+ Site Statistics
+ Search Articles
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ PDF Full Text
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Translate
+ Recently Requested

New ARMA deconvolution method using least squares inversion techniques

New ARMA deconvolution method using least squares inversion techniques

SEG Abstracts 60(Pages 1687-1688

In seismics, the most accepted model for the generation of a seismic trace is the convolutional model. A new ARMA deconvolution method which utilizes only output data is presented. This new method is based on the Canonical Representation Theorem (1), and the ARMA spectrum estimation method (2). The combination of these two theories allows us to represent the seismic trace in a simplified manner, this type of representation decomposes the trace into three parts: an all-pass component, a minimum-phase wavelet and a series of reflection coefficients. Once decomposed the trace in this manner, spiking deconvolution is applied in order to eliminate the minimum-phase component and, then, the new deconvolution method is applied. This new method allows us to estimate and to eliminate the all-pass component giving as a result the desired information: the reflection coefficients. The algorithm developed to implement this new method was tested and applied to seismic data, obtaining very satisfactory results. The results were compared with those obtained from the application of the conventional spiking deconvolution method. This comparison leads us to conclude that the new method can improve the resolution of the data. The major contribution of this new deconvolution method is that it keeps a very efficient and simple computational level, offering results of much better quality than those obtained in conventional form, and, without having to keep the assumption of a minimum-phase input wavelet.

(PDF emailed within 1 workday: $29.90)

Accession: 019511158

Download citation: RISBibTeXText

Related references

Constrained least-squares restoration and renogram deconvolution: a comparison with other techniques. Physics in Medicine and Biology 38(8): 1043-1050, 1993

Matrix-inversion method: Applications to Möbius inversion adn deconvolution. Physical Review. E, Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics 52(6): 6055-6065, 1995

An inequality-constrained least-squares deconvolution method. Journal of Pharmacokinetics and Biopharmaceutics 17(2): 269-289, 1989

Comparison of five least-squares inversion techniques in resistivity sounding. Geophysical Prospecting 30(5): 688-715, 1982

Mean input times of three oral chlorprothixene formulations assessed by an enhanced least-squares deconvolution method. Journal of Pharmaceutical Sciences 85(4): 434-439, 1996

Weighted least-squares deconvolution method for discovery of group differences between complex biofluid 1H NMR spectra. Journal of Magnetic Resonance 183(2): 269-277, 2006

The least-squares and the Whittaker-Robinson-Vondrak method of filter design in the complex deconvolution of data series. Marees Terrestres Bulletin d'Informations, 1992

Novel approach to bioavailability testing: statistical method for comparing drug input calculated by a least-squares deconvolution technique. Journal of Pharmaceutical Sciences 69(3): 318-324, 1980

A novel method for fast and robust estimation of fluorescence decay dynamics using constrained least-squares deconvolution with Laguerre expansion. Physics in Medicine and Biology 57(4): 843-865, 2012

L1 norm inversion method for deconvolution in attenuating media. Geophysical Prospecting 61(4): 771-777, 2013

The matrix inversion iteration method for L (sub 1) norm deconvolution. Shiyou Diqiu Wuli Kantan = Oil Geophysical Prospecting 23(5): 523-532, 1988

Numerical methods in fluorescence deconvolution of single tryptophan protein data containing systematic errors a comparison between the method of moments and least squares. Biophysical Journal 47(2 PART 2): 410A, 1985

Least squares 2-D inversion method for induced polarization data. Earth Science Journal of China University of Geoscience, 1999

Three-dimensional linear gravity inversion using an iterative stochastic least squares method. Eos, Transactions, American Geophysical Union 73(14, special supplement): 82, 1992

Rapid least-squares inversion of apparent resistivity pseudosections by a quasi-Newton method. Geophysical Prospecting 44(1): 131-152, 1996