High density moveout parameter fields V and η. Part two: Simultaneous geostatistical filtering

Meur, D. Le; Siliqi, R.; Gamar, Fatiha; Smith, Lianna J.D.; Touré, J.P.; Herrmann, P.

doi:10.1190/1.1817747

Cited by 3 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the second part of this paper (Le Meur et al, 2003), the authors propose an appropriate route for the simultaneous filtering of V and η, specially designed for moveout correction purposes. The QC sorting of the fields prepares the input of the filtering route.…”

Section: Intelligent Sorting Of V η Pairsmentioning

confidence: 99%

High‐density moveout parameter fields V and η. Part one: Simultaneous automatic picking

Siliqi¹,

Meur²,

Gamar³

et al. 2003

SEG Technical Program Expanded Abstracts 2003

Self Cite

View full text Add to dashboard Cite

The focusing process for time imaging is improved drastically when high-density parameter fields are used. Large offsets, steep dips and finally the anisotropy of the subsurface revise the bases of time processing. Today, two parameters are required: velocity (V) and anellipticity (η). Picking V and η using two-pass techniques cannot be a long-term solution. The estimation of both parameters is very sensitive to the mute function separating near to far offsets. Picking both parameters simultaneously using dense bispectral analysis overcomes this situation.We are proposing in this paper an original parameterization of the non-hyperbolic moveout, which increases the sensitivity of the analysis and allows static moveout corrections, necessary for automatic dense pickings.An intelligent QC sorting of the raw V and η fields, based on lateral coherency of the semblance and the Dixinversion ability of local V and η functions, prepares skeleton fields for simultaneous geostatistical filtering of both parameters.

show abstract

Section: Intelligent Sorting Of V η Pairsmentioning

confidence: 99%