SEQUENTIAL DECONVOLUTION OF TIME VARYING SEISMIC SIGNAL MODELS.

Kollias, Stefanos; Foudopoulos, Panayotis; Halkias, Christos

dc.contributor.author	Kollias, Stefanos	en
dc.contributor.author	Foudopoulos, Panayotis	en
dc.contributor.author	Halkias, Christos	en
dc.date.accessioned	2014-03-01T02:47:36Z
dc.date.available	2014-03-01T02:47:36Z
dc.date.issued	1984	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/33265
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0021563382&partnerID=40&md5=f63ee35f42665e59e6bb203a24999a5f	en
dc.subject.other	COMPUTER PROGRAMMING - Algorithms	en
dc.subject.other	SEISMOLOGY	en
dc.subject.other	AUTOREGRESSIVE MOVING-AVERAGE MODELS	en
dc.subject.other	MINIMUM VARIANCE DECONVOLUTION	en
dc.subject.other	MULTIPLE-REFLECTION SUPPRESSION	en
dc.subject.other	SEQUENTIAL SEISMIC DECONVOLUTION	en
dc.subject.other	TIME-VARYING SEISMIC SIGNALS	en
dc.subject.other	SIGNAL PROCESSING	en
dc.title	SEQUENTIAL DECONVOLUTION OF TIME VARYING SEISMIC SIGNAL MODELS.	en
heal.type	conferenceItem	en
heal.publicationDate	1984	en
heal.abstract	The problem of sequential seismic deconvolution and suppression of multiple reflections is examined in this paper. An ARMA model is used to represent the unknown and probably time varying seismic wavelet, while the reflectivity sequence of the earth is modelled as a white sparse spike train. The method uses a fixed-lag version of minimum variance deconvolution, while an instrumental variable algorithm updates the model parameters. The above model is appropriately combined with a time domain state space earth model, which constructs and removes the part of the signal containing all significant multiple effects. An example is given, which illustrates the above results.	en
heal.publisher	North-Holland, Amsterdam, Neth	en
heal.journalName	[No source information available]	en
dc.identifier.spage	652	en
dc.identifier.epage	655	en