3‐D analytical migration velocity analysis I: Two‐step velocity estimation by reflector‐normal update

Meng, Zhaobo; Wyatt, Kay Dautenhahn

doi:10.1190/1.1820868

Cited by 15 publications

(4 citation statements)

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“…The relationship expressed in (19) forms the basis for the use of ADCIGs for MVA. Similar relationships have been extensively used in MVA methods based on constant-offset Kirchhoff migration (Etgen 1990;Stork 1992;Meng, Bleistein and Valasek 1999a;Meng, Bleistein and Wyatt 1999b). Equation (19) can be used directly to transform measurements of depth errors in ADCIGs into traveltime perturbations that can be inverted by a ray-based tomographic inversion or it can be the foundation for the derivation of accurate RMO functions to be applied to measure depth errors in ADCIGs.…”

Section: Kinematic Properties Of 3d Adcigsmentioning

confidence: 98%

3D angle‐domain common‐image gathers for migration velocity analysis

Biondi

Tisserant

2004

Geophysical Prospecting

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We analyze the kinematic properties of offset-domain Common Image Gathers (CIGs) and Angle-Domain CIGs (ADCIGs) computed by wavefield-continuation migration. Our results are valid regardless of whether the CIGs were obtained by using the correct migration velocity. They thus can be used as a theoretical basis for developing Migration Velocity Analysis (MVA) methods that exploit the velocity information contained in ADCIGs.We demonstrate that in an ADCIG cube the image point lies on the normal to the apparent reflector dip, passing through the point where the source ray intersects the receiver ray. Starting from this geometric result, we derive an analytical expression for the expected movements of the image points in ADCIGs as functions of the traveltime perturbation caused by velocity errors. By applying this analytical result and assuming stationary raypaths, we then derive two expressions for the Residual Moveout (RMO) function in ADCIGs. We verify our theoretical results and test the accuracy of the proposed RMO functions by analyzing the migration results of a synthetic data set with a wide range of reflector dips.Our kinematic analysis leads also to the development of a new method for computing ADCIGs when significant geological dips cause strong artifacts in the ADCIGs computed by conventional methods. The proposed method is based on the computation of offsetdomain CIGs along the vertical-offset axis (VOCIGs) and on the "optimal" combination of these new CIGs with conventional CIGs. We demonstrate the need for and the advantages of the proposed method on a real data set acquired in the North Sea.

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Section: Kinematic Properties Of 3d Adcigsmentioning

confidence: 98%

3D angle‐domain common‐image gathers for migration velocity analysis

Biondi

Tisserant

2004

Geophysical Prospecting

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“…For actual measurement, a method similar to velocity scan is used and the results are averaged within a horizontal range. Equation (5) and its variations have been widely used for 1D velocity scanning (Al-Yahya, 1989;Liu and Bleistein, 1992;Stork, 1992;Ji, 1997;Meng et al, 1999;Mosher et al, 2001;Jiao et al, 2002;Xia et al, 2006;Schneider, 2008), and have been modified to adapt to dipping reflectors. Although equation (5) is based on a very simple model, it provides a good estimate of the global shift and will considerably improve the inversion result.…”

Section: Recovering the Absolute Moveout In The Rmo Datamentioning

confidence: 99%

Velocity analysis using shot‐indexed sensitivity kernels: application to a complex geological model

He¹,

Xie²

2010

SEG Technical Program Expanded Abstracts 2010

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We investigate the capability of inverting large scale velocity errors through wave equation migration velocity analysis using shot-indexed sensitivity kernels. We find that the global shift of the image (absolute residual moveout) is crucial for constraining the large-scale velocity errors in the model when the shift of the image is more than a number of wavelengths. We estimate the shift through fitting the curvature of RMOs on CIGs and add this information into the inversion system. Although the extraction of the shift information is based on a simple model, including this information into RMO data considerably improves the inversion result. We apply our method to Sigsbee benchmark model and demonstrate that the velocity analysis based on sensitivity kernels can handle both large-scale and small-scale velocity errors in a complex geological environment.

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“…Liu (1997) derived an analytical approach to MVA, which imposes no limitation on offset, dip, or velocity distribution. Meng et al (1999aMeng et al ( , 1999b extended the analytical MVA method into 3-D. Liu et al (2001) proposed a common image gather velocity analysis in the angle domain. Sava and Biondi (2004) advanced diffraction focusing velocity analysis.…”

Section: Introductionmentioning

confidence: 99%

A Quadratic precision generalized nonlinear global optimization migration velocity inversion method

Ting

He³

et al. 2009

Appl. Geophys.

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An important research topic for prospecting seismology is to provide a fast accurate velocity model from pre-stack depth migration. Aiming at such a problem, we propose a quadratic precision generalized nonlinear global optimization migration velocity inversion. First we discard the assumption that there is a linear relationship between residual depth and residual velocity and propose a velocity model correction equation with quadratic precision which enables the velocity model from each iteration to approach the real model as quickly as possible. Second, we use a generalized nonlinear inversion to get the global optimal velocity perturbation model to all traces. This method can expedite the convergence speed and also can decrease the probability of falling into a local minimum during inversion. The synthetic data and Marmousi data examples show that our method has a higher precision and needs only a few iterations and consequently enhances the practicability and accuracy of migration velocity analysis (MVA) in complex areas.

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3‐D analytical migration velocity analysis I: Two‐step velocity estimation by reflector‐normal update

Cited by 15 publications

References 0 publications

3D angle‐domain common‐image gathers for migration velocity analysis

3D angle‐domain common‐image gathers for migration velocity analysis

Velocity analysis using shot‐indexed sensitivity kernels: application to a complex geological model

A Quadratic precision generalized nonlinear global optimization migration velocity inversion method

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