Q estimation by combining ISD with LSR method based on shaping-regularized inversion

Luo, Cong; Huang, Guantan; Li, Xiangyang; Wei, Qing. 2019 Q estimation by combining ISD with LSR method based on shaping-regularized inversion. IEEE Geoscience and Remote Sensing Letters, 16 (9). 1457-1461. https://doi.org/10.1109/LGRS.2019.2900732

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Official URL: http://dx.doi.org/10.1109/LGRS.2019.2900732

Abstract/Summary

The quality factor Q is an indispensable parameter for studying wave propagation in viscoelastic media. Q can not only be implemented for improving the quality of wave records but can also be used for directly indicating frequency-dependent anomalies induced by fluids, so it is widely used in seismic exploration and clinical medicine. Q estimation here refers to the extraction of Q information from seismic data; it has aroused lots of attention but is still somewhat controversial due to the limitations of existing methods. In this letter, combined with a logarithmic spectral ratio (LSR) algorithm, we have introduced a sparse-constrained inversion spectral decomposition (ISD) method for average-Q estimation (LSR-ISD), and have used shaping regularization to solve for the spectrum ratio. Then, through regularized linear inversion, average-Q was converted to an interval-Q value. Finally, we have applied this method to synthetic data and field data. Numerical examples and field data application demonstrate that the proposed method produces a series of results with high resolution and good stability.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1109/LGRS.2019.2900732
ISSN:	1545-598X
Date made live:	09 Dec 2019 14:20 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/526143

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1109/LGRS.2019.2900732

ISSN:

1545-598X

Date made live:

09 Dec 2019 14:20 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/526143