Seismic Fault Preserving Diffusion

Abstract : This paper focuses on the denoising and enhancing of 3-D reflection seismic data. We propose a pre-processing step based on a non linear diffusion filtering leading to a better detection of seismic faults. The non linear diffusion approaches are based on the definition of a partial differential equation that allows us to simplify the images without blurring relevant details or discontinuities. Computing the structure tensor which provides information on the local orientation of the geological layers, we propose to drive the diffusion along these layers using a new approach called SFPD (Seismic Fault Preserving Diffusion). In SFPD, the eigenvalues of the tensor are fixed according to a confidence measure that takes into account the regularity of the local seismic structure. Results on both synthesized and real 3-D blocks show the efficiency of the proposed approach.
Complete list of metadatas

Cited literature [26 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-00166722
Contributor : Olivier Lavialle <>
Submitted on : Thursday, August 9, 2007 - 9:18:48 AM
Last modification on : Monday, November 26, 2018 - 1:30:05 PM
Long-term archiving on : Monday, June 27, 2011 - 4:44:57 PM

File

SFPD.pdf
Files produced by the author(s)

Identifiers

Citation

Olivier Lavialle, Sorin Pop, Christian Germain, Marc Donias, Sebastien Guillon, et al.. Seismic Fault Preserving Diffusion. Journal of Applied Geophysics, Elsevier, 2007, 2007 (61), pp.132-141. ⟨10.1016/j.jappgeo.2006.06.002⟩. ⟨hal-00166722⟩

Share

Metrics

Record views

318

Files downloads

269