Seismic trace interpolation in the Fourier transform domain
By N. Gulunay. 2003
209 citations recorded by the source corpus.
Subfields: Geophysics, Ocean Engineering
View Paper: https://www.semanticscholar.org/paper/4df8fd866c7dbc15d6f062388444b5b017a54499
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Geophysics
- Xiaohong Chen
- Jianwei Ma
- Mauricio D. Sacchi
- Xiaoqun Zhang
- Yang Liu
- Jingwei Liang
- Jianjun Gao
- Sergey Fomel
In Ocean Engineering
- Xiaohong Chen
- Yang Liu
- Jianwei Ma
- Sergey Fomel
- Mauricio D. Sacchi
- Misha Elena Kilmer
- Mostafa Naghizadeh
- Jianjun Gao
Citations in the corpus
- Seismic data restoration via data-driven tight frame (2014, methodology): “…in some transform domain, such as the Radon transform (Kabir and Verschuur, 1995; Trad et al., 2002), Fourier transform (Sacchi et al., 1998; Gulunay, 2003; Liu and Sacchi, 2004; Xu et al., 2005; Abma and Kabir, 2006; Trad, 2009), seislet transform (Fomel and Liu, 2010; Liu and Fomel,…”
- Multistep autoregressive reconstruction of seismic records (2007, methodology): “Figures 12a and 12b show the result of first order interpolation of the final reconstructed section (Figure 8d) using Gulunay’s f-k interpolation method (Gulunay, 2003) and MSAR, respectively.”
- 5D seismic data completion and denoising using a novel class of tensor decompositions (2015, methodology): “Other methods exploit the statistical compactness or the predictably of a signal in the f-x domain (Spitz, 1991; Gulunay, 2003; Naghizadeh and Sacchi, 2007, 2010b).”
- A fast reduced-rank interpolation method for prestack seismic volumes that depend on four spatial dimensions (2013, methodology): “A second category groups methods based on prediction filters (Spitz, 1991; Porsani, 1999; Gulunay, 2003; Naghizadeh and Sacchi, 2007, 2009) which use the predictability of linear events in the frequencyspace domain to interpolate aliased data at high frequencies with filters derived from nonaliased…”
- Seismic data interpolation beyond aliasing using regularized nonstationary autoregression (2011, methodology): “(2010b) propose autoregressive spectral estimates to reconstruct aliased data and data with gaps. Seismic data are nonstationary. The standard PEF is designed under the assumption of stationary data and becomes less effective when this assumption is violated (Claerbout, 1992). Cutting data into over”