scholarly journals INVERSION OF INTERVAL VELOCITIES: APPLICATION TO A GEOLOGICAL MODEL FROM A PRE-SALT AREA

2015 ◽  
Vol 33 (1) ◽  
pp. 19
Author(s):  
Thais Gomes Santana ◽  
Amin Bassrei
Keyword(s):  
Singular Value Decomposition ◽  
Relative Entropy ◽  
A Priori ◽  
Singular Value ◽  
A Priori Information ◽  
Minimum Relative Entropy ◽  
Priori Information ◽  
Interval Velocities ◽  
Value Decomposition

ABSTRACT. Seismic methods study the propagation of elastic wave fields inside the Earth, with the goal to provide subsurface images. In this work, the determination of the time interval velocity distribution is the main information provided. Several synthetic models were used, where one is based in a real situation, a dip section from the pre-salt region, central part of the Santos Basin, Brazil. Themethods used to determine interval velocities were based on the Dix transform, singular value decomposition (SVD) and minimum relative entropy (MRE). Dix transform showed excellent results when used in simple geological models, and was coincident to the other two methods. With the addition of a priori information, the SVD and MRE showed to be good methods for the determination of the interval velocities. When comparing SVD and MRE methods the latter showed the best results. When the a priori information is constant, the SVD and MRE methods give the same velocity estimate given from the direct application of the Dix transform.Keywords: inversion of interval velocities, singular value decomposition, minimum relative entropy, pre-salt.RESUMO. Os métodos sísmicos utilizam o campo de propagação de ondas elásticas no interior da Terra, com o objetivo de fornecer imagens da subsuperfície. Neste trabalho, a determinação do campo de velocidades intervalares é a principal informação a ser fornecida. Foram utilizados modelos sintéticos, sendo um deles baseado em uma situação real, no caso uma sessão dip , na região do pré-sal, parte central da Bacia de Santos. Os métodos usados para determinar as velocidades intervalares foram a transformada de Dix, a decomposição por valores singulares (SVD) e a entropia relativa mínima (MRE). A transformada de Dix, quando usada em modelos geológicos mais simples apresentou excelentes resultados coincidente aos outros dois métodos. Com a adição de estimativas a priori , o SVD e o MRE se mostraram como bons métodos para a determinação das velocidades intervalares, sendo que o MRE apresentou os melhores resultados. Quando a informação a priori é constante, os métodos do SVD e MRE fornecem a mesma estimativa de velocidade que é obtida pela transformada de Dix.Palavras-chave: inversão de velocidades intervalares, decomposição por valores singulares, entropia relativa mínima, pré-sal.

Using a Priori Information in Energy-Dispersive X-Ray Fluorescence Analysis of Complex Samples

1991 ◽  
Vol 35 (B) ◽  
pp. 1205-1209
Author(s):  
I. A. Kondurov ◽  
P. A. Sushkov ◽  
T. M. Tjukavina ◽  
G. I. Shulyak
Keyword(s):  
High Temperature Superconductors ◽  
A Priori ◽  
Fluorescence Analysis ◽  
A Priori Information ◽  
Complex Samples ◽  
X Ray ◽  
Edxrf Analysis ◽  
The Matrix ◽  
Priori Information

In multielement EDXRF analysis of very complex unknowns, some problems in data evaluation may be simplified if one can take into account a priori information on the properties of the incident and detected radiations, and also available data on the matrix of the sample. The number of variables can be drastically shortened in the LSM procedures in this case. One of the best examples of complex unknowns is the determination of the rare earth element content of ores, and most recently in samples of high temperature superconductors (HiTc).

scholarly journals Determination of Broadening Functions using the Singular Value Decomposition (SVD) Technique

1999 ◽  
Vol 170 ◽  
pp. 82-90 ◽  
Author(s):  
Slavek Rucinski
Keyword(s):  
Correlation Function ◽  
Singular Value Decomposition ◽  
Cross Correlation ◽  
Singular Value ◽  
Spectral Lines ◽  
Linear Inversion ◽  
Standard Tool ◽  
Contact Binaries ◽  
Value Decomposition

AbstractThe cross-correlation function (CCF) has become the standard tool for extraction of radial-velocity and broadening information from high resolution spectra. It permits integration of information which is common to many spectral lines into one function which is easy to calculate, visualize and interpret. However, the CCF is not the best tool for many applications where it should be replaced by the proper broadening function (BF). Typical applications requiring use of BFs rather than CCFs involve finding locations of star spots, studies of projected shapes of highly distorted stars such as contact binaries (as no assumptions can be made about BF symmetry or even continuity) and [Fe/H] metallicity determinations (good baselines and avoidance of negative lobes are essential). It is stressed that the CCFs are not broadening functions. This note concentrates on the advantages of determining BFs through the process of linear inversion, preferably accomplished using the singular value decomposition (SVD). Some basic examples of numerical operations are given in the IDL programming language.

A New Algorithm to Compensate Ionosphere Phase Contamination

2014 ◽  
Vol 644-650 ◽  
pp. 4551-4554
Author(s):  
Hui Ai ◽  
Jin Feng Hu ◽  
Wan Ge Li ◽  
Zhi Rong Lin ◽  
Ya Xuan Zhang
Keyword(s):  
Fourier Transform ◽  
Singular Value Decomposition ◽  
Prior Information ◽  
Hankel Matrix ◽  
Singular Value ◽  
Echo Signal ◽  
Rank Reduction ◽  
Coherent Integration ◽  
Priori Information ◽  
Value Decomposition

The echo signals of sky-wave over-the-horizon radar involve ionospheric phase contamination with spectrum expansion. The bragg peaks expand and cover the frequency spectrum of low speed target. So ionospheric phase decontamination is necessary before coherent integration. The traditional Hankel Rank Reduction (HRR) phase decontamination method constructs the Hankel matrix by folding the echo signal, estimating instantaneous frequency through singular value decomposition. But HRR method requires the prior information of signal components. The estimation is invalid without priori information. The algorithm presented in this paper does not require the priori information. The algorithm based on matched fourier transform can accurately estimate the phase contamination function for the clutter noise ratio is high. Simulation shows that the proposed algorithm has better performance in phase decontamination.

Defect Structure Analysis in Semiconductors by HREM and New Compatible Techniques

1984 ◽  
Vol 42 ◽  
pp. 364-367
Author(s):  
J.C.H. Spence
Keyword(s):  
A Priori ◽  
Heavy Atom ◽  
A Priori Information ◽  
Atomic Column ◽  
Structure Information ◽  
Semiconductor Defects ◽  
Semiconductor Interfaces ◽  
Priori Information ◽  
Similar Unit

The determination of atomic co-ordinates from HREM images has greatly improved our understanding of semiconductor defects, but chemical and electronic structure information are also needed. Thus suitable HREM compatible techniques must be developed and this article reviews some of these.The intimate relationship between resolution and noise has been exploited for many years in biological HREM. Since the centre of a very broad gaussion peak can be found with an accuracy which depends mainly on noise, heavy atom positions in inorganic crystals can be determined from HREM images with an accuracy of ±0.1Å (well beyond the information and point resolution limits of an HREM image) by the addition of similar unit cell images. This method makes extensive use of a-priori information (that there is only one atomic column rather than an unresolved pair, other atom co-ordinates, symmetry) and fails for isolated defects, but may be useful for semiconductor interfaces and surfaces.

Determination of the pKa Values of trans-Resveratrol, a Triphenolic Stilbene, by Singular Value Decomposition. Comparison with Theory

2020 ◽  
Vol 124 (31) ◽  
pp. 6294-6302
Author(s):  
László Zimányi ◽  
Shareefa Thekkan ◽  
Brett Eckert ◽  
Alanna R. Condren ◽  
Olga Dmitrenko ◽  
...  
Keyword(s):  
Singular Value Decomposition ◽  
Singular Value ◽  
Pka Values ◽  
Value Decomposition

Application of error-ranked singular value decomposition for the determination of potential-derived atomic-centered point charges

2009 ◽  
Vol 30 (5) ◽  
pp. 733-742 ◽  
Author(s):  
Jeffrey S. Tan ◽  
Stephan X. M. Boerrigter ◽  
Raymond P. Scaringe ◽  
Kenneth R. Morris
Keyword(s):  
Singular Value Decomposition ◽  
Singular Value ◽  
Value Decomposition

scholarly journals Statistical Ranging of Orbits for Trans-Neptunian Objects

2002 ◽  
Vol 12 ◽  
pp. 255-256 ◽  
Author(s):  
J. Virtanen ◽  
K. Muinonen ◽  
E. Bowell
Keyword(s):  
Phase Space ◽  
A Priori ◽  
Posteriori Probability ◽  
A Posteriori ◽  
A Priori Information ◽  
A Posteriori Probability ◽  
Uncertainty Prediction ◽  
Absolute Magnitudes ◽  
Priori Information

AbstractWe consider initial determination of orbits for trans-neptunian objects (TNOs), a topical theme because of the rapidly growing TNO population and the challenges in recovering lost TNOs. We apply the method of initial phase-space ranging of orbits to the poorly observed TNOs. The rigorous a posteriori probability density of the TNO orbital elements is examined using a Monte Carlo technique by varying the TNO topocentric ranges corresponding to the observation dates. We can optionally adopt a Bayesian approach to select the region of phase space containing the most plausible orbits. This is accomplished by incorporating semimajor axes, eccentricities, inclinations, and absolute magnitudes of multi-apparition TNOs as a priori information. The resulting a posteriori distributions permit ephemeris and ephemeris uncertainty prediction for TNO recovery observations.

scholarly journals Determination of the barycentric velocity of an astrometric satellite using its own observational data

2007 ◽  
Vol 3 (S248) ◽  
pp. 252-255 ◽  
Author(s):  
A. G. Butkevich ◽  
S. A. Klioner
Keyword(s):  
Observational Data ◽  
A Priori ◽  
Translational Motion ◽  
Orbital Velocity ◽  
A Priori Information ◽  
Proposed Model ◽  
Velocity Constraints ◽  
Priori Information ◽  
Astrometric Data

AbstractThe problem of determination of the orbital velocity of an astrometric satellite from its own observational data is studied. It is well known that data processing of microarcsecond-level astrometric observations imposes very stringent requirements on the accuracy of the orbital velocity of satellite (a velocity correction of 1.45 mm/s implies an aberrational correction of 1 μas). Because of a number of degeneracies the orbital velocity cannot be fully restored from observations provided by the satellite. Seven constraints that must be applied on a velocity parameterization are discussed and formulated mathematically. It is shown what part of velocity can be recovered from astrometric data using a combined fit of both velocity parameters and astrometric parameters of the sources. Numerical simulations show that, with the seven constraints applied, the velocity and astrometric parameters can be reliably estimated from observational data. It is also argued that the idea to improve the velocity of an astrometric satellite from its own observational data is only useful if a priori information on orbital velocity justifies the applicability of the velocity constraints. The proposed model takes into account only translational motion of the satellite and ignores any satellite-specific parameters. Therefore, the results of this study are equally applicable to both scanning missions similar to Gaia, and pointing ones like SIM, provided that enough sources were observed sufficiently uniformly.

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