1991
DOI: 10.1190/1.1443082
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Velocity inversion by differential semblance optimization

Abstract: Differential semblance optimization (DSO) is an approach to inversion of reflection seismograms which avoids the severe convergence difficulties associated with nonlinear least‐squares inversion. The method exploits both moveout and amplitude characteristics of reflections. We have implemented a version appropriate to plane‐wave (p‐tau) seismograms and layered constant‐density acoustic earth models. Theoretical and numerical analyses of this version of DSO indicate that stable and reasonably accurate estimates… Show more

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Cited by 406 publications
(224 citation statements)
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“…In DSVA, the perturbed image is computed by applying the fully automated differential-semblance operator (DSO) (Symes and Carazzone, 1991) to SODCIGs or ADCIGs. When applied to SODCIGs, DSO minimizes the energy not focused at zerooffset.…”
Section: Discussionmentioning
confidence: 99%
“…In DSVA, the perturbed image is computed by applying the fully automated differential-semblance operator (DSO) (Symes and Carazzone, 1991) to SODCIGs or ADCIGs. When applied to SODCIGs, DSO minimizes the energy not focused at zerooffset.…”
Section: Discussionmentioning
confidence: 99%
“…[47]) or subsurface offset in the differential semblance approach (cf. [34]). The operators A we (α) are microlocally invertible under certain conditions on the ray geometry [48] (for small p).…”
Section: Velocity Continuation Of Common-image Point Gathers In the Pmentioning
confidence: 99%
“…We show an example, revealing the potential of the comprehensive theory presented here (Section 4). Velocity continuation of image gathers can directly be exploited in reflection tomography, the problem of determining the background velocity, see [34,35,32,36,37].…”
Section: Introductionmentioning
confidence: 99%
“…In the absence of other information one can use the DSO penalty function P  (x,)=|| (Figure 1a), shown to produce high-quality inversion results (Symes and Carazzone, 1991;Shen et al, 2005).…”
Section: D Asm-idt Theorymentioning
confidence: 99%
“…A key decision in the ASM-IDT inversion procedure is to specify a judicious penalty operator that eliminates energy already optimally focused in the extended image gather volume at the zero correlation lag and upweights that poorly focused at nonzero correlation lags. A common way to accomplish this is through applying a differential semblance operator (DSO) (Symes and Carazzone, 1991;Shen et al, 2005) that cancels out a perfectly focused image at the zero correlation lag. However, there are other classes of penalty functions that can be used in the ASM-IDT inversion procedure; e.g., ones that compensate for illumination irregularities (Yang et al, 2012) or more fully account for scattering theory (Albertin, 2011) The 4D ASM-IDT velocity estimation problem shares many similarities with -and may be regards an extension of -3D ASM-IDT inversion.…”
Section: Introductionmentioning
confidence: 99%