Adaptive multiple subtraction using regularized nonstationary regression
Sergey Fomel, 2010. "Adaptive multiple subtraction using regularized nonstationary regression", Geophysics Today: A Survey of the Field as the Journal Celebrates its 75th Anniversary, Sergey Fomel
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Stationary regression is the backbone of seismic data-processing algorithms including match filtering, which is commonly applied for adaptive multiple subtraction. However, the assumption of stationarity is not always adequate for describing seismic signals. I have developed a general method of nonstationary regression and that applies to nonstationary match filtering. The key idea is the use of shaping regularization to constrain the variability of nonstationary regression coefficients. Simple computational experiments demonstrate advantages of shaping regularization over classic Tikhonov’s regularization, including a more intuitive selection of parameters and a faster iterative convergence. Using benchmark synthetic data examples, I have successfully applied this method to the problem of adaptive subtraction of multiple reflections.
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“In celebration of the 75th year of publication, the Geophysics editorial team invited a collection of papers written by well-recognized experts in various areas of exploration geophysics. These invited papers not only form part of the present book, but they also appear in the September-October 2010 special section of the journal. Geophysics Today: A Survey of the Field as the Journal Celebrates its 75th Anniversary complements this special section with an additional group of papers, drawn from Geophysics during the recent past, that addresses areas the invited articles did not. The result is a snapshot of the state-ofthe- art in the field as Geophysics passes its three-quarter-century mark. This book is Geophysical References Series No. 16.”