Real data results of Kirchhoff elastic wave migration

Geophysics ◽  
1986 ◽  
Vol 51 (4) ◽  
pp. 1006-1011 ◽  
Author(s):  
Ting‐Fan Dai ◽  
John T. Kuo
Keyword(s):  
Seismic Data ◽  
Real Data ◽  
Horizontal Layer ◽  
S Wave ◽  
P Waves ◽  
S Waves ◽  
Surface Data ◽  
And Migration ◽  
Wave Migration ◽  
Kirchhoff Integral

Although Kirchhoff integral migration has attracted considerable attention for seismic data processing since the early 1970s, it, like all other seismic migration methods, is only applicable to compressional (P) waves. Because of a recent surge of interest in shear (S) waves, Kuo and Dai (1984) developed the Kirchhoff elastic (P and S) wave migration (KEWM) formulation and migration principle for the case of source and receiver noncoincidence. They obtained encouraging results using two‐dimensional (2-D) synthetic surface data from various geometric elastic models, including a dipping layer, a composite dipping and horizontal layer, and two layers over a half‐space.

Kirchhoff elastic wave migration for the case of noncoincident source and receiver

Geophysics ◽  
1984 ◽  
Vol 49 (8) ◽  
pp. 1223-1238 ◽  
Author(s):  
John T. Kuo ◽  
Ting‐fan Dai
Keyword(s):  
Elastic Wave ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Horizontal Layer ◽  
P Wave ◽  
Seismic Section ◽  
S Waves ◽  
Surface Data ◽  
Marine Seismic ◽  
Wave Migration

In taking into account both compressional (P) and shear (S) waves, more geologic information can likely be extracted from the seismic data. The presence of shear and converted shear waves in both land and marine seismic data recordings calls for the development of elastic wave‐migration methods. The migration method presently developed consists of simultaneous migration of P- and S-waves for offset seismic data based on the Kirchhoff‐Helmholtz type integrals for elastic waves. A new principle of simultaneously migrating both P- and S-waves is introduced. The present method, named the Kirchhoff elastic wave migration, has been tested using the 2-D synthetic surface data calculated from several elastic models of a dipping layer (including a horizontal layer), a composite dipping and horizontal layer, and two layers over a half‐space. The results of these tests not only assure the feasibility of this migration scheme, but also demonstrate that enhanced images in the migrated sections are well formed. Moreover, the signal‐to‐noise ratio increases in the migrated seismic section by this elastic wave migration, as compared with that using the Kirchhoff acoustic (P-) wave migration alone. This migration scheme has about the same order of sensitivity of migration velocity variations, if [Formula: see text] and [Formula: see text] vary concordantly, to the recovery of the reflector as that of the Kirchhoff acoustic (P-) wave migration. In addition, the sensitivity of image quality to the perturbation of [Formula: see text] has also been tested by varying either [Formula: see text] or [Formula: see text]. For varying [Formula: see text] (with [Formula: see text] fixed), the migrated images are virtually unaffected on the [Formula: see text] depth section while they are affected on the [Formula: see text] depth section. For varying [Formula: see text] (with [Formula: see text] fixed), the migrated images are affected on both the [Formula: see text] and [Formula: see text] depth sections.

scholarly journals Comparison of recent S-wave indicating methods

2018 ◽  
Vol 29 ◽  
pp. 00019
Author(s):  
Katarzyna Hubicka ◽  
Jakub Sokolowski
Keyword(s):  
Real Data ◽  
The Body ◽  
Body Waves ◽  
Identification Accuracy ◽  
P Wave ◽  
S Wave ◽  
P Waves ◽  
S Waves ◽  
Mode Decomposition ◽  
Wave Arrival

Seismic event consists of surface waves and body waves. Due to the fact that the body waves are faster (P-waves) and more energetic (S-waves) in literature the problem of their analysis is taken more often. The most universal information that is received from the recorded wave is its moment of arrival. When this information is obtained from at least four seismometers in different locations, the epicentre of the particular event can be estimated [1]. Since the recorded body waves may overlap in signal, the problem of wave onset moment is considered more often for faster P-wave than S-wave. This however does not mean that the issue of S-wave arrival time is not taken at all. As the process of manual picking is time-consuming, methods of automatic detection are recommended (these however may be less accurate). In this paper four recently developed methods estimating S-wave arrival are compared: the method operating on empirical mode decomposition and Teager-Kaiser operator [2], the modification of STA/LTA algorithm [3], the method using a nearest neighbour-based approach [4] and the algorithm operating on characteristic of signals’ second moments. The methods will be also compared to wellknown algorithm based on the autoregressive model [5]. The algorithms will be tested in terms of their S-wave arrival identification accuracy on real data originating from International Research Institutions for Seismology (IRIS) database.

scholarly journals Three-component amplitude versus offset analysis

1989 ◽  
Vol 20 (2) ◽  
pp. 257
Author(s):  
D.R. Miles ◽  
G. Gassaway ◽  
L. Bennett ◽  
R. Brown
Keyword(s):  
Seismic Data ◽  
P Wave ◽  
S Wave ◽  
Converted Wave ◽  
P Waves ◽  
S Waves ◽  
Avo Analysis ◽  
Avo Inversion ◽  
Amplitude Versus Offset ◽  
Converted Waves

Three-component (3-C) amplitude versus offset (AVO) inversion is the AVO analysis of the three major energies in the seismic data, P-waves, S-waves and converted waves. For each type of energy the reflection coefficients at the boundary are a function of the contrast across the boundary in velocity, density and Poisson's ratio, and of the angle of incidence of the incoming wave. 3-C AVO analysis exploits these relationships to analyse the AVO changes in the P, S, and converted waves. 3-C AVO analysis is generally done on P, S, and converted wave data collected from a single source on 3-C geophones. Since most seismic sources generate both P and S-waves, it follows that most 3-C seismic data may be used in 3-C AVO inversion. Processing of the P-wave, S-wave and converted wave gathers is nearly the same as for single-component P-wave gathers. In split-spread shooting, the P-wave and S-wave energy on the radial component is one polarity on the forward shot and the opposite polarity on the back shot. Therefore to use both sides of the shot, the back shot must be rotated 180 degrees before it can be stacked with the forward shot. The amplitude of the returning energy is a function of all three components, not just the vertical or radial, so all three components must be stacked for P-waves, then for S-waves, and finally for converted waves. After the gathers are processed, reflectors are picked and the amplitudes are corrected for free-surface effects, spherical divergence and the shot and geophone array geometries. Next the P and S-wave interval velocities are calculated from the P and S-wave moveouts. Then the amplitude response of the P and S-wave reflections are analysed to give Poisson's ratio. The two solutions are then compared and adjusted until they match each other and the data. Three-component AVO inversion not only yields information about the lithologies and pore-fluids at a specific location; it also provides the interpreter with good correlations between the P-waves and the S-waves, and between the P and converted waves, thus greatly expanding the value of 3-C seismic data.

Geometrical spreading in a layered transversely isotropic medium with vertical symmetry axis

Geophysics ◽  
2003 ◽  
Vol 68 (6) ◽  
pp. 2082-2091 ◽  
Author(s):  
Bjørn Ursin ◽  
Ketil Hokstad
Keyword(s):  
Ray Tracing ◽  
Seismic Data ◽  
Symmetry Axis ◽  
Transversely Isotropic ◽  
Analytical Approximation ◽  
Geometrical Spreading ◽  
S Wave ◽  
Weak Anisotropy ◽  
P Waves ◽  
Amplitude Versus

Compensation for geometrical spreading is important in prestack Kirchhoff migration and in amplitude versus offset/amplitude versus angle (AVO/AVA) analysis of seismic data. We present equations for the relative geometrical spreading of reflected and transmitted P‐ and S‐wave in horizontally layered transversely isotropic media with vertical symmetry axis (VTI). We show that relatively simple expressions are obtained when the geometrical spreading is expressed in terms of group velocities. In weakly anisotropic media, we obtain simple expressions also in terms of phase velocities. Also, we derive analytical equations for geometrical spreading based on the nonhyperbolic traveltime formula of Tsvankin and Thomsen, such that the geometrical spreading can be expressed in terms of the parameters used in time processing of seismic data. Comparison with numerical ray tracing demonstrates that the weak anisotropy approximation to geometrical spreading is accurate for P‐waves. It is less accurate for SV‐waves, but has qualitatively the correct form. For P waves, the nonhyperbolic equation for geometrical spreading compares favorably with ray‐tracing results for offset‐depth ratios less than five. For SV‐waves, the analytical approximation is accurate only at small offsets, and breaks down at offset‐depth ratios less than unity. The numerical results are in agreement with the range of validity for the nonhyperbolic traveltime equations.

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.

scholarly journals Estimation of radiated energy using the KiK-net downhole records—old method for modern data

2020 ◽  
Vol 221 (2) ◽  
pp. 1029-1042 ◽  
Author(s):  
Hiroo Kanamori ◽  
Zachary E Ross ◽  
Luis Rivera
Keyword(s):  
Site Response ◽  
Source Model ◽  
Synthetic Seismograms ◽  
S Wave ◽  
P Waves ◽  
S Waves ◽  
Radiated Energy ◽  
Time Integral ◽  
Magnitude Range ◽  
Significant Difference

SUMMARY We use KiK-net (NIED) downhole records to estimate the radiated energy, ER, of 29 Japanese inland earthquakes with a magnitude range from Mw = 5.6 to 7.0. The method is based on the work of Gutenberg and Richter in which the time integral of S-wave ground-motion velocity-squared is measured as a basic metric of the radiated energy. Only stations within a distance of 100 km are used to minimize complex path and attenuation effects. Unlike the teleseismic method that uses mainly P waves, the use of S waves which carry more than 95 per cent of the radiated energy allows us to obtain robust results. We calibrate the method using synthetic seismograms to modernize and improve the Gutenberg–Richter method. We compute synthetic seismograms for a source model of each event with a given source function (i.e. known ER), the actual mechanism and the source-station geometry. Then, we compare the given ER with the computed energy metric to correct for the unknown effect of wave propagation and the mechanism. The use of downhole records minimizes the uncertainty resulting from the site response. Our results suggest that the currently available estimates of ER from teleseismic data are probably within a factor of 3, on average, of the absolute value. The scaled energy eR ( = ER/M0) is nearly constant at about 3 × 10−5 over a magnitude range from Mw = 5.6 to 7.0 with a slight increasing trend with Mw. We found no significant difference in eR between dip-slip and strike-slip events.

Transformation to zero offset for mode‐converted waves

Geophysics ◽  
1992 ◽  
Vol 57 (3) ◽  
pp. 474-477 ◽  
Author(s):  
Mohammed Alfaraj ◽  
Ken Larner
Keyword(s):  
Seismic Data ◽  
Constant Velocity ◽  
Reflection Point ◽  
P Waves ◽  
S Waves ◽  
Nmo Correction ◽  
Converted Waves ◽  
Zero Offset ◽  
Correct Data

The transformation to zero offset (TZO) of prestack seismic data for a constant‐velocity medium is well understood and is readily implemented when dealing with either P‐waves or S‐waves. TZO is achieved by inserting a dip moveout (DMO) process to correct data for the influence of dip, either before or after normal moveout (NMO) correction (Hale, 1984; Forel and Gardner, 1988). The TZO process transforms prestack seismic data in such a way that common‐midpoint (CMP) gathers are closer to being common reflection point gathers after the transformation.

A two‐layer stacking procedure to enhance converted waves

Geophysics ◽  
1993 ◽  
Vol 58 (7) ◽  
pp. 997-1001 ◽  
Author(s):  
B. L. N. Kennett
Keyword(s):  
Lower Layer ◽  
Effective Means ◽  
Water Layer ◽  
Physical Models ◽  
S Wave ◽  
P Waves ◽  
S Waves ◽  
Receiver Array ◽  
Sea Bed ◽  
Layer Stacking

For marine seismic sources quite efficient conversion of P‐waves to S‐waves can occur at hard seafloors, e.g., carbonate horizons in tropical waters. The S‐waves are reflected back from structures at depth and are reconverted to P‐waves in the water before detection by the receiver array. Such PSSP reflections can carry useful information on the structure beneath the sea bed but are most significant at large offsets and so are not easily stacked with a conventional normal moveout (NMO) procedure based on a hyperbolic time trajectory. A two‐layer stacking procedure that separates the water layer from the region below the seafloor provides a very effective means of extracting the PSSP arrivals, but also works well for P‐waves. There is no direct analytic form for the stacking trajectories but they can be calculated quite efficiently numerically. A further advantage is that the stacking velocity for S‐waves in the lower layer can be interpreted directly in terms of S‐wave propagation, so that S‐wave interval velocities can be found. Stacking procedures based on such simple physical models are likely to be useful in other cases where attention needs to be focused on a particular aspect of the wavefield.

Downhole seismic imaging of a massive sulfide orebody with mode‐converted waves, Halfmile lake, New Brunswick, Canada

Geophysics ◽  
2004 ◽  
Vol 69 (2) ◽  
pp. 318-329 ◽  
Author(s):  
Gilles Bellefleur ◽  
Christof Müller ◽  
David Snyder ◽  
Larry Matthews
Keyword(s):  
New Brunswick ◽  
Seismic Data ◽  
Massive Sulfide ◽  
Data Migration ◽  
P Waves ◽  
S Waves ◽  
Additional Imaging ◽  
Mineralized Zone ◽  
Converted Waves ◽  
Host Rocks

Multioffset, multiazimuth downhole seismic data were acquired at Halfmile lake, New Brunswick, to image known massive sulfide lenses and to investigate the potential existence of a steeply dipping mineralized zone connecting them. The massive sulfide lenses, which have significantly higher elastic impedances than host rocks, produce strong scattering. The downhole seismic data show prominent scattered (P‐P and S‐S) and mode‐converted (P‐S and S‐P) waves originating from the deposit. Such complex scattering from massive sulfide ore was not observed previously in vertical seismic profiling data. Migration of the scattered and mode‐converted waves from several shot points imaged different parts of the deepest lens. The scattered S‐waves and mode‐converted waves provide additional imaging capabilities that should be considered when selecting downhole seismic methods for mining exploration.

Thin-bed prestack spectral inversion

Geophysics ◽  
2009 ◽  
Vol 74 (4) ◽  
pp. R49-R57 ◽  
Author(s):  
J. Germán Rubino ◽  
Danilo Velis
Keyword(s):  
Time Window ◽  
A Priori ◽  
Amplitude Spectrum ◽  
Wavelet Spectrum ◽  
Model Parameters ◽  
Data Sets ◽  
S Wave ◽  
P Waves ◽  
S Waves ◽  
Zero Offset

Prestack seismic data has been used in a new method to fully determine thin-bed properties, including the estimation of its thickness, P- and S-wave velocities, and density. The approach requires neither phase information nor normal-moveout (NMO) corrections, and assumes that the prestack seismic response of the thin layer can be isolated using an offset-dependent time window. We obtained the amplitude-versus-angle (AVA) response of the thin bed considering converted P-waves, S-waves, and all the associated multiples. We carried out the estimation of the thin-bed parameters in the frequency (amplitude spectrum) domain using simulated annealing. In contrast to using zero-offset data, the use of AVA data contributes to increase the robustness of this inverse problem under noisy conditions, as well as to significantly reduce its inherent nonuniqueness. To further reduce the nonuniqueness, and as a means to incorporate a priori geologic or geophysical information (e.g., well-log data), we imposed appropriate bounding constraints to the parameters of the media lying above and below the thin bed, which need not be known accurately. We tested the method by inverting noisy synthetic gathers corresponding to simple wedge models. In addition, we stochastically estimated the uncertainty of the solutions by inverting different data sets that share the same model parameters but are contaminated with different noise realizations. The results suggest that thin beds can be characterized fully with a moderate to high degree of confidence below tuning, even when using an approximate wavelet spectrum.

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