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dc.date.accessioned 2019-03-01T18:39:50Z
dc.date.available 2019-03-01T18:39:50Z
dc.date.issued 2017
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/72813
dc.description.abstract We present an algorithm to estimate blocky images of the subsurface acoustic impedance (AI) from seismic reflection data. We use the total variation semi-norm (TV) to regularize the inversion and promote blocky solutions which are, by virtue of the capability of TV to handle edges properly, adequate to model layered earth models with sharp contrasts. In addition, the use of the TV leads to a convex objective function that can be minimized using a gradientbased algorithm that only requires matrix-vector multiplications and no direct matrix inversion. The latter makes the algorithm numerically stable, easy to apply, and economic in terms of computational cost. Besides, given appropriate a priori information, the algorithm allows to easily incorporate into the inversion scheme the low frequency trend that is missing from the data. Numerical tests on noisy 2D synthetic and field data show that the proposed method is capable of providing consistent and blocky AI images that preserve edges and the subsurface layered structure. en
dc.language en es
dc.subject impedancia acústica es
dc.subject algoritmos es
dc.title Acoustic impedance estimation using a gradient-based algorithm with total variation semi-norm regularization en
dc.type Objeto de conferencia es
sedici.creator.person Pérez, Daniel Omar es
sedici.creator.person Velis, Danilo Rubén es
sedici.subject.materias Ciencias Astronómicas es
sedici.description.fulltext true es
mods.originInfo.place Facultad de Ciencias Astronómicas y Geofísicas es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/4.0/
sedici.date.exposure 2017
sedici.relation.event 15th International Congress of the Brazilian Geophysical Society (Río de Janeiro, Brasil, 31 de julio al 3 de agosto de 2017) es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) Except where otherwise noted, this item's license is described as Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)