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.

Supercritical reflections observed in P- and S- wave data

Geophysics ◽  
1985 ◽  
Vol 50 (2) ◽  
pp. 185-195 ◽  
Author(s):  
D. F. Winterstein ◽  
J. B. Hanten
Keyword(s):  
Seismic Data ◽  
Critical Angle ◽  
Plane Waves ◽  
Critical Distance ◽  
P Wave ◽  
S Wave ◽  
Sh Waves ◽  
Midland Basin ◽  
Head Waves ◽  
Sonic Logs

We have observed a conspicuous example of supercritical reflection in both P- and SH- wave seismic data. Data were recorded in the Midland Basin (Texas) Project of the Conoco Shear Wave Group Shoot in 1977–1978. P- and S- wave critical angle phenomena, as observed in the data, are remarkably similar. Event amplitudes are small or undetectable at offsets out to about 2 000 ft, but at offsets from 2 500 to 3 600 ft amplitudes are higher than those of any other event. Head waves originating at the critical distance are weak but detectable. Long path multiplies of the supercritical parts of P and SH events appear at expected times and offsets. Constant velocity moveout corrections helped identify them. Sonic logs in combination with a knowledge of the lithology made it possible to model P- wave critical angle phenomena. Agreement of model results with the data was good when we assumed cylindrical wavefronts. As expected, modeling based on plane waves was unable to match observed phase and amplitude behavior. A number of potential uses for supercritical reflections in exploration and data processing readily come to mind, many of them related to the recording of relatively high amplitudes at distances where source noise is low. Observed rise in amplitude near the critical offset was very abrupt, particularly for SH-waves. This suggests that variations in the onset of high amplitudes may be useful for monitoring changes in velocity contrast at the reflecting interface.

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.

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.

scholarly journals Ultrasonic and seismic constraints on crystallographic preferred orientations of the Priestley Glacier shear margin, Antarctica

2022 ◽  
Author(s):  
Franz Lutz ◽  
David J. Prior ◽  
Holly Still ◽  
M. Hamish Bowman ◽  
Bia Boucinhas ◽  
...  
Keyword(s):  
Ice Core ◽  
Seismic Profile ◽  
P Wave ◽  
Quality Data ◽  
S Wave ◽  
P Waves ◽  
Velocity Anisotropy ◽  
Wave Data ◽  
Axis Alignment ◽  
Safety Considerations

Abstract. Crystallographic preferred orientations (CPOs) are particularly important in controlling the mechanical properties of glacial shear margins. Logistical and safety considerations often make direct sampling of shear margins difficult and geophysical measurements are commonly used to constrain the CPOs. We present here the first direct comparison of seismic and ultrasonic data with measured CPOs in a polar shear margin. The measured CPO from ice samples from a 58 m deep borehole in the left lateral shear margin of the Priestley Glacier, Antarctica, is dominated by horizontal c-axes aligned sub-perpendicular to flow. A vertical seismic profile experiment with hammer shots up to 50 m away from the borehole, in four different azimuthal directions, shows velocity anisotropy of both P-waves and S-waves. Matching P-wave data to the anisotropy corresponding to CPO models defined by horizontally aligned c-axes gives two possible solutions for c-axis azimuth, one of which matches the c-axis measurements. If both P-wave and S-wave data are used, there is one best fit for azimuth and intensity of c-axis alignment that matches well the measurements. Azimuthal P-wave and S-wave ultrasonic data recorded in the laboratory on the ice core show clear anisotropy that matches that predicted from the CPO of the samples. With good quality data, azimuthal increments of 30° or less will constrain well the orientation and intensity of c-axis alignment. Our experiments provide a good framework for planning seismic surveys aimed at constraining the anisotropy of shear margins.

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.

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.

SV-P: A potential viable alternative to mode-converted P-SV seismic data for reservoir characterization

2017 ◽  
Vol 5 (4) ◽  
pp. T579-T589 ◽  
Author(s):  
Menal Gupta ◽  
Bob Hardage
Keyword(s):  
Seismic Data ◽  
Seismic Analysis ◽  
Joint Inversion ◽  
P Wave ◽  
S Wave ◽  
Converted Wave ◽  
Important Distinction ◽  
Wave Data ◽  
Multicomponent Seismic ◽  
Injection Zone

P-SV seismic acquisition requires 3C geophones and thus has greater cost compared with conventional P-P data. However, some companies justify this added cost because P-SV data provide an independent set of S-wave measurements, which can increase the reliability of subsurface property estimation. This study investigates SV-P data generated by a vertical vibrator and recorded by vertical geophones as a cost-effective alternative to traditional P-SV data. To evaluate the efficacy of the SV-P mode relative to the P-P and P-SV modes, multicomponent seismic data from Wellington Field, Kansas, were interpreted. P-P amplitude variation with offset (AVO) gathers and stacked SV-P seismic data were jointly inverted to estimate elastic properties, which were compared with the estimates obtained from joint inversion of P-P AVO gathers, stacked P-SV seismic data, and inversion of P-P AVO gathers data. All inversions provide identical P-impedance characteristics. However, a significant improvement in S-impedance estimates is observed when P-P and converted wave data (either SV-P or P-SV) are inverted jointly, compared with P-P inversion results alone. In the Arbuckle interval, which is being considered for [Formula: see text] injection, use of converted-wave data clearly demarcates the Middle Arbuckle baffle zone and the Lower Arbuckle injection zone, with the latter having low P- and S-impedances. These observations, although consistent with other well-based geologic evidence, are absent on P-P-only inversion results. No major difference in the inversion results is seen when SV-P data are used instead of P-SV data. Moreover, we determine for the first time by comparing the SV-P image obtained from vertical-vibrator data and the SV-P image obtained from horizontal-vibrator data that both data image subsurface geology equivalently, except for the important distinction that the former contains more valuable higher frequencies than the latter. Because legacy P-wave data can be reprocessed to extract the SV-P mode, using SV-P data can provide a unique way to perform multicomponent seismic analysis.

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.

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

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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