Multisource encoding and decoding using the signal apparition technique
(2018) In Geophysics 83(1). p.4959 Abstract
Signal apparition is a method for encoding sources in simultaneous multisource seismic acquisition and decoding the multisource response of the earth into its singlesource responses. For M sources, encoding is performed by applying periodic sequences of period M to each of the sources along source lines. Decoding is achieved in the wavenumber domain for each frequency by solving an M × M linear system of equations. The system's matrix is the product of a Fourier matrix and an encoding matrix, the latter containing the information of the codes. The solution of the system is unique when the encoding matrix is invertible. When the encoding sequences consist of time delays applied to sources' firing times, the determinant of the encoding... (More)
Signal apparition is a method for encoding sources in simultaneous multisource seismic acquisition and decoding the multisource response of the earth into its singlesource responses. For M sources, encoding is performed by applying periodic sequences of period M to each of the sources along source lines. Decoding is achieved in the wavenumber domain for each frequency by solving an M × M linear system of equations. The system's matrix is the product of a Fourier matrix and an encoding matrix, the latter containing the information of the codes. The solution of the system is unique when the encoding matrix is invertible. When the encoding sequences consist of time delays applied to sources' firing times, the determinant of the encoding matrix becomes a polynomial. A unique solution to decoding then exists if the roots of the polynomial avoid the unit circle. Periodic timeshift sequences for two, three, four, and six sources are discussed. A model example of simultaneous foursource data acquisition illustrates the performance of the encoding/decoding technique for the spatially nonaliased case.
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 author
 Amundsen, Lasse ; Andersson, Fredrik ^{LU} ; van Manen, Dirk Jan ; Robertsson, Johan O.A. and Eggenberger, Kurt
 organization
 publishing date
 20180101
 type
 Contribution to journal
 publication status
 published
 subject
 in
 Geophysics
 volume
 83
 issue
 1
 pages
 49  59
 publisher
 Soc Exploration Geophysicists
 external identifiers

 scopus:85038122909
 ISSN
 00168033
 DOI
 10.1190/GEO20170206.1
 language
 English
 LU publication?
 yes
 id
 564e8786734040c5b4104407afc48c48
 date added to LUP
 20180103 07:47:55
 date last changed
 20211006 02:00:25
@article{564e8786734040c5b4104407afc48c48, abstract = {<p>Signal apparition is a method for encoding sources in simultaneous multisource seismic acquisition and decoding the multisource response of the earth into its singlesource responses. For M sources, encoding is performed by applying periodic sequences of period M to each of the sources along source lines. Decoding is achieved in the wavenumber domain for each frequency by solving an M × M linear system of equations. The system's matrix is the product of a Fourier matrix and an encoding matrix, the latter containing the information of the codes. The solution of the system is unique when the encoding matrix is invertible. When the encoding sequences consist of time delays applied to sources' firing times, the determinant of the encoding matrix becomes a polynomial. A unique solution to decoding then exists if the roots of the polynomial avoid the unit circle. Periodic timeshift sequences for two, three, four, and six sources are discussed. A model example of simultaneous foursource data acquisition illustrates the performance of the encoding/decoding technique for the spatially nonaliased case.</p>}, author = {Amundsen, Lasse and Andersson, Fredrik and van Manen, Dirk Jan and Robertsson, Johan O.A. and Eggenberger, Kurt}, issn = {00168033}, language = {eng}, month = {01}, number = {1}, pages = {4959}, publisher = {Soc Exploration Geophysicists}, series = {Geophysics}, title = {Multisource encoding and decoding using the signal apparition technique}, url = {http://dx.doi.org/10.1190/GEO20170206.1}, doi = {10.1190/GEO20170206.1}, volume = {83}, year = {2018}, }