Optimum source-receiver orientations to capture PP, PS, SP, and SS reflected wave modes

2019 ◽  
Vol 38 (1) ◽  
pp. 45-52 ◽  
Author(s):  
Andre Pugin ◽  
Öz Yilmaz
Keyword(s):  
Seismic Source ◽  
Data Sets ◽  
S Wave ◽  
Reflection Mode ◽  
Near Surface ◽  
Reflected Wave ◽  
Source Type ◽  
Receiver Array ◽  
Soil Site ◽  
Wave Modes

We conducted a field experiment at the geotechnical research soil site #1 in Ottawa, Ontario, Canada, and recorded 9-C seismic data along a short line traverse 90 m in length using a multicomponent vibrator source named Microvibe and a landstreamer receiver array with 48 3-C 28-Hz geophones at 0.75-m intervals. The receiver spread length is 35.25 m, and the near-offset is 1.50 m. We used three source and three receiver orientations — vertical (V), inline-horizontal (H1), and transverse-horizontal (H2). We identified several reflection wave modes in the field records — PP, PS, SP, and SS, in addition to refracted waves, and Rayleigh-mode and Love-mode surface waves. We computed the semblance spectra of the selected shot records and ascertained the wave modes based on the semblance peaks. We then performed CMP stacking of each of the 9-C data sets using the PP, PS/SP, and SS stacking velocities. This field test convincingly demonstrates that there is no pure P- or S-wave land seismic source — any source type can generate any combination of wave modes — PP, PS, SP, and SS, and partitioning of the source energy depends on the source orientation and VP/VSratio. All three receiver orientations will capture all reflected wave modes — PP, PS, SP, and SS — but with varying strength. The magnitude of the reflection amplitude captured by one of the three receiver orientations will depend on the reflector depth, source-receiver offset, and the near-surface P- and S-wave velocities in the vicinity of the receiver location. The most prominent PP reflection energy is recorded by the VV source-receiver orientation, whereas the most prominent SS reflection energy is recorded by the H2H2 source-receiver orientation. Additionally, the optimum source-receiver orientation for PS reflection mode is VH1, and the optimum source-receiver orientation for SP reflection mode is H1V.

Shear and compressive wave data acquisition using multicomponent vibrating source and landstreamer

2021 ◽  
Author(s):  
Andre Pugin ◽  
Barbara Dietiker ◽  
Kevin Brewer ◽  
Timothy Cartwright
Keyword(s):  
Leading Edge ◽  
Data Sets ◽  
Compressive Wave ◽  
Near Surface ◽  
Source Type ◽  
Receiver Array ◽  
Surface Data ◽  
Source Orientation ◽  
Refracted Waves ◽  
Wave Modes

<p>In the vicinity of Ottawa, Ontario, Canada, we have recorded many multicomponent seismic data sets using an in-house multicom­ponent vibrator source named Microvibe and a landstreamer receiver array with 48 3-C 28-Hz geophones at 0.75-m intervals. The receiver spread length was 35.25 m, and the near-offset was 1.50 m. We used one, two or three source and three receiver orientations — vertical (V), inline-horizontal (H1), and transverse-horizontal (H2). We identified several reflection wave modes in the field records — PP, PS, SP, and SS, in addition to refracted waves, and Rayleigh-mode and Love-mode surface waves. We computed the semblance spectra of the selected shot records and ascertained the wave modes based on the semblance peaks. We then performed CMP stacking of each of the 9-C data sets using the PP and SS stacking velocities to compute PP and SS reflection profiles.</p><p>Despite the fact that any source type can generate any combination of wave modes — PP, PS, SP, and SS, partitioning of the source energy depends on the source orientation and VP/VS ratio. Our examples demonstrate that the most prominent PP reflection energy is recorded by the VV source-receiver orientation, whereas the most prominent SS reflection energy is recorded by the H2H2 source-receiver orientation with possibility to obtain decent shear wave near surface data in all other vibrating and receiving directions.</p><p>Pugin, Andre and Yilmaz, Öz, 2019. Optimum source-receiver orientations to capture PP, PS, SP, and SS reflected wave modes. The Leading Edge, vol. 38/1, p. 45-52. https://doi.org/10.1190/tle38010045.1</p>

NEW AND FUTURE DEVELOPMENTS IN SEISMIC EXPLORATION

1982 ◽  
Vol 22 (1) ◽  
pp. 200
Author(s):  
Carl H. Savit
Keyword(s):  
Seismic Reflection ◽  
Seismic Source ◽  
Velocity Estimation ◽  
Seismic Exploration ◽  
Bright Spot ◽  
S Wave ◽  
Near Surface ◽  
The Earth ◽  
Surface Materials ◽  
Receiver Arrays

Present research in reflection seismic prospecting is proceeding with three major goals.Intensive work is being done on the problem of obtaining useful reflections beneath complex near-surface materials. Such near-surface materials distort both the down-going and reflected wavefronts to an extent that deep reflections either cannot be distinguished or are so distorted as to conceal their true shapes. Current research seeks methods for obtaining enough information about near-surface irregularities to construct a model upon which to base a wavefront correction.The second major goal is to improve the resolution of the seismic reflection process. Resolution is lost because high frequencies are often weak in seismic sources and are severely attenuated by the earth, by receiver arrays, and by most processing steps. Seismic bandwidth can be increased by improving the high frequency output of the seismic source to compensate for attentuation in the earth, by reducing the size of receiver arrays, and by drastically reducing the inaccuracies of conventional processing algorithms.The third line of investigation seeks to increase the amount of information extracted from the seismic signal. The first step in this direction was the bright-spot technique, in which qualitative information on seismic reflection amplitudes was used to identify hydrocarbon deposits. Interval velocity estimation was a natural result of moving from a qualitative to a quantitative analysis of amplitudes. In theory, with a combination of P and S wave reflection data, virtually all elastic properties of subsurface rocks could be extracted from the data.In the more distant future, computers could handle complex interpretation tasks and make drilling decisions.The principal barrier to rapid implementation of virtually all of the new techniques is inadequate computer power. Despite the explosive growth of the power of computers, mainframe manufacturers have been unable to satisfy the even more rapidly increasing demands of geophysicists. Innovative processing techniques and specialized computer equipment will be essential to continuing rapid progress in geophysical exploration.

Near-surface S-wave velocities estimated from traffic-induced Love waves using seismic interferometry with double beamforming

2016 ◽  
Vol 4 (4) ◽  
pp. SQ23-SQ31 ◽  
Author(s):  
Nori Nakata
Keyword(s):  
Traffic Noise ◽  
Velocity Model ◽  
Dispersion Analysis ◽  
Love Waves ◽  
Seismic Interferometry ◽  
S Wave ◽  
Source Imaging ◽  
Near Surface ◽  
Parallel Lines ◽  
Receiver Array

I use ambient noise, especially traffic noise, to estimate the 2D near-surface S-velocity distribution. Near-surface velocities are useful for understanding structure, stiffness, porosity, and pore pressure for engineering/environmental purposes and static correction of active-source imaging. I extract Love waves propagating between each receiver pair from 12 h of traffic noise using seismic interferometry with power-normalized crosscorrelation. The receiver array contained three parallel lines, each of which had 100 transverse-component geophones. I apply double beamforming to the correlations at the parallel lines for improving the signal-to-noise ratio of the extracted Love waves to satisfy the stationary phase assumption for seismic interferometry. I use these Love waves for a dispersion analysis to estimate a 2D near-surface S-wave velocity model based on the multichannel analysis of surface waves. To improve the lateral resolution of the velocity model, I sort the extracted waves according to common midpoints (CMPs) and limited the maximum offset of receiver pairs. The dispersion analysis at each CMP is based on the assumption of layered media, and using all CMPs, I can estimate high-resolution 2D velocities down to 80 m depth. The velocity variations are similar to the location of strong reflectors obtained by a previous study. The main features of the velocity model are recovered even from 1 h of continuous traffic-noise data, which means that the proposed technique can be used for efficient 4D surveys.

Three-component seismic land streamer study of an esker architecture through S- and surface-wave imaging

Geophysics ◽  
2018 ◽  
Vol 83 (6) ◽  
pp. B339-B353 ◽  
Author(s):  
Bojan Brodic ◽  
Alireza Malehmir ◽  
André Pugin ◽  
Georgiana Maries
Keyword(s):  
Surface Wave ◽  
Seismic Source ◽  
Transverse Component ◽  
P Wave ◽  
Wave Component ◽  
Sh Wave ◽  
S Wave ◽  
Near Surface ◽  
Wave Velocities ◽  
Wave Nature

We deployed a newly developed 3C microelectromechanical system-based seismic land streamer over porous glacial sediments to delineate water table and bedrock in Southwestern Finland. The seismic source used was a 500 kg vertical impact drop hammer. We analyzed the SH-wave component and interpreted it together with previously analyzed P-wave component data. In addition to this, we examined the land streamer’s potential for multichannel analysis of surface waves and delineated the site’s stratigraphy with surface-wave-derived S-wave velocities and [Formula: see text] ratios along the entire profile. These S-wave velocities and [Formula: see text] ratios complement the interpretation conducted previously on P-wave stacked section. Peculiarly, although the seismic source used is of a vertical-type nature, the data inspection indicated clear bedrock reflection on the horizontal components, particularly the transverse component. This observation led us to scrutinize the horizontal component data through side-by-side inspection of the shot records of all the three components and particle motion analysis to confirm the S-wave nature of the reflection. Using the apparent moveout velocity of the reflection, as well as the known depth to bedrock based on drilling, we used finite-difference synthetic modeling to further verify its nature. Compared with the P-wave seismic section, bedrock is relatively well delineated on the transverse component S-wave section. Some structures connected to the kettle holes and other stratigraphic units imaged on the P-wave results were also notable on the S-wave section, and particularly on the surface-wave derived S-wave velocity model and [Formula: see text] ratios. Our results indicate that P-, SV-, and SH-wave energy is generated simultaneously at the source location itself. This study demonstrates the potential of 3C seismic for characterization and delineation of the near-surface seismics.

Constrained Surface-wave Dispersion Inversion Using GPR Reflection Data

2020 ◽  
Author(s):  
Shufan Hu ◽  
Yonghui Zhao ◽  
Wenda Bi ◽  
Ruiqing Shen ◽  
Bo Li ◽  
...  
Keyword(s):  
Surface Wave ◽  
Wave Dispersion ◽  
Dispersion Curves ◽  
Data Sets ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Near Surface ◽  
Reflection Data ◽  
Uniqueness Of The Solution ◽  
S Model

<p>Ground penetrating radar (GPR) and Seismic Surface Wave methods (SWMs) are two nondestructive testing (NDT) methods commonly used in near-surface site investigations. These two methods investigate the media properties of subsurface based on different physical phenomena. GPR has a good resolvability to characterize the layered structure since the propagation of electromagnetic wave is sensitive to the change of electrical properties, while, the geometric dispersion of surface waves can be used to retrieve the variation of S-wave velocity (<em>V</em>s) with depth. In most situations, these two data sets are processed separately, and the results are later used for comprehensive interpretation. Constrained inversion, as a way to implement data fusion, can alleviate the non-uniqueness of the solution and produce more consistent information for the comprehensive site and material investigations.</p><p>We present an algorithm for the inversion of surface-wave dispersion curves with GPR interface constraints in 2D media. The reflection interfaces interpreted from the GPR profile are integrated into a cell- and boundary-based <em>V</em>s model. This implementation allows both vertical and lateral changes within each region while also allows sharp changes across the boundaries. In addition, our algorithm simultaneously inverts several dispersion curves extracted along the survey line using multi-size spatial windows, which mitigates the adverse effects of 1D assumption in traditional surface-wave dispersion inversion and improves the matching of GPR and SWMs in lateral variations. We use synthetic and field data sets to test the effectivity of the proposed method. Both results show the improved resolution of the <em>V</em>s model retrieved by the constrained inversion compared to the standard inversion.</p>

The shape of things to come — Development and testing of a new marine vibrator source

2019 ◽  
Vol 38 (9) ◽  
pp. 680-690 ◽  
Author(s):  
Benoît Teyssandier ◽  
John J. Sallas
Keyword(s):  
Seismic Source ◽  
Test Facility ◽  
Data Sets ◽  
Far Field ◽  
Ocean Bottom ◽  
Air Gun ◽  
Seismic Image ◽  
Field Radiation ◽  
Technical Issues ◽  
To Come

Ten years ago, CGG launched a project to develop a new concept of marine vibrator (MV) technology. We present our work, concluding with the successful acquisition of a seismic image using an ocean-bottom-node 2D survey. The expectation for MV technology is that it could reduce ocean exposure to seismic source sound, enable new acquisition solutions, and improve seismic data quality. After consideration of our objectives in terms of imaging, productivity, acoustic efficiency, and operational risk, we developed two spectrally complementary prototypes to cover the seismic bandwidth. In practice, an array composed of several MV units is needed for images of comparable quality to those produced from air-gun data sets. Because coupling to the water is invariant, MV signals tend to be repeatable. Since far-field pressure is directly proportional to piston volumetric acceleration, the far-field radiation can be well controlled through accurate piston motion control. These features allow us to shape signals to match precisely a desired spectrum while observing equipment constraints. Over the last few years, an intensive validation process was conducted at our dedicated test facility. The MV units were exposed to 2000 hours of in-sea testing with only minor technical issues.

P- and S-wave attenuation logs from monopole sonic data

Geophysics ◽  
2000 ◽  
Vol 65 (3) ◽  
pp. 755-765 ◽  
Author(s):  
Xinhua Sun ◽  
Xiaoming Tang ◽  
C. H. (Arthur) Cheng ◽  
L. Neil Frazer
Keyword(s):  
Wave Attenuation ◽  
Fluid Velocity ◽  
P Wave ◽  
Reservoir Rock ◽  
Rock Properties ◽  
S Wave ◽  
Intrinsic Attenuation ◽  
Modified Method ◽  
Receiver Array ◽  
Attenuation Profiles

In this paper, a modification of an existing method for estimating relative P-wave attenuation is proposed. By generating synthetic waveforms without attenuation, the variation of geometrical spreading related to changes in formation properties with depth can be accounted for. With the modified method, reliable P- and S-wave attenuation logs can be extracted from monopole array acoustic waveform log data. Synthetic tests show that the P- and S-wave attenuation values estimated from synthetic waveforms agree well with their respective model values. In‐situ P- and S-wave attenuation profiles provide valuable information about reservoir rock properties. Field data processing results show that this method gives robust estimates of intrinsic attenuation. The attenuation profiles calculated independently from each waveform of an eight‐receiver array are consistent with one another. In fast formations where S-wave velocity exceeds the borehole fluid velocity, both P-wave attenuation ([Formula: see text]) and S-wave attenuation ([Formula: see text]) profiles can be obtained. P- and S-wave attenuation profiles and their comparisons are presented for three reservoirs. Their correlations with formation lithology, permeability, and fractures are also presented.

Vector-based elastic reverse time migration based on scalar imaging condition

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. S111-S127 ◽  
Author(s):  
Qizhen Du ◽  
ChengFeng Guo ◽  
Qiang Zhao ◽  
Xufei Gong ◽  
Chengxiang Wang ◽  
...  
Keyword(s):  
Alternative Methods ◽  
Polarity Reversal ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
S Wave ◽  
Converted Wave ◽  
Imaging Condition ◽  
Time Migration ◽  
Wavefield Separation ◽  
Wave Modes

The scalar images (PP, PS, SP, and SS) of elastic reverse time migration (ERTM) can be generated by applying an imaging condition as crosscorrelation of pure wave modes. In conventional ERTM, Helmholtz decomposition is commonly applied in wavefield separation, which leads to a polarity reversal problem in converted-wave images because of the opposite polarity distributions of the S-wavefields. Polarity reversal of the converted-wave image will cause destructive interference when stacking over multiple shots. Besides, in the 3D case, the curl calculation generates a vector S-wave, which makes it impossible to produce scalar PS, SP, and SS images with the crosscorrelation imaging condition. We evaluate a vector-based ERTM (VB-ERTM) method to address these problems. In VB-ERTM, an amplitude-preserved wavefield separation method based on decoupled elastic wave equation is exploited to obtain the pure wave modes. The output separated wavefields are both vectorial. To obtain the scalar images, the scalar imaging condition in which the scalar product of two vector wavefields with source-normalized illumination is exploited to produce scalar images instead of correlating Cartesian components or magnitude of the vector P- and S-wave modes. Compared with alternative methods for correcting the polarity reversal of PS and SP images, our ERTM solution is more stable and simple. Besides these four scalar images, the VB-ERTM method generates another PP-mode image by using the auxiliary stress wavefields. Several 2D and 3D numerical examples are evaluated to demonstrate the potential of our ERTM method.

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.

Sign in / Sign up

Export Citation Format

Share Document