Velocity‐independent datuming of seismic data

Kelamis, Panos G.; Verschuur, Eric; Berkhout, A. J.; Erickson, Kevin

doi:10.1190/1.1821047

Cited by 8 publications

(6 citation statements)

References 3 publications

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“…In order to accommodate more complex wave propagation effects Hindriks and Duijndam (), Kelamis et al . () and Al‐Ali and Verschuur (), proposed more flexible traveltime operators dedicated to the near‐surface area. Estimation of the traveltime operators can be achieved in a purely data‐driven manner, without estimating the velocity‐depth model, as pioneered by Berkhout (, ).…”

Section: Introductionmentioning

confidence: 99%

“…Bagaini and Alkhalifa (2006) proposed operators with low-order parametrization that focus the data at a certain datum level and Heilmann, Mann and Koglin (2006) considered a so-called common reflection surface (CRS)-based imaging solution, where the two-way reflection times are described with less than 10 parameters in the 2D case with surface topography included. In order to accommodate more complex wave propagation effects Hindriks and Duijndam (1999), Kelamis et al (1999) and Al-Ali and Verschuur (2006), proposed more flexible traveltime operators dedicated to the near-surface area. Estimation of the traveltime operators can be achieved in a purely data-driven manner, without estimating the velocity-depth model, as pioneered by Berkhout (1997aBerkhout ( , 1997b.…”

Section: Introductionmentioning

confidence: 99%

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Solving the complex near‐surface problem using 3D data‐driven near‐surface layer replacement

Sun

Verschuur

Vrolijk³

2014

Geophysical Prospecting

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In many land seismic situations, the complex seismic wave propagation effects in the near‐surface area, due to its unconsolidated character, deteriorate the image quality. Although several methods have been proposed to address this problem, the negative impact of 3D complex near‐surface structures is still unsolved to a large extent. This paper presents a complete 3D data‐driven solution for the near‐surface problem based on 3D one‐way traveltime operators, which extends our previous attempts that were limited to a 2D situation. Our solution is composed of four steps: 1) seismic wave propagation from the surface to a suitable datum reflector is described by parametrized one‐way propagation operators, with all the parameters estimated by a new genetic algorithm, the self‐adjustable input genetic algorithm, in an automatic and purely data‐driven way; 2) surface‐consistent residual static corrections are estimated to accommodate the fast variations in the near‐surface area; 3) a replacement velocity model based on the traveltime operators in the good data area (without the near‐surface problem) is estimated; 4) data interpolation and surface layer replacement based on the estimated traveltime operators and the replacement velocity model are carried out in an interweaved manner in order to both remove the near‐surface imprints in the original data and keep the valuable geological information above the datum. Our method is demonstrated on a subset of a 3D field data set from the Middle East yielding encouraging results.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Solving the complex near‐surface problem using 3D data‐driven near‐surface layer replacement

Sun

Verschuur

Vrolijk³

2014

Geophysical Prospecting

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“…Kelamis et al ͑1999͒ presented a waveequation datuming scheme based on the principles of common focusing point ͑CFP͒ technology ͑Berkhout, 1997a, b͒. The velocitydepth model is expressed in terms of model-independent propagation operators, which can be updated in an iterative way ͑Bolte and Verschuur, 1998͒.…”

Section: Introductionmentioning

confidence: 99%

Comparison between interferometric migration and reduced-time migration of common-depth-point data

Zhou

Jiang

et al. 2006

GEOPHYSICS

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One of the difficulties in seeing beneath salt is that the migration velocity in the salt and above it is not well known. This can lead to defocusing of migration images beneath the salt. In this paper, we show that reduced-time migration ͑RTM͒ and interferometric migration ͑IM͒ can partly mitigate this problem. RTM time-shifts the traces with the time difference between the calculated arrival time sg ref and the natural arrival time sg ref of a reference reflection, where s and g denote the source and receiver locations on the surface, respectively. We use the terms natural and calculated to represent, respectively, the arrival times that are velocity-independent ͑traveltimes directly extracted from the data without knowledge of the velocity model͒ and velocity-dependent ͑traveltimes calculated by ray tracing through a given velocity model͒. The benefit of RTM is a significant reduction of defocusing errors caused by errors in the migration velocity. IM, on the other hand, requires extrapolation of the surface data below salt using the natural arrival times sg ref of the subsalt reference reflector, and migration of the extrapolated data below the salt. The benefit with IM is that no salt velocity model is needed, so the model-based defocusing errors are, in theory, eliminated. To reduce computational time, we implement IM with a seminatural Green's function ͑combination of model-based calculated and picked natural traveltimes͒. Because no explicit data extrapolation is needed, IM with seminatural Green's functions is more cost-efficient than the standard IM. In this paper, we tested both RTM and IM with seminatural Green's functions on a synthetic and a field common-depth-point ͑CDP͒ data set, the latter from the Gulf of Mexico ͑GOM͒. Results show that both RTM and IM can remove the significant kinematic distortions caused by the overburden without knowledge of the overburden velocity.

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“…The approach of CFP, introduced by Berkhout (1992Berkhout ( , 1997; Thorbecke (1997), has been further developed under the DELPHI project of the Delft University of Technology. This technology has successfully been used for velocity independent redatuming Kelamis et al (1999) and for estimation of Green functions and velocity models Kabir and Verschuur (1997); Bolte et al (1999); Hegge et al (1999); Brisbourne et al (2000). In this research we have attempted to adapt for the first time this approach to shallow, high-resolution shear-wave seismic data.…”

Section: Introductionmentioning

confidence: 99%

A CFP Approach to Estimate the Shear-wave Velocity Distribution in the Shallow Subsoil

Thorbecke¹,

Ghose²

2007

Near Surface 2007 - 13th EAGE European Meeting of Environmental and Engineering Geophysics

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The CFP approach has been used to estimate Green functions for a high-resolution shear-wave reflection field dataset. This data set contains lateral variations of the near surface and has very low velocities. To estimate a velocity model for this kind of data is not an easy task. The CFP approach gives one-way Green function times which are accurate as indicated by the flat events at t=0. These Green functions contain all the information needed to build an accurate velocity model.

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Velocity‐independent datuming of seismic data

Cited by 8 publications

References 3 publications

Solving the complex near‐surface problem using 3D data‐driven near‐surface layer replacement

Solving the complex near‐surface problem using 3D data‐driven near‐surface layer replacement

Comparison between interferometric migration and reduced-time migration of common-depth-point data

A CFP Approach to Estimate the Shear-wave Velocity Distribution in the Shallow Subsoil

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