Mejoramiento de la imagen en RTM (Reverse time migration) usando transformaciones integrales.
Reverse time migration image improvement using integral transforms. Juan Guillermo Paniagua Castrillón; PhD student in Mathematical Engineering, GRIMMAT – Research group in mathematical modeling, EAFIT University. Marzo 7 de 2016.
Speaker: Juan Guillermo Paniagua Castrillón
Affiliation: PhD student in Mathematical Engineering, GRIMMAT – Research group in mathematical modeling, EAFIT University
Talk title: Reverse time migration image improvement using integral transforms
Linear integral transforms can be described as a representation of one space into another space. These integral transforms have been used in different fields of knowledge such as applied mathematics, mathematical physics and engineering science. They have been applied in solving several problems in fluid mechanics, signal processing, electronics, quantum mechanics, viscoelaticity, seismic signal analysis, among other areas. Some problems in Geophysics (Such as Phase shift migration and Kirchhoff migration) can be solved through the use of integral transforms.
The imaging condition in reverse time migration (RTM) is one of them.
RTM is achieved by a forward and a reverse time propagation of source and receiver wavefields respectively, obtained by modeling the acoustic wave equation and followed by applying some criteria known as imaging condition. The cross-correlation in time between source and receiver wavefields is the commonly used imaging condition. This imaging condition produces spatial low frequency noise (Artifacts) due to the backscattered correlation between the source and receiver wave-fields. Different techniques and other imaging conditions have been used to remove these artifacts (Valenciano and Biondi, 2003 Kaelin et al, 2006, Guitton, 2007, Liu, 2011, Whitmore, 2012, Pestana et al, 2013, Shragge, 2014, Youn, 2001, Guitton et al, 2006, among others).
In this seminar, we propose a post-imaging approach, based on linear integral transforms, the Riesz and Laguerre-Gauss transforms, which excludes high frequency spatial components and the low frequency noise, reducing artifacts and enhance the edges on a reflective events in the RTM images.
The Laguerre-Gauss spatial filter allows for performing a Radial Hilbert transform with high contrastive and isotropic edge enhancement without resolution loss. The spatial low frequency noise around the enhanced edges is largely suppressed.