Where are the fault‐plane reflections?

Lynn, Walt; González, Alfonso; MacKay, Scott

doi:10.1190/1.1888724

Cited by 13 publications

(9 citation statements)

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“…For example, Lynn et al (1991) suggest that ignoring anisotropy may, in some areas, compensate for the errors in constant-velocity DMO. In such areas, if we ignore anisotropy, we may observe that constant-velocity DMO enables both horizontal and steep reflections to be stacked with the same velocity, and that squeezed DMO does not.…”

Section: Offset (Km)mentioning

confidence: 99%

Squeezing dip moveout for depth‐variable velocity

Hale

Artley

1993

GEOPHYSICS

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In dip‐moveout (DMO) processing, velocity variations with depth can be handled approximately by squeezing a constant‐velocity DMO operator to narrow its impulse response. This squeezed DMO approximation provides a computationally efficient and reasonably accurate method of DMO correction for depth‐variable velocity. DMO is squeezed by two modifications to constant‐velocity DMO. One modification is a squeezing function of time that depends only on simple time averages of velocity that are likely to be known before DMO is applied. This squeeze function ensures that squeezed DMO accurately handles moderately steep reflections and can be incorporated with simple time stretching before and after DMO, without any changes to existing constant‐velocity DMO methods. The second modification is a constant squeezing factor, which may be used to tune squeezed DMO to better handle steep reflections. This factor requires only trivial changes to constant‐velocity DMO methods. Tests with both synthetic and recorded seismic data suggest that squeezed DMO is an effective method for handling velocity variations with depth. These tests also show that the differences between constant‐velocity DMO and squeezed DMO can be significant.

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Section: Offset (Km)mentioning

confidence: 99%

Squeezing dip moveout for depth‐variable velocity

Hale

Artley

1993

GEOPHYSICS

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“…Not only velocity analysis, but practically all other conventional seismic processing and interpretation techniques become inaccurate if the medium is anisotropic (Lynn et al, 1991;Alkhalifah and Larner, 1994;Tsvankin, 1995;Tsvankin and Thomsen, 1995).…”

Section: Introductionmentioning

confidence: 99%

Feasibility of estimating vertical transverse isotropy from microseismic data recorded by surface monitoring arrays

2011

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Microseismic data recorded by surface monitoring arrays can be used to estimate the effective anisotropy of the overburden and reservoir. In this study we used the inversion of picked Pwave arrival times to estimate the Thomsen parameter δ and the anellipticity coefficient η. This inversion employs an analytic equation of P-wave traveltimes as a function of offset in homogeneous, transversely isotropic media with a vertical axis of symmetry. We considered a star-like distribution of receivers and, for this geometry, we analyzed the sensitivity of the inversion method to picking noise and to uncertainties in the P-wave vertical velocity and source depth. Long offsets, as well as a high number of receivers per line, improve the estimation of δ and η from noisy arrival times. However, if we do not use the correct value of the P-wave vertical velocity or source depth, the long-offset may increase the inaccuracy in the estimation of the anisotropic parameters. Such inaccuracy cannot be detected from time residuals. We also applied this inversion to field data acquired during the hydraulic fracturing of a gas shale reservoir and compared the results with the anisotropic parameters estimated from synthetic arrival times computed for an isotropic layered medium. The effective anisotropy from the inversion of the field data cannot be explained by layering only and is partially due to the intrinsic anisotropy of the reservoir and/ or overburden. This study emphasizes the importance of using accurate values of the vertical velocity and source depth in the P-wave arrival time inversion for estimating anisotropic parameters from passive seismic data.

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“…If the velocity of the sloping event is higher, then, in most cases, anisotropy is present, and η is positive. If the medium is also vertically inhomogeneous, then the anisotropy must be even more significant, because inhomogeneity tends to reduce the influence of anisotropy on the isotropic homogeneous DMO operation (Lynn et. al., 1991;Alkhalifah, 1996).…”

Section: Stacking-velocity Measurementsmentioning

confidence: 99%

Seismic data processing in vertically inhomogeneous TI media

Alkhalifah

1997

GEOPHYSICS

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The first and most important step in processing data in transversely isotropic (TI) media for which velocities vary with depth is parameter estimation. The multilayer normal-moveout (NMO) equation for a dipping reflector provides the basis for extending the TI velocity analysis of Alkhalifah and Tsvankin to vertically inhomogeneous media. This NMO equation is based on a root-mean-square (rms) average of interval NMO velocities that correspond to a single ray parameter, that of the dipping event. Therefore, interval NMO velocities [including the normal-moveout velocity for horizontal events, V nmo (0)] can be extracted from the stacking velocities using a Dix-type differentiation procedure. On the other hand, η, which is a key combination of Thomsen's parameters that time-related processing relies on, is extracted from the interval NMO velocities using a homogeneous inversion within each layer. Time migration, like dip moveout, depends on the same two parameters in vertically inhomogeneous media, namely V nmo (0) and η, both of which can vary with depth. Therefore, V nmo (0) and η estimated using the dip dependency of P-wave moveout velocity can be used for TI time migration. An application of anisotropic processing to seismic data from offshore Africa demonstrates the importance of considering anisotropy, especially as it pertains to focusing and imaging of dipping events.

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Where are the fault‐plane reflections?

Cited by 13 publications

References 0 publications

Squeezing dip moveout for depth‐variable velocity

Squeezing dip moveout for depth‐variable velocity

Feasibility of estimating vertical transverse isotropy from microseismic data recorded by surface monitoring arrays

Seismic data processing in vertically inhomogeneous TI media

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