Doctoral Dissertations

Abstract

"The object of this study is the investigation of a linear threshold element technique for identifying surface multiples on a single seismic trace. Traces of seismic events were generated which contained primaries, surface multiples, and various levels of Gaussian random noise. Since it was necessary to separate the events as much as possible, the traces were subjected to pulse-compression deconvolution processing prior to LTE analysis. Mean frequency, peak frequency, amplitude spectrum variance, periodicity, and polarity were employed as pattern parameters. A set of weights was found that would maximize the moment of inertia of the S line distribution of the patterns subject to the constraint that the sum of the squared values of the weights was minimized. It is shown that the problem of the maximization of the moment of inertia reduces to the solution of a simple eigenvalue problem. Furthermore, the optimum set of weights is the eigenvector corresponding to the largest eigenvalue of a matrix proportional to the autocovariance matrix of the pattern vectors. The classes of patterns representing primaries and multiples on traces with high signal-to-noise ratios were clustered and separated, making identification by inspection a simple procedure. Clustering and separation of classes on traces with low signal-to-noise ratios was less than optimum"--Abstract, page ii.

Advisor(s)

Zenor, Hughes M., 1908-2001

Committee Member(s)

Betten, J. Robert
Carlile, Robert E.
Bain, Lee J.
Rupert, Gerald B., 1930-2016
Robinson, John C.

Department(s)

Geosciences and Geological and Petroleum Engineering

Degree Name

Ph. D. in Geophysical Engineering

Publisher

University of Missouri--Rolla

Publication Date

1970

Pagination

viii, 93 pages

Note about bibliography

Includes bibliographical references (pages 87-92).

Rights

© 1970 David Nuse Peacock, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Subject Headings

MicroseismsSeismic reflection methodEstimation theoryNoise control

Thesis Number

T 2366

Print OCLC #

6020060

Electronic OCLC #

850573774

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