inversion of logging-while-drilling multipole acoustic data to determine formation shear-wave transverse isotropy

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. D121-D132
Author(s):  
Yang-Hu Li ◽  
Song Xu ◽  
Can Jiang ◽  
Yuan-Da Su ◽  
Xiao-Ming Tang
Keyword(s):  
Shear Wave ◽  
Joint Inversion ◽  
Transverse Isotropy ◽  
Synthetic Data ◽  
Flexural Wave ◽  
Inversion Method ◽  
S Wave ◽  
Acoustic Data ◽  
Wave Data ◽  
Logging While Drilling

Seismic-wave anisotropy has long been an important topic in the exploration and development of unconventional reservoirs, especially in shales, which are commonly characterized as transversely isotropic ([TI] or vertical TI [VTI]) media. At present, the shear-wave (S-wave) TI properties have mainly been determined from monopole Stoneley- or dipole flexural-wave measurements in wireline acoustic logging, but the feasibility of those obtained from logging-while-drilling (LWD) acoustic data needs to be established. We have developed a joint inversion method for simultaneously determining formation S-wave transverse isotropy and vertical velocity from LWD multipole acoustic data. Our theoretical analysis shows that the presence of anisotropy strongly influences LWD Stoneley- and quadrupole-wave dispersion characteristics. Although the monopole Stoneley and quadrupole waves are sensitive to the formation S-wave TI parameters, they suffer from the typical nonuniqueness problem when using the individual-wave data to invert parameters alone. Thus, the respective dispersion data can be jointly used to estimate the formation S-wave TI properties. By the joint inversion, the nonuniqueness problem in the parameter inversion can also be effectively alleviated. The feasibility of the method has been verified by the processing results of theoretical synthetic data and field LWD acoustic-wave data. Therefore, the result offers an effective method for evaluating VTI formation anisotropy from acoustic LWD data.

Elastic full waveform inversion of multicomponent ocean-bottom cable seismic data: Application to Alba Field, U. K. North Sea

Geophysics ◽  
2010 ◽  
Vol 75 (6) ◽  
pp. R109-R119 ◽  
Author(s):  
Timothy J. Sears ◽  
Penny J. Barton ◽  
Satish C. Singh
Keyword(s):  
Wave Velocity ◽  
Seismic Data ◽  
Waveform Inversion ◽  
P Wave ◽  
Full Waveform Inversion ◽  
Ocean Bottom ◽  
S Wave ◽  
Wave Data ◽  
Data Inversion ◽  
Full Waveform

Elastic full waveform inversion of multichannel seismic data represents a data-driven form of analysis leading to direct quantification of the subsurface elastic parameters in the depth domain. Previous studies have focused on marine streamer data using acoustic or elastic inversion schemes for the inversion of P-wave data. In this paper, P- and S-wave velocities are inverted for using wide-angle multicomponent ocean-bottom cable (OBC) seismic data. Inversion is undertaken using a two-dimensional elastic algorithm operating in the time domain, which allows accurate modeling and inversion of the full elastic wavefield, including P- and mode-converted PS-waves and their respective amplitude variation with offset (AVO) responses. Results are presented from the application of this technique to an OBC seismic data set from the Alba Field, North Sea. After building an initial velocity model and extracting a seismic wavelet, the data are inverted instages. In the first stage, the intermediate wavelength P-wave velocity structure is recovered from the wide-angle data and then the short-scale detail from near-offset data using P-wave data on the [Formula: see text] (vertical geophone) component. In the second stage, intermediate wavelengths of S-wave velocity are inverted for, which exploits the information captured in the P-wave’s elastic AVO response. In the third stage, the earlier models are built on to invert mode-converted PS-wave events on the [Formula: see text] (horizontal geophone) component for S-wave velocity, targeting first shallow and then deeper structure. Inversion of [Formula: see text] alone has been able to delineate the Alba Field in P- and S-wave velocity, with the main field and outlier sands visible on the 2D results. Inversion of PS-wave data has demonstrated the potential of using converted waves to resolve shorter wavelength detail. Even at the low frequencies [Formula: see text] inverted here, improved spatial resolution was obtained by inverting S-wave data compared with P-wave data inversion results.

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.

scholarly journals Comment on Shear wave reflection seismic yields subsurface dissolution and subrosion patterns: application to the Ghor Al-Haditha sinkhole site, Dead Sea, Jordan by Polom et al. (2018)

2019 ◽  
Author(s):  
Michael Ezersky ◽  
Anatoly Legchenko ◽  
Lev Eppelbaum ◽  
Abdallah Al-Zoubi ◽  
Abdelrahman Abueladas
Keyword(s):  
Shear Wave ◽  
Seismic Data ◽  
Seismic Reflection ◽  
Wave Reflection ◽  
Dead Sea ◽  
S Wave ◽  
Reflection Seismic ◽  
Salt Layer ◽  
Wave Technique

Abstract. Seismic reflection S-wave technique is very effective and has demonstrated nice results in previous investigations of various authors. However, the salt layer was not detected in the Ghor Al-Haditha area (Jordan) because of some reasons. The main reason is that about ~ 80 % of reflection lines were carried outside the salt area delineated by Ezersky et al. (2013b) based on results of El-Isa et al. (1995). Other possible factor is too strong filtering of seismic data obtained from the upper part of the section (up to 50 m deep). Our and Polom (2018) assessment of the work of other authors diverges. We affirm that the salt layer of 7–10 m thickness is located at ~ 40 m depth in the Ghor Al-Haditha area.

Poststack, prestack, and joint inversion of P- and S-wave data for Morrow A sandstone characterization

2015 ◽  
Vol 3 (3) ◽  
pp. SZ59-SZ92 ◽  
Author(s):  
Paritosh Singh ◽  
Thomas L. Davis ◽  
Bryan DeVault
Keyword(s):  
Wave Velocity ◽  
Seismic Data ◽  
Joint Inversion ◽  
Wave Impedance ◽  
P Wave ◽  
S Wave ◽  
Wave Data ◽  
Wave Inversion ◽  
Density Maps ◽  
P Wave Velocity

Exploration for oil-bearing Morrow sandstones using conventional seismic data/methods has a startlingly low success rate of only 3%. The S-wave velocity contrast between the Morrow shale and A sandstone is strong compared with the P-wave velocity contrast, and, therefore, multicomponent seismic data could help to characterize these reservoirs. The SV and SH data used in this study are generated using S-wave data from horizontal source and horizontal receiver recording. Prestack P- and S-wave inversions, and joint P- and S-wave inversions, provide estimates of P- and S-wave impedances, and density for characterization of the Morrow A sandstone. Due to the weak P-wave amplitude-versus-angle response at the Morrow A sandstone top, the density and S-wave impedance estimated from joint P- and S-wave inversions were inferior to the prestack S-wave inversion. The inversion results were compared with the Morrow A sandstone thickness and density maps obtained from well logs to select the final impedance and density volume for interpretation. The P-wave impedance estimated from prestack P-wave data, as well as density and S-wave impedance estimated from prestack SV‐wave data were used to identify the distribution, thickness, quality, and porosity of the Morrow A sandstone. The stratal slicing method was used to get the P- and S-wave impedances and density maps. The S-wave impedance characterizes the Morrow A sandstone distribution better than the P-wave impedance throughout the study area. Density estimation from prestack inversion of SV data was able to distinguish between low- and high-quality reservoirs. The porosity volume was estimated from the density obtained from prestack SV-wave inversion. We found some possible well locations based on the interpretation.

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