An Exact Solution of the Equation of the Conversion Point for P-SV Converted Wave at a Horizontal Reflector

2005 ◽  
Vol 48 (5) ◽  
pp. 1261-1267 ◽  
Author(s):  
Chun-Fang YUAN ◽  
Su-Ping PENG ◽  
Liang-Liang YANG
2004 ◽  
Vol 56 (3) ◽  
pp. 155-163 ◽  
Author(s):  
Fredy A.V. Artola ◽  
Ricardo Leiderman ◽  
Sergio A.B. Fontoura ◽  
Mércia B.C. Silva

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. S99-S110
Author(s):  
Daniel A. Rosales ◽  
Biondo Biondi

A new partial-prestack migration operator to manipulate multicomponent data, called converted-wave azimuth moveout (PS-AMO), transforms converted-wave prestack data with an arbitrary offset and azimuth to equivalent data with a new offset and azimuth position. This operator is a sequential application of converted-wave dip moveout and its inverse. As expected, PS-AMO reduces to the known expression of AMO for the extreme case when the P velocity is the same as the S velocity. Moreover, PS-AMO preserves the resolution of dipping events and internally applies a correction for the lateral shift between the common-midpoint and the common-reflection/conversion point. An implementation of PS-AMO in the log-stretch frequency-wavenumber domain is computationally efficient. The main applications for the PS-AMO operator are geometry regularization, data-reduction through partial stacking, and interpolation of unevenly sampled data. We test our PS-AMO operator by solving 3D acquisition geometry-regularization problems for multicomponent, ocean-bottom seismic data. The geometry-regularization problem is defined as a regularized least-squares-objective function. To preserve the resolution of dipping events, the regularization term uses the PS-AMO operator. Application of this methodology on a portion of the Alba 3D, multicomponent, ocean-bottom seismic data set shows that we can satisfactorily obtain an interpolated data set that honors the physics of converted waves.


Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. N1-N10
Author(s):  
Keshan Zou

Analyzing the Aki-Richards equation for converted waves, I found that it is possible to decouple the effect of density contrast from that of shear velocity contrast. The two terms were mixed when the P-wave incident angle was less than 30°, but they started to separate at a middle angle range (approximately 40°). The term related to S-wave velocity contrast reached zero at an incident angle around 60°. However, the other term, which was related to the density contrast, did not reverse polarity until 90°. Furthermore, this density term reached almost the maximum (magnitude) around 60°. Based on those characteristics, I designed a new method called “S-Zero Stack” to capture the density contrast reliably at the subsurface interface without going to inversion. S-Zero Stack captured subsurface density anomalies using a special stacking method. It is simple but robust, even when there is noise in the common-conversion-point gathers. Combined with the traditional P-wave amplitude-variation-with-offset technique, S-Zero Stack of PS-waves may help discriminate commercial gas from fizz in gas sand and could be a useful tool in shale gas exploration to locate lower-density anomalies (sweet spots).


Geophysics ◽  
2005 ◽  
Vol 70 (4) ◽  
pp. D29-D36 ◽  
Author(s):  
Mirko van der Baan

Common-conversion-point (CCP) sorting of P-SV converted-wave data is conventionally done by first sorting data into common asymptotic-conversion-point (CACP) gathers and then computing the involved CCP shifts from analytic approximations. I explore an alternative method where the latter step is replaced by an entirely data-driven approach. Moveout curves of correlated P-P and P-SV reflections in collocated CMP and CACP gathers are first scanned for points of equal slowness. A common-source slowness indicates that the downgoing branches of the P-P and P-SV waves overlap if the conversion occurs at the reflecting interface. The P-SV conversion point is then assumed to be situated underneath the associated P-P wave midpoint. A migration of amplitudes from CACP to CCP gathers is straightforward once the exact CCP position is known. This data-driven approach requires kinematic information only and is exact for laterally homogeneous media with arbitrary strength of anisotropy if horizontal symmetry planes are present at all depths. Both time-offset and τ-p domain implementations are possible, although the latter are preferred.


Geophysics ◽  
1999 ◽  
Vol 64 (3) ◽  
pp. 678-690 ◽  
Author(s):  
Leon Thomsen

Converted‐wave processing is more critically dependent on physical assumptions concerning rock velocities than is pure‐mode processing, because not only moveout but also the offset of the imaged point itself depend upon the physical parameters of the medium. Hence, unrealistic assumptions of homogeneity and isotropy are more critical than for pure‐mode propagation, where the image‐point offset is determined geometrically rather than physically. In layered anisotropic media, an effective velocity ratio [Formula: see text] (where [Formula: see text] is the ratio of average vertical velocities and γ2 is the corresponding ratio of short‐spread moveout velocities) governs most of the behavior of the conversion‐point offset. These ratios can be constructed from P-wave and converted‐wave data if an approximate correlation is established between corresponding reflection events. Acquisition designs based naively on γ0 instead of [Formula: see text] can result in suboptimal data collection. Computer programs that implement algorithms for isotropic homogeneous media can be forced to treat layered anisotropic media, sometimes with good precision, with the simple provision of [Formula: see text] as input for a velocity ratio function. However, simple closed‐form expressions permit hyperbolic and posthyperbolic moveout removal and computation of conversion‐point offset without these restrictive assumptions. In these equations, vertical traveltime is preferred (over depth) as an independent variable, since the determination of the depth is imprecise in the presence of polar anisotropy and may be postponed until later in the flow. If the subsurface has lateral variability and/or azimuthal anisotropy, then the converted‐wave data are not invariant under the exchange of source and receiver positions; hence, a split‐spread gather may have asymmetric moveout. Particularly in 3-D surveys, ignoring this diodic feature of the converted‐wave velocity field may lead to imaging errors.


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