Simultaneous Joint Inversion for Surface-consistent Amplitude and Deconvolution

Garceran, K.; Meur, D. Le

doi:10.3997/2214-4609.20148167

Cited by 6 publications

(5 citation statements)

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“…The root-mean-square (RMS) amplitude value of a seismic trace, computed within a defined time window is used in the surface-consistent equations (Taner and Koelher, 1981). Each RMS amplitude A is decomposed into a combination of two terms: a source term AS and a receiver term A R as: A = ASAR The log domain is used and the system is solved using a least-squares approach (Garceran and Le Meur, 2012). In the two-term decomposition, the solution is offset by a constant, which means that the true solution only differs by an unknown scalar.…”

Section: Description Of the Methodsmentioning

confidence: 99%

Data-constrained Surface-consistent Amplitude Corrections

Garceran¹,

Popa²,

Mesaabi³

et al. 2013

London 2013, 75th Eage Conference en Exhibition Incorporating SPE Europec

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Section: Description Of the Methodsmentioning

confidence: 99%

Data-constrained Surface-consistent Amplitude Corrections

Garceran¹,

Popa²,

Mesaabi³

et al. 2013

London 2013, 75th Eage Conference en Exhibition Incorporating SPE Europec

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“…In our workflow, the source wavelet is estimated from the surface-consistent deconvolution (Taner et al, 1981;Garceran et al, 2012;Zhang et al, 2015). In surfaceconsistent deconvolution, the recorded seismogram can be modeled as:…”

Section: Source Wavelet and Spatially-variant Waveformmentioning

confidence: 99%

A practical acoustic full waveform inversion workflow applied to a 3D land dynamite survey

Mei

Tong

2015

SEG Technical Program Expanded Abstracts 2015

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Full waveform inversion (FWI) has been used to successfully build high-resolution earth velocity models for marine data. For land data sets, FWI using acoustic wave equation (acoustic-FWI) remains challenging due to the lack of modeling of strong surface waves, converted waves, phase dispersion, and near-surface weathering layer distortion. In addition, for land dynamite surveys, the source wavelet information is usually missing, and the recorded individual waveform varies greatly because of the spatially variant shot characteristics such as source charge size, shot depth, and hole-pattern as well as the distortion caused by the near-surface weathering layer. We designed and implemented a practical and comprehensive workflow to mitigate missing source wavelet information and vast spatial variation in the waveforms and to address the common challenges of acoustic-FWI application on land surveys during field data preparation.

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“…The surface topography is incised by several local rios causing large amplitudes variations from shot to shot. Therefore simultaneous joint inversion for surface consistent amplitude and deconvolution was computed on shot gathers with strong noise attenuation conditioning (Garceran et Le Meur, 2012). Operators and scalar were applied thereafter on mildly de-noised shots.…”

Section: Time Processingmentioning

confidence: 99%