Seismic data irregularly sampled in two dimensions is transformed to the Fourier/Radon domain using a least squares formulation where the inverse transform, from the Fourier/Radon to the spatial domain is used as a forward model. By a proper choice of the region of support, the total number of parameters is limited (yet such that the actual data is optimally contained), leading to a stable inversion. Subsequently the data can be transformed to any desired grid in the spatial domain. Also, using suitable transforms, signal and noise map to different parts of the transform domain and can be separated. The method is applied to synthetic and marine data. I. Introduction In exploration seismology structural information of the subsurface is obt...
Many seismic data processing and imaging processes require densely and regularly sampled data, where...
Seismic data are often irregularly and inadequately sampled spatially due to economic and logistic c...
this paper is to introduce an efficient method to resample the 2D irregularly sampled data on a regu...
In seismic exploration an image of the subsurface is generated from seismic data through various dat...
In seismic exploration an image of the subsurface is generated from seismic data through various dat...
Seismic data acquisition is frequently carried out at irregular sampling intervals along spatial coo...
In seismic data analysis, recorded data often are transformed to various domains to discriminate ag...
In seismic data analysis, recorded data often are transformed to various domains to discriminate ag...
Least-squares Fourier reconstruction is basically a discrete linear inverse problem that attempts to...
Least-squares Fourier reconstruction is basically a discrete linear inverse problem that attempts to...
Least-squares Fourier reconstruction is basically a discrete linear inverse problem that attempts to...
The development of new tools for high-resolution seismic imaging has been for many years one of the ...
Fourier reconstruction is basically a linear inverse problem that attempts to recover the Fourier sp...
The Radon transform (RT) has many desirable properties which make it particularly useful for multip...
This work determines whether the amount of frequency components present in the data can be reduced, ...
Many seismic data processing and imaging processes require densely and regularly sampled data, where...
Seismic data are often irregularly and inadequately sampled spatially due to economic and logistic c...
this paper is to introduce an efficient method to resample the 2D irregularly sampled data on a regu...
In seismic exploration an image of the subsurface is generated from seismic data through various dat...
In seismic exploration an image of the subsurface is generated from seismic data through various dat...
Seismic data acquisition is frequently carried out at irregular sampling intervals along spatial coo...
In seismic data analysis, recorded data often are transformed to various domains to discriminate ag...
In seismic data analysis, recorded data often are transformed to various domains to discriminate ag...
Least-squares Fourier reconstruction is basically a discrete linear inverse problem that attempts to...
Least-squares Fourier reconstruction is basically a discrete linear inverse problem that attempts to...
Least-squares Fourier reconstruction is basically a discrete linear inverse problem that attempts to...
The development of new tools for high-resolution seismic imaging has been for many years one of the ...
Fourier reconstruction is basically a linear inverse problem that attempts to recover the Fourier sp...
The Radon transform (RT) has many desirable properties which make it particularly useful for multip...
This work determines whether the amount of frequency components present in the data can be reduced, ...
Many seismic data processing and imaging processes require densely and regularly sampled data, where...
Seismic data are often irregularly and inadequately sampled spatially due to economic and logistic c...
this paper is to introduce an efficient method to resample the 2D irregularly sampled data on a regu...