FairfieldNodal's excellent nodal adventure

Mitchell, Steve; Ray, Cliff; Marc, Etienne; Hays, David; Craft, Kenneth L.

doi:10.1190/1.3513628

Cited by 5 publications

(1 citation statement)

References 16 publications

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“…We assume that the seismic record is blended using two independent sources that correspond to two shooting vessels in the oceanbottom node (OBN) acquisition (Mitchell et al, 2010). Here, one source means a collection of shots from one shooting vessel.…”

Section: Numerical Blendingmentioning

confidence: 99%

Iterative deblending of simultaneous-source seismic data using seislet-domain shaping regularization

2014

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We used a novel iterative estimation scheme for separation of blended seismic data from simultaneous sources. The scheme is based on an augmented estimation problem that can be solved by iteratively constraining the deblended data using shaping regularization in the seislet domain. We formulated the forward modeling operator in the commonreceiver domain, in which two sources were assumed to be blended using a random time-shift dithering approach. The nonlinear shaping-regularization framework offered some freedom in designing a shaping operator to constrain the model in an underdetermined inverse problem. We designed the backward operator and the shaping operator for the shaping-regularization framework. The backward operator can be optimally chosen as half of the identity operator in the two-source case, and the shaping operator can be chosen as coherency-promoting operator. The high performance deblending effect of the iterative framework was tested on three numerically blended synthetic data sets and one numerically blended field data set. Compared with alternative f-k domain thresholding and f-x predictive filtering, seislet-domain soft thresholding exhibits the most robust behavior.

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Section: Numerical Blendingmentioning

confidence: 99%