Article history: Available online 3 May 2016

Today, the problem of surface-related multiples, especially in shallow water, is not fully solved. Although surface-related multiple elimination (SRME) method has proved to be successful on a large number of data cases, the involved adaptive subtraction acts as a weak link in this methodology, where primaries can be distorted due to their interference with multiples. Therefore, recently, SRME h...

Radio occultation (RO) has been proven to be a powerful technique for ionospheric electron density profile (EDP) retrieval. The Abel inversion currently used in RO EDP retrieval has degraded performance in regions with large horizontal gradients because of an assumption of spherical symmetry as indicated by many studies. Some alternative methods have been proposed in the past; the global ionosp...

The theory of compressed sensing suggests that successful inversion of an image of the physical world (e.g., a radar/sonar return or a sensor array snapshot vector) for the source modes and amplitudes can be achieved at measurement dimensions far lower than what might be expected from the classical theories of spectrum or modal analysis, provided that the image is sparse in an apriori known bas...

Abstract. One of the main tasks in 3D geological modeling is boundary parametrization subsurface from observations and geophysical inversions. Several approaches have been developed for geometric inversion joint datasets. However, robust, quantitative integration models datasets with different spatial coverage, resolution, levels sparsity remains challenging. promising approach recovering units...

The problem of matrix inversion is central to many applications of Numerical Linear Algebra. When the matrix to invert is dense, little can be done to avoid the costly O(n) process of Gaussian Elimination. When the matrix is symmetric, one can use the Cholesky Factorization to reduce the work of inversion (still O(n), but with a smaller coefficient). When the matrix is both sparse and symmetric...

The LSQR algorithm developed by Paige and Saunders (1982) is considered one of the most efficient and stable methods for solving large, sparse, and ill-posed linear (or linearized) systems. In seismic tomography, the LSQR method has been widely used in solving linearized inversion problems. As the amount of seismic observations increase and tomographic techniques advance, the size of inversion ...

This paper generalizes the parallel selected inversion algorithm called PSelInv to sparse nonsymmetric matrices. We assume a general sparse matrix A has been decomposed as PAQ = LU on a distributed memory parallel machine, where L,U are lower and upper triangular matrices, and P,Q are permutation matrices, respectively. The PSelInv method computes selected elements of A. The selection is confin...

Information about reservoir properties usually comes from two sources: seismic data and well logs. The former provide an indirect, low resolution image of rock velocity and density. The latter provide direct, high resolution (but laterally sparse) sampling of these and other rock parameters. An important problem in reservoir characterization is how best to combine these data sets, allowing the ...