Multistep autoregressive reconstruction of seismic records

By Mostafa Naghizadeh, Mauricio D. Sacchi. 2007

168 citations recorded by the source corpus.

Subfields: Geophysics, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/d2a93680b4135eddc5434dc894f46259c23e9479

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In Geophysics

In Mechanical Engineering

Citations in the corpus

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…”
Dreamlet-based interpolation using POCS method (2014, methodology): “Using mask function, anti-aliasing seismic data interpolation is obtained in Fourier domain (Gao et al., 2012; Naghizadeh, 2012) and curvelet domain (Naghizadeh and Sacchi, 2010), while performance is easily affected by the parameter setting.”
Tensor completion based on nuclear norm minimization for 5D seismic data reconstruction (2013, methodology): “Prediction filtering methods use the predictability of the signal in the F−X or T−X domain (Spitz, 1991; Naghizadeh and Sacchi, 2007).”
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).”
Curvelet-based POCS interpolation of nonuniformly sampled seismic records (2012, methodology): “Recently, Naghizadeh and Sacchi (2007) gave a multistep autoregressive (MSAR) method, trying to predict all the frequencies from the low frequency part.”
Seismic data restoration via data-driven tight frame (2014, background): “…can be implemented in the time-spatial t-x domain (Crawley et al., 1999; Liu and Fomel, 2011), the frequency-spatial f-x domain (Spitz, 1991; Porsani, 1999; Naghizadeh and Sacchi, 2007), the frequency-wavenumber f-x domain (Gulunay, 2003), and even the curvelet domain (Naghizadeh and Sacchi, 2010).”