Amplitude analysis with an optimal model-based linear AVO approximation: Part I — Theory

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. C59-C69 ◽  
Author(s):  
E. Causse ◽  
M. Riede ◽  
A. J. van Wijngaarden ◽  
A. Buland ◽  
J. F. Dutzer ◽  
...  

Linear equations used to approximate reflection coefficient-versus-angle curves are usually valid only for small seismic parameter changes across reflectors, and they are rather inaccurate close to the critical angle. These inaccuracies affect the quality of AVO analysis and cause systematic errors when estimating relative seismic-parameter variations at reflectors, especially for density. We present an optimal model-based approach to build more accurate linear AVO approximations. Their basis functions are calculated by applying singular value decomposition to realistic modeled AVO curves. By extending the validity range of linear approximations to larger angles, this approach helps when using information contained at near-critical offsets. It alsooffers several advantages in other situations. The basis functions of the new approximations are orthogonal. Their coefficients represent new AVO attributes that can be used either to classify AVO responses directly, or to obtain more accurate estimates of usual AVO attributes (intercept, gradient, and possibly a third coefficient). This leads to a better estimation of seismic-parameter contrasts at reflecting interfaces. These coefficients are naturally sorted in decreasing order of importance. Therefore, the proper number of terms in the proposed equations can be chosen easily to offer an optimal compromise between noise and the information carried by each coefficient. Synthetic tests confirm the robustness of the method. This flexible and robust approach will be particularly well adapted for three-parameter AVO analysis.

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. C71-C79 ◽  
Author(s):  
E. Causse ◽  
M. Riede ◽  
A. J. van Wijngaarden ◽  
A. Buland ◽  
J. F. Dutzer ◽  
...  

AVO analysis can be conducted by estimating amplitude variation with offset (AVO) attributes from seismic prestack data and by characterizing the measured amplitude responses by the position of their projection in the attribute space. The most common AVO attributes are the intercept (zero-offset reflectivity) and AVO gradient. We have constructed an optimized, model-based linear AVO equation that is more accurate than usual AVO approximations. The parameters of this equation represent new AVO attributes that are more directly related to the information contained in seismic reflection amplitudes. We use these new AVO attributes to classify reflector responses from field data. Five seismic facies are defined that are characterized by differentdistributions of seismic parameters. Nine reflector classes are formed by associating appropriate pairs of facies. The expected locations of the different reflector classes in the space of optimized attributes are found by modeling and are used to derive a classification scheme. This scheme is applied to sections of optimized attributes calculated from the prestack data, leading to a vertical section showing the distribution of most probable facies in an area containing a sand reservoir. We compare the new approach to classification with intercept and gradient. The new method is more robust and less sensitive to the number of attributes (two or three) used for classification. It offers an optimal, flexible, and robust way of extracting the information contained in reflection amplitudes by simple linear AVO equations.


2014 ◽  
Vol 2014 ◽  
pp. 1-5
Author(s):  
Guohua Wang ◽  
Yufa Sun

A broadband radar cross section (RCS) calculation approach is proposed based on the characteristic basis function method (CBFM). In the proposed approach, the desired arbitrary frequency band is adaptively divided into multiple subband in consideration of the characteristic basis functions (CBFs) number, which can reduce the universal characteristic basis functions (UCBFs) numbers after singular value decomposition (SVD) procedure at lower subfrequency band. Then, the desired RCS data can be obtained by splicing the RCS data in each subfrequency band. Numerical results demonstrate that the proposed method achieve a high accuracy and efficiency over a wide frequency range.


2001 ◽  
Vol 123 (5) ◽  
pp. 884-891 ◽  
Author(s):  
Francis H. R. Franc¸a ◽  
Ofodike A. Ezekoye ◽  
John R. Howell

This work investigates inverse boundary design for radiation, convection and conduction combined-mode heat transfer. The problem consists of finding the heat flux distribution on a heater that satisfies both the temperature and the heat flux prescribed on a design surface of an enclosure formed by two finite parallel plates. A gray participating medium flows in laminar regime between the walls, which are gray, diffuse emitters and absorbers. All the thermal properties are uniform. This problem is described by an ill-conditioned system of non-linear equations. The solution is obtained by regularizing the system of equations by means of truncated singular value decomposition (TSVD).


2007 ◽  
Vol 05 (01) ◽  
pp. 79-104 ◽  
Author(s):  
ERIK ANDRIES ◽  
THOMAS HAGSTROM ◽  
SUSAN R. ATLAS ◽  
CHERYL WILLMAN

Linear discrimination, from the point of view of numerical linear algebra, can be treated as solving an ill-posed system of linear equations. In order to generate a solution that is robust in the presence of noise, these problems require regularization. Here, we examine the ill-posedness involved in the linear discrimination of cancer gene expression data with respect to outcome and tumor subclasses. We show that a filter factor representation, based upon Singular Value Decomposition, yields insight into the numerical ill-posedness of the hyperplane-based separation when applied to gene expression data. We also show that this representation yields useful diagnostic tools for guiding the selection of classifier parameters, thus leading to improved performance.


Author(s):  
Zhong-Gen Wang ◽  
Jun-Wen Mu ◽  
Wen-Yan Nie

In this paper, a merged ultra-wideband characteristic basis function method (MUCBFM) is presented for high-precision analysis of wideband scattering problems. Unlike existing singular value decomposition (SVD) enhanced improved ultra-wideband characteristic basis function method (SVD-IUCBFM), the MUCBFM reduces the number of characteristic basis functions (CBFs) necessary to express a current distribution. This reduction is achieved by combining primary CBFs (PCBFs) with the secondary level CBFs (SCBFs) to form a single merged ultra-wideband characteristic basis function (MUCBF). As the MUCBF incorporates the effects of PCBFs and SCBFs, the accuracy does not change significantly compared to that obtained by the SVD-IUCBFM. Furthermore, the efficiencies of constructing the CBFs and filling the reduced matrix are improved. Numerical examples verify and demonstrate that the proposed method is credible both in terms of accuracy and efficiency.


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