Seismic vertical transversely isotropic parameter inversion from P- and S-wave cross-borehole measurements in an aquifer environment

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. D101-D116
Author(s):  
Julius K. von Ketelhodt ◽  
Musa S. D. Manzi ◽  
Raymond J. Durrheim ◽  
Thomas Fechner
Keyword(s):  
Transversely Isotropic ◽  
P Wave ◽  
Perturbation Equation ◽  
S Wave ◽  
P Waves ◽  
Data Set ◽  
Near Surface ◽  
S Waves ◽  
Wave Measurements ◽  
Wave Splitting

Joint P- and S-wave measurements for tomographic cross-borehole analysis can offer more reliable interpretational insight concerning lithologic and geotechnical parameter variations compared with P-wave measurements on their own. However, anisotropy can have a large influence on S-wave measurements, with the S-wave splitting into two modes. We have developed an inversion for parameters of transversely isotropic with a vertical symmetry axis (VTI) media. Our inversion is based on the traveltime perturbation equation, using cross-gradient constraints to ensure structural similarity for the resulting VTI parameters. We first determine the inversion on a synthetic data set consisting of P-waves and vertically and horizontally polarized S-waves. Subsequently, we evaluate inversion results for a data set comprising jointly measured P-waves and vertically and horizontally polarized S-waves that were acquired in a near-surface ([Formula: see text]) aquifer environment (the Safira research site, Germany). The inverted models indicate that the anisotropy parameters [Formula: see text] and [Formula: see text] are close to zero, with no P-wave anisotropy present. A high [Formula: see text] ratio of up to nine causes considerable SV-wave anisotropy despite the low magnitudes for [Formula: see text] and [Formula: see text]. The SH-wave anisotropy parameter [Formula: see text] is estimated to be between 0.05 and 0.15 in the clay and lignite seams. The S-wave splitting is confirmed by polarization analysis prior to the inversion. The results suggest that S-wave anisotropy may be more severe than P-wave anisotropy in near-surface environments and should be taken into account when interpreting cross-borehole S-wave data.

Separation and enhancement of split S‐waves on multicomponent shot records from the BIRPS WISPA experiment

Geophysics ◽  
1994 ◽  
Vol 59 (1) ◽  
pp. 131-139 ◽  
Author(s):  
M. Boulfoul ◽  
D. R. Watts
Keyword(s):  
Synthetic Data ◽  
P Wave ◽  
Moving Window ◽  
Wave Analysis ◽  
S Wave ◽  
Near Surface ◽  
S Waves ◽  
Wave Velocities ◽  
Wave Splitting ◽  
Explosive Source

Instantaneous rotations are combined with f-k filtering to extract coherent S‐wave events from multicomponent shot records recorded by British Institutions Reflection Profiling Syndicate (BIRPS) Weardale Integrated S‐wave and P‐wave analysis (WISPA) experiment. This experiment was an attempt to measure the Poisson’s ratio of the lower crest by measuring P‐wave and S‐wave velocities. The multihole explosive source technique did generate S‐waves although not of opposite polarization. Attempts to produce stacks of the S‐wave data are unsuccessful because S‐wave splitting in the near surface produced random polarizations from receiver group to receiver group. The delay between the split wavelets varies but is commonly between 20 to 40 ms for 10 Hz wavelets. Dix hyperbola are produced on shot records after instantaneous rotations are followed by f-k filtering. To extract the instantaneous polarization, the traces are shifted back by the length of a moving window over which the calculation is performed. The instantaneous polarization direction is computed from the shifted data using the maximum eigenvector of the covariance matrix over the computation window. Split S‐waves are separated by the instantaneous rotation of the unshifted traces to the directions of the maximum eigenvectors determined for each position of the moving window. F-K filtering is required because of the presence of mode converted S‐waves and S‐waves produced by the explosive source near the time of detonation. Examples from synthetic data show that the method of instantaneous rotations will completely separate split S‐waves if the length of the moving window over which the calculation is performed is the length of the combined split wavelets. Separation may be achieved on synthetic data for wavelet delays as small as two sample intervals.

A simple method for resolving large converted‐wave (P-SV) statics

Geophysics ◽  
1993 ◽  
Vol 58 (3) ◽  
pp. 429-433 ◽  
Author(s):  
Peter W. Cary ◽  
David W. S. Eaton
Keyword(s):  
P Wave ◽  
S Wave ◽  
Converted Wave ◽  
P Waves ◽  
Simple Method ◽  
Near Surface ◽  
S Waves ◽  
Static Solutions ◽  
Surface Fluctuations

The processing of converted‐wave (P-SV) seismic data requires certain special considerations, such as commonconversion‐point (CCP) binning techniques (Tessmer and Behle, 1988) and a modified normal moveout formula (Slotboom, 1990), that makes it different for processing conventional P-P data. However, from the processor’s perspective, the most problematic step is often the determination of residual S‐wave statics, which are commonly two to ten times greater than the P‐wave statics for the same location (Tatham and McCormack, 1991). Conventional residualstatics algorithms often produce numerous cycle skips when attempting to resolve very large statics. Unlike P‐waves, the velocity of S‐waves is virtually unaffected by near‐surface fluctuations in the water table (Figure 1). Hence, the P‐wave and S‐wave static solutions are largely unrelated to each other, so it is generally not feasible to approximate the S‐wave statics by simply scaling the known P‐wave static values (Anno, 1986).

Numerical simulation of azimuthal acoustic logging in a borehole penetrating a rock formation boundary

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. D283-D291 ◽  
Author(s):  
Peng Liu ◽  
Wenxiao Qiao ◽  
Xiaohua Che ◽  
Xiaodong Ju ◽  
Junqiang Lu ◽  
...  
Keyword(s):  
Domain Model ◽  
P Wave ◽  
S Wave ◽  
Angle Variation ◽  
P Waves ◽  
Acoustic Logging ◽  
S Waves ◽  
Rock Formation ◽  
Logging Tool ◽  
Difference Time

We have developed a new 3D acoustic logging tool (3DAC). To examine the azimuthal resolution of 3DAC, we have evaluated a 3D finite-difference time-domain model to simulate a case in which the borehole penetrated a rock formation boundary when the tool worked at the azimuthal-transmitting-azimuthal-receiving mode. The results indicated that there were two types of P-waves with different slowness in waveforms: the P-wave of the harder rock (P1) and the P-wave of the softer rock (P2). The P1-wave can be observed in each azimuthal receiver, but the P2-wave appears only in the azimuthal receivers toward the softer rock. When these two types of rock are both fast formations, two types of S-waves also exist, and they have better azimuthal sensitivity compared with P-waves. The S-wave of the harder rock (S1) appears only in receivers toward the harder rock, and the S-wave of the softer rock (S2) appears only in receivers toward the softer rock. A model was simulated in which the boundary between shale and sand penetrated the borehole but not the borehole axis. The P-wave of shale and the S-wave of sand are azimuthally sensitive to the azimuth angle variation of two formations. In addition, waveforms obtained from 3DAC working at the monopole-transmitting-azimuthal-receiving mode indicate that the corresponding P-waves and S-waves are azimuthally sensitive, too. Finally, we have developed a field example of 3DAC to support our simulation results: The azimuthal variation of the P-wave slowness was observed and can thus be used to reflect the azimuthal heterogeneity of formations.

The 1998 Valhall microseismic data set: An integrated study of relocated sources, seismic multiplets, and S-wave splitting

Geophysics ◽  
2009 ◽  
Vol 74 (5) ◽  
pp. B183-B195 ◽  
Author(s):  
K. De Meersman ◽  
J.-M. Kendall ◽  
M. van der Baan
Keyword(s):  
Seismic Anisotropy ◽  
Amplitude Ratio ◽  
Temporal Variations ◽  
Oil Field ◽  
P Wave ◽  
Wave Form ◽  
S Wave ◽  
Data Set ◽  
Wave Splitting ◽  
Source Mechanisms

We relocate 303 microseismic events recorded in 1998 by sensors in a single borehole in the North Sea Valhall oil field. A semiautomated array analysis method repicks the P- and S-wave arrival times and P-wave polarizations, which are needed to locate these events. The relocated sources are confined predominantly to a [Formula: see text]-thick zone just above the reservoir, and location uncertainties are half those of previous efforts. Multiplet analysis identifies 40 multiplet groups, which include 208 of the 303 events. The largest group contains 24 events, and five groups contain 10 or more events. Within each multiplet group, we further improve arrival-time picking through crosscorrelation, which enhances the relative accuracy of the relocated events and reveals that more than 99% of the seismic activity lies spatially in three distinct clusters. The spatial distribution of events and wave-form similarities reveal two faultlike structures that match well with north-northwest–south-southeast-trending fault planes interpreted from 3D surface seismic data. Most waveform differences between multiplet groups located on these faults can be attributed to S-wave phase content and polarity or P-to-S amplitude ratio. The range in P-to-S amplitude ratios observed on the faults is explained best in terms of varying source mechanisms. We also find a correlation between multiplet groups and temporal variations in seismic anisotropy, as revealed by S-wave splitting analysis. We explain these findings in the context of a cyclic recharge and dissipation of cap-rock stresses in response to production-driven compaction of the underlying oil reservoir. The cyclic nature of this mechanism drives the short-term variations in seismic anisotropy and the reactivation of microseismic source mechanisms over time.

Shallow near-surface effects

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. T221-T231 ◽  
Author(s):  
Christine E. Krohn ◽  
Thomas J. Murray
Keyword(s):  
Time Delay ◽  
Velocity Gradient ◽  
P Wave ◽  
Unconsolidated Sediments ◽  
P Waves ◽  
Large Computer ◽  
Near Surface ◽  
S Waves ◽  
High Attenuation ◽  
Pulse Broadening

The top 6 m of the near surface has a surprisingly large effect on the behavior of P- and S-waves. For unconsolidated sediments, the P-wave velocity gradient and attenuation can be quite large. Computer modeling should include these properties to accurately reproduce seismic effects of the near surface. We have used reverse VSP data and computer simulations to demonstrate the following effects for upgoing P-waves. Near the surface, we have observed a large time delay, indicating low velocity ([Formula: see text]), and considerable pulse broadening, indicating high attenuation ([Formula: see text]). Consequently, shallowly buried geophones have greater high-frequency bandwidth compared with surface geophones. In addition, there is a large velocity gradient in the shallow near surface (factor of 10 in 5 m), resulting in the rotation of P-waves to the vertical with progressively smaller amplitudes recorded on horizontal phones. Finally, we have found little indication of a reflection or ghost from the surface, although downgoing reflections have been observed from interfaces within the near surface. In comparison, the following have been observed for upgoing S-waves: There is a small increase in the time delay or pulse broadening near the surface, indicating a smaller velocity gradient and less change in attenuation. In addition, the surface reflection coefficient is nearly one with a prominent surface ghost.

Near-surface scattering phenomena and implications for tunnel detection

2015 ◽  
Vol 3 (1) ◽  
pp. SF43-SF54 ◽  
Author(s):  
Shelby L. Peterie ◽  
Richard D. Miller
Keyword(s):  
Synthetic Data ◽  
P Wave ◽  
S Wave ◽  
Seismic Line ◽  
Data Set ◽  
Near Surface ◽  
Tunnel Detection ◽  
Impedance Contrast ◽  
Diffraction Imaging ◽  
Imaging Algorithms

Tunnel locations are accurately interpreted from diffraction sections of focused mode converted P- to S-wave diffractions from a perpendicular tunnel and P-wave diffractions from a nonperpendicular (oblique) tunnel. Near-surface tunnels are ideal candidates for diffraction imaging due to their small size relative to the seismic wavelength and large acoustic impedance contrast at the tunnel interface. Diffraction imaging algorithms generally assume that the velocities of the primary wave and the diffracted wave are approximately equal, and that the diffraction apex is recorded directly above the scatterpoint. Scattering phenomena from shallow tunnels with kinematic properties that violate these assumptions were observed in one field data set and one synthetic data set. We developed the traveltime equations for mode-converted and oblique diffractions and demonstrated a diffraction imaging algorithm designed for the roll-along style of acquisition. Potential processing and interpretation pitfalls specific to these diffraction types were identified. Based on our observations, recommendations were made to recognize and image mode-converted and oblique diffractions and accurately interpret tunnel depth, horizontal location, and azimuth with respect to the seismic line.

Velocity anisotropy in shale determined from crosshole seismic and vertical seismic profile data

Geophysics ◽  
1990 ◽  
Vol 55 (4) ◽  
pp. 470-479 ◽  
Author(s):  
D. F. Winterstein ◽  
B. N. P. Paulsson
Keyword(s):  
Seismic Profile ◽  
P Wave ◽  
Isotropic Model ◽  
S Wave ◽  
Vertical Seismic Profile ◽  
Near Surface ◽  
S Waves ◽  
Velocity Anisotropy ◽  
Wave Velocities ◽  
Late Tertiary

Crosshole and vertical seismic profile (VST) data made possible accurate characterization of the elastic properties, including noticeable velocity anisotropy, of a near‐surface late Tertiary shale formation. Shear‐wave splitting was obvious in both crosshole and VSP data. In crosshole data, two orthologonally polarrized shear (S) waves arrived 19 ms in the uppermost 246 ft (75 m). Vertically traveling S waves of the VSP separated about 10 ms in the uppermost 300 ft (90 m) but remained at nearly constant separation below that level. A transversely isotropic model, which incorporates a rapid increase in S-wave velocities with depth but slow increase in P-wave velocities, closely fits the data over most of the measured interval. Elastic constants of the transvesely isotropic model show spherical P- and [Formula: see text]wave velocity surfaces but an ellipsoidal [Formula: see text]wave surface with a ratio of major to minor axes of 1.15. The magnitude of this S-wave anisotropy is consistent with and lends credence to S-wave anisotropy magnitudes deduced less directly from data of many sedimentary basins.

scholarly journals Phased array compaction cell for measurement of the transversely isotropic elastic properties of compacting sediments

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. WA113-WA123 ◽  
Author(s):  
Kurt T. Nihei ◽  
Seiji Nakagawa ◽  
Frederic Reverdy ◽  
Larry R. Myer ◽  
Luca Duranti ◽  
...  
Keyword(s):  
Elastic Properties ◽  
Phased Array ◽  
Transversely Isotropic ◽  
P Wave ◽  
S Wave ◽  
P Waves ◽  
Array Measurements ◽  
Experimental Apparatus ◽  
Marine Sediment Sample ◽  
Plane P Waves

Sediments undergoing compaction typically exhibit transversely isotropic (TI) elastic properties. We present a new experimental apparatus, the phased array compaction cell, for measuring the TI elastic properties of clay-rich sediments during compaction. This apparatus uses matched sets of P- and S-wave ultrasonic transducers located along the sides of the sample and an ultrasonic P-wave phased array source, together with a miniature P-wave receiver on the top and bottom ends of the sample. The phased array measurements are used to form plane P-waves that provide estimates of the phase velocities over a range of angles. From these measurements, the five TI elastic constants can be recovered as the sediment is compacted, without the need for sample unloading, recoring, or reorienting. This paper provides descriptions of the apparatus, the data processing, and an application demonstrating recovery of the evolving TI properties of a compacting marine sediment sample.

Full-waveform matching of VP and VS models from surface waves

2019 ◽  
Vol 218 (3) ◽  
pp. 1873-1891 ◽  
Author(s):  
Farbod Khosro Anjom ◽  
Daniela Teodor ◽  
Cesare Comina ◽  
Romain Brossier ◽  
Jean Virieux ◽  
...  
Keyword(s):  
Surface Waves ◽  
Wave Velocity ◽  
Real Data ◽  
Test Site ◽  
P Wave ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Data Set ◽  
Near Surface ◽  
Velocity Models

SUMMARY The analysis of surface wave dispersion curves (DCs) is widely used for near-surface S-wave velocity (VS) reconstruction. However, a comprehensive characterization of the near-surface requires also the estimation of P-wave velocity (VP). We focus on the estimation of both VS and VP models from surface waves using a direct data transform approach. We estimate a relationship between the wavelength of the fundamental mode of surface waves and the investigation depth and we use it to directly transform the DCs into VS and VP models in laterally varying sites. We apply the workflow to a real data set acquired on a known test site. The accuracy of such reconstruction is validated by a waveform comparison between field data and synthetic data obtained by performing elastic numerical simulations on the estimated VP and VS models. The uncertainties on the estimated velocity models are also computed.

Advances in surface-wave tomography for near-surface applications

2021 ◽  
Vol 40 (8) ◽  
pp. 567-575
Author(s):  
Myrto Papadopoulou ◽  
Farbod Khosro Anjom ◽  
Mohammad Karim Karimpour ◽  
Valentina Laura Socco
Keyword(s):  
Surface Wave ◽  
Wave Velocity ◽  
P Wave ◽  
Seismic Exploration ◽  
S Wave ◽  
Data Set ◽  
Near Surface ◽  
Processing Times ◽  
Spatial Coverage ◽  
Wave Tomography

Surface-wave (SW) tomography is a technique that has been widely used in the field of seismology. It can provide higher resolution relative to the classical multichannel SW processing and inversion schemes that are usually adopted for near-surface applications. Nevertheless, the method is rarely used in this context, mainly due to the long processing times needed to pick the dispersion curves as well as the inability of the two-station processing to discriminate between higher SW modes. To make it efficient and to retrieve pseudo-2D/3D S-wave velocity (VS) and P-wave velocity (VP) models in a fast and convenient way, we develop a fully data-driven two-station dispersion curve estimation, which achieves dense spatial coverage without the involvement of an operator. To handle higher SW modes, we apply a dedicated time-windowing algorithm to isolate and pick the different modes. A multimodal tomographic inversion is applied to estimate a VS model. The VS model is then converted to a VP model with the Poisson's ratio estimated through the wavelength-depth method. We apply the method to a 2D seismic exploration data set acquired at a mining site, where strong lateral heterogeneity is expected, and to a 3D pilot data set, recorded with state-of-the-art acquisition technology. We compare the results with the ones retrieved from classical multichannel analysis.

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