A fast reduced-rank interpolation method for prestack seismic volumes that depend on four spatial dimensions

By Jianjun Gao, Mauricio D. Sacchi, Xiaohong Chen. 2013

149 citations recorded by the source corpus.

Subfields: Applied Mathematics, Computer Vision and Pattern Recognition, Geophysics

View Paper: https://www.semanticscholar.org/paper/89b8dbb1b3779b56d0cde60792fb9ce7bf7d3987

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In Applied Mathematics

In Computer Vision and Pattern Recognition

In Geophysics

Citations in the corpus

Fast dual-domain reduced-rank algorithm for 3D deblending via randomized QR decomposition (2016, methodology): “Alternative rapid rank-reduction methods, such as Lanczos bidiagonalization and randomized SVD, have recently been applied for seismic data reconstruction and denoising (Gao et al., 2011, 2013; Oropeza and Sacchi, 2011).”
5D seismic data completion and denoising using a novel class of tensor decompositions (2015, methodology): “Other variations enforce the low rank through less expensive matrix decomposition, completely avoiding the calculation of the SVD (Gao et al., 2011, 2013; Kumar et al., 2013) or applying the SVD to a randomized subset of the original matrix (Oropeza and Sacchi, 2010, 2011).”
Damped multichannel singular spectrum analysis for 3D random noise attenuation (2015, background): “…transform domain thresholding strategies (Donoho, 1995; Neelamani et al., 2008; Fomel and Liu, 2010; Chen et al., 2014, 2016) and Cadzow filtering (Trickett, 2008; Trickett and Burroughs, 2009) or multichannel singular spectrum analysis (Oropeza and Sacchi, 2011; Chiu, 2013; Gao et al., 2013).”
Seismic data restoration via data-driven tight frame (2014, methodology): “For the other three methods, it takes about 1 min for shearlet method, about 10 s for the TF method, and less than 10 s for the POCS method.”
Dreamlet-based interpolation using POCS method (2014, methodology): “Methods for interpolation can be divided into three categories (Gao et al., 2013): First, methods based onmathematical transform and signal analysis (Herrmann and Hennenfent, 2008; Naghizadeh and Innanen, 2011; Naghizadeh and Sacchi, 2010; Trad et al.”
Robust reduced-rank filtering for erratic seismic noise attenuation (2015, methodology): “…the singular spectrum analysis (SSA) method (Sacchi, 2009; Oropeza and Sacchi, 2011), also known as Cadzow filtering (Trickett, 2008; Trickett and Burroughs, 2009), was introduced to attenuate incoherent noise and for seismic data reconstruction (Oropeza and Sacchi, 2011; Gao et al., 2013).”
Multidimensional simultaneous random plus erratic noise attenuation and interpolation for seismic data by joint low-rank and sparse inversion (2015, methodology): “…subspace methods based on the Lanczos iteration (Golub and Kahan, 1965; Golub and Van Loan, 2013) such as in Trickett (2003), Korobeynikov (2010), Gao et al. (2013), or randomized methods on which we will focus, already used in Oropeza and Sacchi (2011), although without the advantages…”
Interpolation and denoising of high-dimensional seismic data by learning a tight frame (2015, methodology): “Rank-reduced methods (Trickett et al., 2010; Kreimer and Sacchi, 2012; Gao et al., 2013; Ma, 2013; Yang et al., 2013) assume that the seismic data itself or constant-frequency slices of the fully sampled data can be reformulated to a low-rank matrix for reconstruction purpose.”